Abstract SubmissionsGrad Student Travel Grants
to UCGIS Summer Assembly 2000
Ram Alagan, Department of Geology and Geography, West Virginia
University, West Virginia 26506. E-mail: ralagan@geo.wvu.edu.
GIS and Natural Resources: Exploring Social Struggles in the
Knuckles Forest, Sri Lanka
Forest management is a systematic endeavor to both minimize the adverse
effects caused by people on the environment, and maximize the benefits
of forestlands to society. Over the past century Sri Lanka's
forestlands have been reduced from 80% to 17% of land cover. The major
causes of this denudation were brought about by colonization, growing
demand for timber, extension of agricultural land, settlement expansion,
and the growth of tourism. Several forest management agencies in Sri
Lanka have adopted GIS as part of their forest management strategy.
However, most have been criticized due to the imposition of top-down
technical solutions on local communities. To explore these dramatic
changes and the impact of GIS-based forest management strategies a case
study is presented of Knuckles Forest, the second largest forest in Sri
Lanka. The day-to-day struggles for survival experienced by the local
communities of Knuckles Forest have contributed to the general
degradation of the forest ecosystem and created tensions between local
communities and government agencies as both contest forest resources.
Technological solutions generated using GIS have become a critical focus
of this debate. This paper examines (1) the struggle between government
and local communities over Knuckles Forest, (2) evaluates the pivotal
change in power relations brought about by the use of GIS in forest
management and, (3) proposes alternative approaches to consensus
building and integrated societal land-use management strategies for
Knuckles Forest.
Key words: GIS, Knuckles Forest, social struggle
BACK TO LIST OF TRAVEL GRANTS
1. Amy J. Liu*, Susanna T.Y. Tong, James A. Goodrich
*student
2. Geography Department, University of Cincinnati
3. 70 Pickett's Charge, #69, Fort Thomas, KY 41075
4. Phone: 606-442-0580; Fax: 513-556-3370; E-mail: liu_amy@msn.com
5. Title: Using land use as a mitigation strategy for the water quality
impacts of global warming: A scenario analysis on two watersheds in the
Ohio River Basin
6. Abstract
This study uses an integrative approach to study the water quality
impacts of future global climate and land use changes. In this study,
changing land use types was used as a mitigation strategy to reduce the
adverse impacts of global climate change on water resources. The climate
scenarios were based on projections made by the Intergovernmental Panel of
Climate Change (IPCC) and the United Kingdom Hadley Centre=s climate model
(HadCM2). The Thornthwaite water balance model was coupled with a land use
model (L-THIA) to investigate the hydrologic effects of future climate and
land use changes in the Ohio River Basin. The land use model is based on
the Soil Conservation Service’s curve number method. It uses the curve
number, an index of land use and soil type, to calculate runoff volume and
depth. The ArcView programming language, Avenue, was used to integrate the
two models into a geographic information system (GIS). An output of the
water balance model, daily precipitation values adjusted for potential
evapotranspiration, served as one of the inputs into the land use model.
Two watersheds were used in the present study: one containing the city of
Cincinnati on the mainstem of the Ohio River, and one containing the city of
Columbus on a tributary of the Ohio River. These cities represent two major
metropolitan areas in the Ohio River Basin with different land uses
experiencing different rates of population growth. The projected
hypothetical land use changes were based on linear extrapolations of current
population data.
Results of the analyses indicate that conversion from agricultural land
use to low-density residential land use decreases the amount of surface
runoff by approximately 43% in Cincinnati, and 32% in Columbus. The land
use practices which generate the least amount of runoff are forest,
low-density residential, and agriculture; whereas high-density residential
and commercial land use types produce the highest runoff. The hydrologic
soil type present was also an important factor in determining the amount of
runoff and non-point source pollution. A runoff depth matrix and total
nitrogen matrix were created for Cincinnati and Columbus to describe
possible land use mitigation measures in response to global climate change.
The differences in Cincinnati and Columbus were due to differences in
geographic location, air temperature, and total runoff. The results of this
study will be useful to planners and policy makers for defining the possible
impacts of future global climate and land use changes on water resources.
BACK TO LIST OF TRAVEL GRANTS
1. John Greenwood Cloud
2. Geography Department, University of California at Santa Barbara
3. Geography Department, University of California at Santa Barbara,
Santa Barbara, CA 93106
4. Phone 805-963-1632; Fax 805-893-7782; email: cloud9@geog.ucsb.edu
5. Hidden in Plain Sight: The Clandestine Histories of GIS
6. Future progress in Geographic Information Science will be grounded
in a deeper understanding of the science's origins and early history, a
subject that has been curiously ignored in extant GIS scholarship. The
majority of present geographic science technologies were devised during
the Second World War and the Cold War. The histories of GIS are
complexly entangled with global geopolitics and the most secret
technologies and programs in modern history. My dissertation research
on the geographic applications of the declassified CORONA reconnaissance
satellite program (1958-72) and the World Geodetic System has disclosed
the complex and creative roles played by classified military and
intelligence research and applications in the creation of modern GIS.
Orthodox histories of GIS have missed much because they begin
somewhere in the middle of the story. Salient stages of that story
include: the development of sophisticated analytical use of
co-registered thematic map overlays, not as disembodied techniques but
as tools inbedded in specific
social structures addressed to social and environmental change; the
rapid and complex postwar evolutions of analog and digital computation,
particularly oriented to graphics and display; the analog to digital
transition in geodata, which was grounded in the veritable revolution in
geodesy that made the World Geodetic System one of the key intellectual
achievements of the Cold War; the beginnings of global geo-referenced
remote sensing databases and modern digital cartography in top secret
reconnaissance and cartography programs; and only then the origin and
evolution of large publicly acknowledged geo-databases and digital
algorithmic implementation of traditional and novel cartographic
processes (the locii of almost all extant GIS history); the
corporatization of GIS practice; a wide variety (and varying quality) of
critiques of GIS; and evolving contestation and re-construction of GIS.
My UCGIS paper will focus on the decades of GIS history BEFORE the
Canadian Geographic Information System and cartographic algorithm
developments at the Harvard School of Design. GIS pioneers range from
the studiously ignored brilliant British planner Jaqueline Tyrwhitt
through Nazi spatial theorists (including Walter Christaller) to the
applications of CORONA to clandestine georeferencing of the planet. The
history of GIS is deeper, much darker, and altogether more interesting
than has been recognized thus far.
BACK TO LIST OF TRAVEL GRANTS
1. Full name: Tarig Abdelgayoum Ali
2. Name of department and university: Department of Civil & Environmental Engineering and Geodetic Science, The Ohio State
University
3. Mailing address:
Department of Civil & Environmental Engineering and Geodetic Science
The Ohio State University
470 Hitchcock Hall, 2070 Neil Avenue
Columbus, OH 43210-1275
4. Phone, fax, e-mail:
Tel: (614) 292-4303 "Office"
Tel: (614) 431-0238 "Home"
E-mail: ali.50@osu.edu
5. Title of poster/paper presentation:
A large-scale GIS backward-tracking method for modeling contaminated sediments transport in Lake Erie Erie coastal areas
6. The abstract:
This paper presents the results of an on-going research for monitoring soil erosion and modeling contaminated sediments
transport using a large-scale spatio-temporal approach. The research has made use of periodical aerial photographs to monitor
terrain surface and shoreline changes and to model soil runoff and direct soil discharge from the eroded shoreline. Estimation of
the amount of contaminated sediments transported in the study area and its impact is also studied here. Aerial photographs
acquired by the National Geodetic Survey of NOAA and GPS ground survey data by OSU are used for photogrammetric
adjustment and for extracting terrain surface model and shoreline. The soil erosion modeled here mainly caused by
precipitation-based runoff and the direct soil discharge resulted from shoreline-bluff erosion. The sediment-transport model
developed in this research, is obtained by adopting a backward-tracking approach that uses the measured sediment load
values at the study area outlet, and the surface flow runoff model to find-out on a cell-by-cell basis the contribution of each cell
in the study area to the gage station. While previous models could not be used to estimate the actual soil loss (in terms of
transported sediment) or to get the actual spatial soil-loss/soil-gain relationship, our model accounts for the actual soil loss as
measured at the study area gage. A phosphorus concentration model is developed using a backward-tracking approach based
on the resulted surface runoff model and a parameterized cross-entities relationship model. Another phosphorus concentration
model for the area is developed using the expected phosphorus concentration values associated with different land-use
categories in the study area. The comparison between the two phosphorus transport models and the analysis of phosphorus
loads measured at the gage station and the phosphorus models values shows that it is not always accurate to assume
specific-range of expected phosphorus concentration associated with land-use categories. Moreover it is found as a result of
this research that phosphorus concentration is not only a function in land uses or soil types, but is also a function in other spatial
factors. One of the important results of the research besides, is the weak spatial correlation that has been found between the
soil discharge and the corresponding phosphorus concentration transport by surface runoff. This testifies that, phosphorus
concentration is not a factor in the soil loss function, at least for this study area. Temporal event-based climatic precipitation
grids are created from the digital precipitation model PRISM and are treated as time-pounded individual layers to represent
their temporal information. Using the Arc/Info weighted flow-accumulation function, the runoff model as been generated using
the precipitation grids resulted from PRISM and USGS stream flow data. The significance of this research?s results is clearly
depicted on the set of large-scale models developed here that we anticipate to be used as analytical tools for the assessment
of water quality parameters and for modeling and predicting coastal terrain models and shoreline changes in coastal areas.
BACK TO LIST OF TRAVEL GRANTS
1. Jeremy Mennis
2. Department of Geography, Pennsylvania State University
3. 302 Walker Building, University Park, PA 16802
4. Phone: (814) 865-6421, Fax: (814) 863-7943, Email: jmennis@gis.psu.edu
5. Integrating Cognitive Principles in GIS Database Representation
6. Abstract
The UCGIS has previously recognized the need for developing GIS database
representations that are more closely aligned with the way that people
conceptualize geographic domains (UCGIS, 1996). The research presented
here addresses this research goal by describing the design, and initial
efforts at implementation, of a GIS database model that is informed by the
principles of geographic cognition. The objectives for this database model
are three-fold: 1) to efficiently manage and integrate diverse sets of
spatiotemporal observational data so that those data may be queried,
visualized, and entered into statistical analyses, 2) to allow for the
explicit representation of geographic entities, processes, and
relationships in a manner that is intuitive and useful to the researcher,
and 3) to facilitate the exploration and analysis of spatiotemporal data
sets in a manner that supports cognitive processes of geographic knowledge
acquisition.
The database model proposed here uses object-oriented modeling and
artificial intelligence (AI) knowledge representation techniques to
integrate principles of geographic cognition into GIS database
representation. This database model is composed of two separate, yet
interrelated parts, the Data Component and the Knowledge Component. The
Data Component can be conceptualized as a multidimensional,
spatiotemporally referenced 'hypercube' of observational data that is akin
to the 'feature space' concept commonly cited in the analysis of remote
sensing imagery. The Knowledge Component stores information about
higher-level semantic 'objects,' the geographic entities or processes that
are described by the data, as well as categorical hierarchies, rule-bases,
and other semantic information that may be associated with the
observational data. A detailed conceptual overview of the proposed
database model can found in Mennis et al. (forthcoming; see an online
version of this paper at www.geovista.psu.edu/publications/mennis/cogdb.html).
User interaction with the proposed database implementation will be provided
through integration with the GeoVista Studio, an interactive,
spatiotemporal data visualization and analysis tool set being developed at
Pennsylvania State University's geographic visualization research center,
the GeoVista Center (www.geovista.psu.edu). In order to evaluate the
utility of the proposed database model, a case study database
implementation will focus on the spatiotemporal analysis of storm events in
the Susquehanna River Basin in central Pennsylvania using an approximately
1.7 gigabyte spatiotemporal meteorological data set. The database model is
being developed using the object-oriented database POET, by Poet Software
(San Mateo, California), running on Windows NT. The visual modeling
language UML (Unified Modeling Language) is being used to specify and
design the database in the Java programming language. A preliminary
version of the Data Component has been implemented thus far, and current
efforts focus on linking the Data Component with the GeoVista Studio as
well as the design, specification, and coding of the Knowledge Component in
UML and Java.
References
Mennis, J.L., Peuquet, D.J., and Qian, L., forthcoming. A conceptual
framework for incorporating cognitive principles into geographic database
representation. International Journal of Geographical Information Science.
UCGIS (University Consortium for Geographic Information Science), 1996.
Research Priorities for Geographic Information Science. Cartography and
Geographic Information Systems 23(3):115-127.
BACK TO LIST OF TRAVEL GRANTS
1. Full name
Soe Win Myint
2. Name of department and university
Department of Geography and Anthropology, Louisiana State University
3. Mailing address
Dept. of Geography and Anthropology
230 Howe/Russell Geoscience Complex
Louisiana State University
Baton Rouge, LA 70803 - 4105
4. Phone, fax, e-mail
(Off.) 225 388 6132
(Lab.) 225 388 6119
(Res.) 225 334 5008
Fax: 225 388 4420
Email: swmyint@lsu.edu
5. Title of poster/paper presentation
Image texture analysis with high-resolution airborne data using wavelet
transform.
Abstract
Advanced Thermal and Land Applications Sensor (ATLAS) image data at 10 m
spatial resolution acquired with 15 channels (0.45 m - 12.2 m) was used for
this research. The data was collected by a NASA Lear Jet flying at 16,500
feet over Baton Rouge, Louisiana, on May 11, 1998. The research is to
examine the utility of innovative classification approach such as wavelet
transforms in tracking urban features from high-resolution multispectral
data. Traditional image classification methods, such as maximum likelihood
classifiers use spectral information (pixel values) as a basis to analyze
and classify remote sensing images. To extract the heterogeneous nature of
urban features in high-resolution images, we need the information contained
in a group of pixels instead of individual spectral values. One of the key
obstacles to extracting texture information has been the lack of an
adequate method to effectively characterize different scales of texture.
Recent development in spatial/frequency analysis of wavelet transfor
ms help to overcome this difficulty. This paper introduces the use of
wavelet transform as to characterize image textures at multiple scales. The
performances of wavelet transforms were measured for the classification of
8 different land cover classes derived from the ATLAS data. Different
wavelet decomposition models, sample sizes, and channels, and mother bodies
of the same features were experimented and examined. These 8 classes
include residential-1 (single family homes with < 30% tree canopy),
residential-2 (single family homes with between 30 - 60% tree canopy),
residential-3 (single family homes with > 60% tree canopy), dense
vegetation, commercial and offices, water bodies, bare soil prepared for
agriculture, and agriculture land with crops. The channels and index
selected for this study include channel 2 (0.52 - 0.60 micrometer:
visible), channel 6 (0.76 - 0.93 micrometer: reflected infrared), channel
13 (9.60 - 10.2 micrometer: thermal infrared), and normalized difference
vegetation index (NDVI) com
posite image. Samples of different sizes (45x45, 23x23, and 13x13) were
used in the study. Five texture samples of each size for each texture class
were extracted for wavelet analysis. From the standard wavelet
decomposition, it is understood that further decomposition is done using
the low frequency channels. However, the most important information for
texture appears in the high frequency channels (the detail sub-bands).
Thus, we up-sampled the first level detail sub-images. In this study, the
further decomposition is carried out in the horizontal edge and the
reconstructed image of the first level three detail images plus the
standard decomposition. Haar, Daubechies, and Mallat wavelets were used in
this study. The geometric mean vectors of sub-images of a sample mean and
entropy were used as a total feature vector of the samples. The performance
of a minimum distance classifier was evaluated for texture classification.
Wavelet representations for urban texture feature types were classified
with very few e
rrors. The reliability exhibited by texture signatures of wavelet
transforms is beneficial for accomplishing high-resolution image
classification.
Key words: wavelet transform, multi-resolution, entropy, texture, urban
landscape, remote sensing.
BACK TO LIST OF TRAVEL GRANTS
1. Full name
Giorgos Mountrakis
2. Name of department and university
Department of Spatial Information Engineering, University of Maine
3. Mailing address
Giorgos Mountrakis, 5711 Boardman Hall #348, Orono, ME, 04469, USA
4. Phone, fax, e-mail
Phone : (207) 581-2106
Fax : (207) 581-2206
Email : giorgos@spatial.maine.edu
5. Title of poster/paper presentation
"Modeling Change within an Integrated Spatio-Temporal Environment"
6. Abstract
Modern geospatial information environments are characterized by higher
integration requirements, due to increased amounts and diverse types of
information. Handling multi-resolution and multi-type information is a
fundamental issue in representing the real world in an appropriate
manner. Furthermore, an emphasis on the temporal aspect of data should
be given, in order to manage the evolution of objects through time by
modeling change. The need for frequent updates, and advanced query
capabilities are also essential components of an efficient
spatio-temporal model.
Such a model should work from the perspective that there are many
possible representations of spatial phenomena stored implicitly in
information resources, and that information on change lies in
combinations of these representations. We arrive at information about
change in spatial phenomena through multiple observations of phenomena
over time. Analysis of these observations may reveal very different
temporal behaviors from quite dynamic to essentially static. The types
of change that may be observed include existence (phenomena appear and
disappear), changes in shape, changes in location, changes in
non-spatial characteristics, and combinations of them. Thus, within the
model spatio-temporal change is decomposed into four potentially
independent categories: existence, boundary redefinition, movement and
thematic state changes. Furthermore, patterns of change built from
multiple observations over time can lead to estimates or predictions of
unobserved change.
A spatio-temporal gazetteer is employed to support direct
spatio-temporal query and data analysis. In this process, it is
important to first consider the evidence or basis for identifying
change. The content of the gazetteer is built and maintained from a
library of spatial information resources called the multimedia
information store which can include maps, imagery, video, and text as
well as other possible media. The multimedia information store is
characterized as an implicit information store. Spatio-temporal queries
on the resources level, based on a common spatial and time reference
system, are performed, as well as a statistical analysis of the
available resources and their accuracy.
The spatio-temporal gazetteer is an indexing structure over the
multimedia information store and is the key mechanism for converting the
implicit information contained in the multimedia information store into
explicit change information. Components of the gazetteer store
primitives of change that can be converted to explicit change by
operations over the gazetteer subcomponents. The gazetteer consists of
several sub-components. A Geographic Entity Register is used to record
the identified spatio-temporal objects. The existence or not of an
object over time is addressed within its content, without any further
information. Three other specialized registers are used to record the
three remaining components of change: the Boundary Register, the
Thematic State Register, and the Movement Register. Quantitative queries
on an object's change are executed at this more detailed level. At the
middle level, an indexing structure is created, based on these three
levels, building the Change Indexing Register. This register provides
the essential multi-dimensional indexing mechanism, with flags to all
the attributes that have been modified. Binary qualitative queries on
the attributes, such as evidences of change at the object are performed
in this register.
BACK TO LIST OF TRAVEL GRANTS
1) Steven M. Manson
2) Graduate School of Geography, Clark University
3) 950 Main Street Worcester, MA 01610
4) Voice: 508 793 7336; Fax: 508 793 8881; Email:
smanson@clarku.edu
5) Integrated assessment and projection of
land-use/cover change in the southern Yucatán
peninsular region of Mexico: Methodological aspects
6) Abstract:
1. OVERVIEW
This research introduces an “Agent-based Dynamic
Spatial Simulation” (ADSS) to project short-term
land-use/cover change (LUCC) scenarios in the Yucatán
Peninsula, Mexico. Human-induced LUCC significantly
changes biogeochemical cycles and thereby affects
climate, biotic diversity, and livelihoods. This
research draws on an “actor-institution-environment”
conceptual framework that focuses on household
decision making, socioeconomic institutions, and the
biophysical environment.
2. METHODOLOGICAL FRAMEWORK
The ADSS couples an agent-based model (ABM) and
generalized cellular automata (GCA). ABMs use
autonomous software entities, agents, to model
behavior. Here they embody the actor and institution
components of the conceptual framework. Ecological
models based on cellular automata suggest the use of
GCA to represent the environment. The ADSS is written
in the C++ language and integrated with IDRISI GIS.
In the ADSS, actors, or farming households, make
production decisions based on internal resources,
external variables, and GCA environmental information.
These production decisions result in LUCC that feeds
back on the GCA, simulating actor-environment
relationships. Institutions affect actor decision
making, and by extension, the environment
3. RESEARCH STAGES
3a. Data Acquisition
The ADSS draws on: 1) archival research and field
interviews; 2) 210 household socioeconomic surveys;
and 3) spatial data from 1970 to 1997, including
aerial photography, satellite imagery, and digital
maps of human and biophysical characteristics.
3b. ADSS Creation
GCA: The environment is embodied in GCA lattices
representing land-use, land-cover, soils, hydrology,
slope, aspect, market access, and infrastructure. GCA
rules, derived from ecological literature and
interviews, model environmental processes such as
secondary forest succession.
ABM: Land manager cognition (represented by heuristics
and genetic programs) combines socioeconomic and
environmental variables to yield production decisions.
Institutions modify decision making factors: land
tenure, market variables, and governmental subsidies.
Actor and institution characteristics are derived from
surveys and archival research.
3c. Simulation and Validation
The ADSS creates Monte Carlo-based probabilistic
estimates of LUCC, iterating through forty model
‘years’, as follows:
1) The ADSS updates exogenous parameters (e.g.,
population growth, prices).
2) Institutions modify actor resources (e.g., subsidy
access).
3) The GCA updates the environment (e.g., forest
succession).
4) Household actor decisions affect resources (e.g.,
income) and the GCA (e.g., land-use).
5) Projections are validated with recent LUCC data.
Tests are based on error matrices; fractal dimension
and contagion indices; multi-resolution goodness of
fit; and uncertainty propagation.
4. SIGNIFICANCE
This research exemplifies how GIS is moving from
‘systems’ to a broader ‘science’ that speaks to larger
research communities. The research addresses themes
underexplored by LUCC modeling: 1) distinct
spatiotemporal patterning; 2) uncertainty; and 3) the
complexity of socioeconomic and environmental
relationships. The research speaks to geographic
actor-structure debates by combining micro-scale
phenomena (ABM actors and GCA neighborhood functions)
with those at larger scales (ABM institutions and GCA
non-contiguous transition functions). The ADSS’s
scale sensitivity and embodiment of a conceptual
framework serves as a point of communication between
GIS and its critics. Finally, the ABM-GCA coupling
addresses surface/entity integration in GIS, answers
the call for artificial intelligence in environmental
modeling via use of genetic programming, and furthers
the use of GIS for dynamic modeling.
BACK TO LIST OF TRAVEL GRANTS
1. Brian Hastings King
2. Department of Geography, University of Colorado at Boulder
3. 1855 Athens Street #104, Boulder, CO 80302
4. 303-492-6854, kbrian@ucsu.colorado.edu
5. Towards a participatory GIS: PRA, counter-mapping and GIS in the
developing world
**[484 words w/o reference section]**
6. This project will address the use of participatory methods and GIS in
human geographic projects in the developing world. Building particularly
on Harris et al. 1995, the use of participatory rural appraisal (PRA)
methods provides an exciting opportunity to link GIS with broad-based
social concerns. Additionally, this serves as a response to critiques that
GIS is an overly positivist epistemology that ignores local knowledge. PRA
is designed to incorporate local participation into planning processes,
and there is a growing literature on the use of local sketch-maps to
challenge state hegemony of development and conservation processes.
Called counter-mapping, there is the potential to incorporate these maps
into a GIS to present alternative cultural and geographic representations.
In this project, I digitize counter-maps and enter them into a GIS in
order to understand the practical and emancipatory potential of these
alternative representations. Additionally, this project addresses the
counter-mapping literature and suggests ways to connect this work with
UCGIS's research priority on GIS and Society. I analyze a series of case
studies in South America, Africa and Asia that utilize GIS to represent
alternative geographic knowledge through a deliberative and participatory
process and make suggestions for incorporating PRA methods into future GIS
research.
A series of popular debates between the GIS community and a group of human
geographers occurred in the 1990s over the direction of GIS and society
and helped shape the UCGIS white paper on the same subject. Most notably,
Sheppard (1995) and Pickles (1995) assert that a broadening of the
research agenda is needed to address the ways that societal structures
shape the access and use of GIS technologies, as well as to how GIS is
utilized to examine social, economic and political topics. In a
disappointing assessment, Da Cruz (1999) argues that this transition has
not occurred, largely because of the positivist epistemological
assumptions behind GIS, as well as the control exercised by certain groups
with particular agendas. The assertion that GIS is divorced from
alternative knowledge and local problems is an important one, however,
there are a number of case studies in the developing world to suggest that
research is addressing the use of GIS as a participatory technology. One
goal of this project is to suggest how GIS can include local knowledge
by utilizing a PRA methodology.
This investigation is part of my doctoral research, which is addressing
the changing livelihoods of rural South Africans following the 1994
transition from apartheid. My doctoral research questions include: In a
spatially segregated society, how are rural communities changing their
livelihoods within South Africa's radically changing political economy?
How is local knowledge being incorporated into the national discourse?
Additionally, I am interested in the utility of participatory methods as a
form of resistance, a common assumption in the counter-mapping literature.
There have been some recent challenges to this assertion, and I consider how
local communities within South Africa utilize GIS to redress apartheid's
inequities.
References:
Da Cruz, P.R. 1999. "GIS as social technology." South African Geographical
Journal 81(3): 119-125
Harris, T.M., D. Weiner, T. Warner, and R. Levin. 1995. "Pursuing social
goals through participatory GIS: Redressing South Africa's historical
political ecology." In Ground Truth: The social implications of
geographic information systems, J. Pickles (ed.) pp. 196-222. New
York: Guilford Press.
Pickles, J. 1995. "Representations in an electronic age: Geography, GIS
and democracy." In Ground Truth: The social implications of geographic
information systems, J. Pickles (ed.) pp. 1-30. New York: Guilford Press.
Sheppard, E. 1995. "GIS and society: Towards a research agenda."
Cartography and GIS 22: 5-16.
BACK TO LIST OF TRAVEL GRANTS
1. Laurie Skye Ames
2. Departments of Geography and Agricultural Engineering
University of Idaho
3. Engineering Physics 425
Moscow, ID 83844-0904
4. 208.885.7333 phone
208.885.7908 fax
lauriea@iron.mines.uidaho.edu
5. The Use of Remote Sensing To Determine Acreage of Agricultural =
Burning
6. Abstract
Each year thousands of hectares are burnt in agricultural areas. Reports
on the amount of hectares burnt vary widely depending upon the agency or
group issuing the report. Increased awareness of air quality, this issue
is a concern due to the health risk involved. Satellite imagery can be a
useful tool to objectively assess the amount of hectares burnt. Similar
techniques are being explored in determining the location and amount of
land burnt by forest fires. These techniques use AVHRR satellite imagery
and are not a fine enough resolution. Burn acreage detection on farmland
requires a small pixel size. A field is typically 16.2 to 48.6 hectares.
Landsat TM imagery with a pixel of 30 meters is preferred.20
Objectives
Develop a procedure and evaluate the viability of using Landsat TM
imagery to determine hectares of fields burnt. If we can accurately
estimate burnt hectares, we can develop a technique for agencies
assessment of the impact of agricultural burning. Interested parties
will have objectively derived estimates. The applications of this
technique are far reaching in agriculture, forestry and for air quality
issues.20
Significance
Current estimates rely on farm reports, permits and visual inspection by
aircraft. As the population grows the effects on health issues
increases. The EPA has been asked to evaluate stubble burning and decide
on enforcement according to The Idaho Spokesman-Review,
Saturday, February 26, 2000. As funding is cut it becomes a
more critical issue of how to enforce and determine hectares each year.
Satellite imagery help mitigate the problems of determining hectares as
well as helping to cut the high cost of enforcement.
Interested agencies include the Natural Resource Conservation Service
(NRCS), Department of Environmental Quality and the Department of
Environment. These agencies, farm cooperatives and associations all need
to have accurate information as they make informed decisions on field
burning, plant rotation and management practices.
Methods
This on going study started with a Landsat 7 Enhanced Thematic Mapper
(ETM) image from September 18, 1999. A subset was selected. An
unsupervised classification was performed. We checked our findings with
NRCS records. Our preliminary analysis appears to match fairly well with
NRCS records.
As we develop a technique for future agencies we will add the temporal
factor. Adding an image taken prior to our scene allows us to identify
fields burnt previously then tilled. A scene taken after our current
image allows us to study what happens over the sixteen-day return period
of the satellite. Adding a MODIS images to our data set is a possibility
as its return period is quicker.
The images will be geo-registered and layers of information on soil type
and landuse added. Integrating the image into ArcView gives us more
analysis capabilities. This will allow agencies to have not only an
operational technique, but also a visual representation for public use.
BACK TO LIST OF TRAVEL GRANTS
1.Joseph P. Messina
2.Department of Geography, University of North Carolina at Chapel Hill
3.Joseph P. Messina, Department of Geography CB#3220, University of North
Carolina at Chapel Hill, Chapel Hill, NC 27599-3220
4.919-962-3870, 919-962-1537, messina@email.unc.edu
5.A Cellular Modeling Approach to Dynamic Systems
Characterization: Deforestation and Agricultural Extensification in the
Ecuadorian Amazon
[ABSTRACT at 515 words]
6. Global change research includes an extensive body of literature
covering population-environment interactions focusing on the central
issues of migration and demography, environmental site and situation, and
socio-economic structures. However, rarely are these conditions addressed
within a spatially-explicit, temporally dependent form. Quite often this
is simply because neither the data nor the modeling methodologies combine
well to effectively address uncertainty with spatially defined time-series
data. As dynamical systems theory has advanced, the available data and the
simulation tools have evolved so that it is now possible to simulate not
only general change but also the spatial organization of individual
landscape elements and their respective interaction. In this research, a
cellular automaton model is proposed as an effective framework for the
predictive modeling of landuse/landcover change (LULCC) associated with
the spatial pattern and rates of deforestation and agricultural
extensification in the Ecuadorian Amazon.
The research study site in the northeastern Ecuadorian Amazon, known
regionally as the Northern Oriente, is significant from a social,
biophysical, and geographical basis. Settlers in the Napo and Sucumbios
provinces are generally poor in-migrants settling on predefined 50 hectare
plots, clearing primary forest to grow subsistence crops, coffee, and
later, pasture for cattle. Despite its global biodiversity and carbon
sequestration significance, agricultural settlement and concurrent
deforestation threaten the region. The specific site selected for modeling
is an intensive study area (ISA) of approximately 200 km2 located to the
northeast of the regional capital and largest central place, Lago Agrio.
Cellular automata (CA) were originally conceived by Ulam and von Neumann
in the 1940s to provide a formal framework for investigating the behavior
of complex, extended systems. The model presented employs user-defined
rules based upon spatially-explicit probabilities derived from both
biophysical and social characteristics to produce an output image of the
anthropomorphized landscape. The ERDAS Imagine Spatial Modeler, an
interactive visual tool, was used for model development and enhanced using
the spatial model language (SML).
The primary input data for the model are landuse/landcover layers derived
using Landsat Thematic Mapper data ranging temporally from 1986 through
1999 classified using a hybrid unsupervised/supervised classification
scheme. Attribution was performed using the results from field work
conducted in February 1999 and February/March 2000. Additional data layers
include transportation, topography, and hydrography.
Model calibration was conducted through comparison of the model's output
to an historical data set with respect to the key variable, agricultural
extensification. The changing temporal and spatial location/process of
tropical development provides insight into the activities that currently
encourage land clearing. In this way, spatial patterns point to a set of
factors that can explain recent changes in regional rates of
landuse/landcover change and provide focused spatial constructions
suitable for modeling. This work combines the historically descriptive
aspects of society with remote sensing and landscape ecology towards the
development of a Geographic Information Science based Northern Oriente
analogue. With improved data handling, the modeling scheme presented here
is extensible to a variety of tropical environments and regional contexts,
making cellular automaton modeling not only a promoter of research into
predictive spatial systems but more importantly an effective approach to
probabilistic modeling of population-environment interactions.
BACK TO LIST OF TRAVEL GRANTS
1. Asad Ullah
2. Department of Geography, University of Nebraska-Lincoln.
3. CALMIT, 113 Nebraska Hall, University of Nebraska, Lincoln, NE 68588-0517
4. (402) 472-7565, (402) 472-2410, asad@calmit.unl.edu
5. Title: Potentials of Geographic Information Systems and Remote Sensing for an
Examination of Environmental Variability Through Analysis of Historical Spectral
and Spatial Data.
6. Abstract:
This paper reports on the results of monitoring and mapping changes in
the spatial extent of standing surficial water and wetland at Enders and
surrounding Lakes, Brown County, Nebraska. The overall purpose of the research
was to evaluate the potential of remotely sensed data and Geographic Information
Systems (GIS) in providing practical, quick and cost effective solution to the
problem of detecting and mapping changes in the areal extent of wetlands caused
by flooding within an area of 100sq. miles around Enders Lake over a period of
several years.
Among the wetlands are saturated meadows, shallow marshes, and
open-water lakes. The wetlands range in size from less than one acre to two
thousand acres (Wolfe, 1984). This study is very important because a reduction
in the size of wetlands can be of great economic lose to the area ranchers as
these wetlands, especially the wet meadows provide abundant and nutritious
forage which is used as winter cattle feed. These wetlands also used as grazing
sites as well as a source of water to livestock.
The data used in this study were: 1) Landsat Thematic Mapper (TM) images
(1986, 1991, and 1992); 2) black-and-white (B&W) aerial photographs (1939, 1954,
1961, and 1968); 3) National Aerial Photography Program, both color-infrared
(CIR) and B&W photographs (1989 and 1993); and 4) National Wetland Inventory
(NWI) data-sets.
Several standard, commonly used image-analysis techniques were
considered. The Tasseled-Cap Transformation (TCT ) was used to identify open
surficial water and wetland areas from the TM images and scanned CIR
photographs. The transformed images were classified using unsupervised
classification. In order to calculate areas of surficial water and wetlands, the
classified image was multiplied with another raster image created by rasterizing
a vector layer of polygons for each lake.
The study shows that remote sensing data with GIS can be used to
successfully identify and measure variations in the extent of open surficial
water and wetland areas of (even) very small lakes. The study also shows that
wetlands within the study area are dynamic and change frequently. The change in
open surficial water has a direct effect on the areal extent of the wetland.
For example, in 1993, the areal extent of open surficial water showed a negative
change for all the lakes. In the same year the areal extent of wetlands also
decreased (regardless of a difference in procedures between digital
classification and manual photo interpretation).
Finally, this study also shows that the extent of open surficial water has
generally increased over the years (especially in bigger lakes like Enders and
Willow). In other smaller lakes, the spatial extent of open water has either
increased in most years or stayed the same. Wetland areas, too, either
increased or remained the same in most cases. But, wetland areas around the
big lakes like Moon lake and Ender lake, have decreased considerably.
BACK TO LIST OF TRAVEL GRANTS
Sorin Matei
Annenberg School for Communication
University of Southern California
1443 S. Barry Ave. # 206
Los Angeles, CA 90025
Phone: 310 312 2973; Fax: 603 737 6859
email: matei@usc.edu
http://www.metamorph.org, * http://www.metamorph.org/maps.
The distortion factor: Mapping and modeling mass media
influence on
perception of Los Angeles urban space
Abstract
This project employs GIS modeling for explaining maps of
social
perceptions of the Los Angeles urban space. The goal of the
project is
to measure the degree of perceptual distortion in people's
assessment
of their urban environment, especially due to mass media
consumption.
The perceptual maps are based on "comfort" feelings about
the Los
Angeles core urban area obtained from respondents to a large
scale
survey. Study participants were instructed to color in black
and white
maps of Los Angeles county using green wherever they feel
safe --
areas that are desirable and which foster a sense of good
living.
Areas somewhat comfortable were colored in orange. Red was
used for
areas where respondents felt threatened, unsafe or where
they felt
they did not belong. Unknown areas were colored in blue or
left blank.
Initial hypothesized relationships were that due to media
coverage
green areas were believed to be related to housing
desirability and
but red areas will not be related to objective fear inducing
factors,
such as crime. The perceptual distortion was hypothesized to
be shaped
by mass communication sources, especially commercial TV
news. One
hypothesis is that television coverage of crime and ethnic
relations
emphasizes the dangerousness of minority populated areas and
that
those respondents who are heavy users of television will
display a
negative bias in their spatial perception toward these
areas.
Individual perception maps were averaged using ArcView
Spatial Analyst
map algebra functions. An average map of comfort for all the
respondents involved in the study was generated. The raster
map was
then used for assigning "comfort" values to the
municipalities covered
by it whose housing desirability, crime and population
composition
were also known. The goodness of fit between the perceptual
and the
socio-demographic themes was then assessed using the S-Plus
spatial
statistical module for Arcview 3.0. The procedures used,
spatial
autocorrelation and regression, allow to control for spatial
non-independence of the cases analyzed (municipalities). The
findings,
so far, indicate that housing desirability, comfort and
ethnic
composition variables are autocorrelated. Also, it appears
that crime
is positively associated with comfort. This indicates that
the Los
Angeles respondents selected fort the study are more likely
to find
areas with relatively high levels of crime more comfortable
than those
with lower levels of crime. On the other hand it appears
that
discomfort goes with presence of increased proportion of
minority
population. As the project is in progress, these findings
are to be
considered preliminary. The next step will be to create an
average map
of comfort for high media consumption respondents only
(media
consumption = time spent with TV and using TV news for
learning about
community). The goodness of fit of these maps with crime,
population
composition and housing desirability will be again assessed
in order
to find out if there is a factor of distortion due to media
consumption. The hypothesized relationship is that the
comfort areas
of high media consumers will remain negatively correlated
with
presence of minority populations, due to the unfair coverage
of the
areas by television.
BACK TO LIST OF TRAVEL GRANTS
1. Rosso, Pablo H.(student); Hansen, Everett M., and Kanaskie, Alan.
2. Dept. Botany and Plant Pathology, Oregon State University
3. Dept. Botany and Plant Pathology, Oregon State University, Cordley Hall 2082, , Corvallis, OR 97331.
4. ph: (541)752-0494, fax: (541)737-3573, e-mail: rossop@bcc.orst.edu
5. TITLE: Use Of GIS To Assess The Risk Of Swiss Needle Cast Disease Of Coastal Douglas-Fir In Oregon
6. ABSTRACT:
Swiss needle cast of Douglas-fir, a fungal disease, is producing severe defoliation and growth reduction in forests
and plantations along the coastal area of Oregon. Presently, planting of tree species other than Douglas-fir in
highly susceptible stands seems to be the only disease management option. A GIS-based predictive model is being
built in order to understand important aspects of the ecology of the disease and to determine the areas of higher
disease risk.
A ground-based survey of the disease (about 200 plots) was done to generate the dependent variable. GIS was used to
obtain, adapt and incorporate climatic and stand history independent variables. These variables included:
temperature, precipitation , fog-low cloud occurrence, past stand composition, etc. Topographic characteristics of
the stands measured in situ were used to account for local-scale variability. Variables were used directly,
combined or modified to represent other factors such as ambient vapor pressure deficit, solar radiation incidence,
etc. After a series of exploratory analyses, variables were incorporated into a multiple regression model.
Preliminary results suggest a stronger association of temperature and precipitation with the disease. Locally, the
position of the stand in the slope and the slope aspect better explained the distribution of the disease. Whether
or not Douglas-fir dominated the previous stand composition was also found to be correlated with low and high
disease severity, respectively. Results are in accordance with recent findings about the physiology of the disease
and the biology of the fungus, which demonstrates the utility of GIS on large-scale epidemiological modeling.
Swiss needle cast disease of Douglas-fir has been expanding and intensifying in severity since the first stands
showing symptoms called the attention of forest managers about 15 years ago. The causes of this out-brake are not
clear, considering that its causal agent, the fungus Phaeocryptopus gaeumaniae, has been always present in
Douglas-fir forests and plantations. Results of the research presented here suggest that the cause could be found
in environmental changes or in the effect of relatively recent forest practices. This model also provides an
insight on the influence of the environment on the disease, which can guide not only the decision-making process of
forest managers, but also future research on microclimatology of the disease and biology of the causal agent. The
final model will be transferred to a GIS environment to automatically produce disease risk maps.
BACK TO LIST OF TRAVEL GRANTS
1. Ruihong Huang
2. Department of Geography, University of Wisconsin-Milwaukee
3. 3553 N Oakland Ave #210
Milwaukee, WI 53211
4. 414-229 5818, ruihong@csd.uwm.edu
5. Titles of poster/paper presentation
(1) Trip Planner for Transit Information System (completed)
(2) Real-time Bus Information System (completed)
6. Abstracts
(1) Trip Planner for Transit Information System
(URL: http://gis.sarup.uwm.edu/ruihong/)
This is a pilot project of Milwaukee Transit Information System sponsored
by Wisconsin Department of Workforce Development and the University of
Wisconsin-Milwaukee Center for Transportation Education and Development.
The goal of the project is to develop an on-line transit information
system to provide information on transit routing, schedules and automatic
trip itinerary.
Trip planning for transit system is more complicated than the usual
routing for the shortest path. First, traveling in a transit system is
controlled by schedule instead of just speed and distance, therefore, the
fastest route, which depends on trip date and start time, is not unique;
Second, in the bus route network, one street may have more than one bus
routes, then, should we use bus routes or the street center-lines to
create network? Moreover, considering waiting time in trips in a transit
system is even challenging, because the waiting time is extremely dynamic.
The application was programmed in Visual Basic 6.0 with MapObjects 2.0,
Netengine 1.1 and MapObjects IMS 2.0. Like other network analysis
software, NetEngine is not designed particularly for schedule controlled
and overlaping multi-route transit systems. For the overlaping
multiple-route problem, the project designed a particular database
structure that one arc in the network may contain more than one bus route,
therefore, the street map was used to create bus route network. For the
waiting time problem, the project designed a probability model in
computing the possible waiting time at each transfer point towards a
particular direction for different time periodes based on schedule and
weekdays. This possible waiting time can be taken as a turn weight at the
junction on a transit network. The turn weights update according to the
trip date and hour. Therefore, the fastest route can be solved by
NetEngine.
The application has been serving on the web since September 1999 and runs
smoothly. Considering the complexity of transit network and currently
available software packges, this method is effective and efficient in
providing advanced transit services.
(2) Real-time Bus Information
(URL: http://gis.sarup.uwm.edu/ruihong/)
This is an tentative application trying to provide real-time bus location
information as well as other bus related information through the internet.
The server captures and serves bus location information every 6 seconds,
and web browsers are set to update automatically at interval of about 30
seconds. The application provides schedule and street information query,
map zoom and pan, and automatic street labeling when the map is zoomed to
certain scale. Because real-time GPS data is not available currently, a
simulate database is used to control bus movements.
BACK TO LIST OF TRAVEL GRANTS
1. Name: Austin Troy
2. Department and University: Environmental Science, Policy and
Management Department, U.C. Berkeley
3. Mailing Address: 525 Alcatraz Ave #3 Oakland, CA 94609
4. Phone: 510-652-0631, fax: 510-642-7553,
email:austint@nature.berkeley.edu
5. Paper Presentation Title: "Assessing the effects of natural hazard
disclosure on property markets using a spatial hedonic analysis"
ABSTRACT:
In 1998 California passed a law requiring property sellers to inform
potential buyers of several types of natural hazard that may affect the
property. Theory predicts that such a law should result in the
capitalization of some of the costs associated with natural hazards into the
selling price of a property. This study analyzes the extent to which
disclosure requirements have affected market prices of vacant and
developed properties in regulatory flood and wildfire zones. Furthermore,
it looks at how those effects vary based on market and demographic
characteristics.
Among other methods, this study utilizes a spatially oriented hedonic
analysis to answer these questions. In hedonic analysis, observed sales
prices are regressed against quantifiable property attributes. The
components of the sales price can then be disaggregated and an index of
implicit marginal prices can be developed. In this case, vectors of
structural, locational and neighborhood attributes are included as
independent variables, along with a dummy variable for presence in or
out of a designated hazard zone.
While Geographic Information Systems (GIS) have previously been used
in conducting hedonic analyses, this study is unique in several ways.
First, it is one of the largest scale hedonic studies ever done. It is
intended to yield conclusions at the state level, but the state's size and
its extreme diversity make this extremely challenging. In order to isolate
significant trends across the numerous cross sections of the state, a
complex and innovative multi-stage spatial cluster sampling methodology
was developed--a methodology that could prove useful in future large-
scale social science statistical studies. Using GIS and statistical tools,
cross sections of California's nearly 2000 zip codes were created, based
on several criteria. These cross sections served as the basis of a stratified
random sample of zip codes. Then, individual property transaction data
were purchased for each of those sampled zip codes, address geocoded
and overlaid with hazard layers. For the second sampling tier, a random
sample of recently transacted households was taken, stratified by
presence in or out of the hazard zone. The sampling rates of both tiers
were used as regression weights.
The second reason why the study is unique is its intensive
paramaterization of locational attributes as explanatory (main effects and
control) variables. In addition to assigning each household presence in
or out of multiple hazard zones, each household was assigned values for
distance to nearest school, hospital, municipal park, open space preserve,
shopping center, golf course, industrial facility, hazardous waste site and
cultural facility. Tools assigning both straight-line distance and road
distance were experimented with for this purpose. Additionally, an
innovative index was developed quantifying a household's access to
business districts and employment opportunities.
To date, most of the regressions have been run. Results indicate that prior
to the law's passage there was only a modest differential between the
sales prices of comparable properties in and out of the flood zone, while
after the law's passage, this differential became much more
pronounced. Further results are pending.
BACK TO LIST OF TRAVEL GRANTS
1. Mark Wegener
2. Environmental Monitoring Department,
Institute for Environmental Studies,
University of Wisconsin-Madison
3. 2802 Arbor Dr. #2
Madison, WI
53711
4. Phone: 608-233-1013
e-mail: wegener@students.wisc.edu
5. Historical Land Use/Land Cover Change in the North Temperate Lakes LTER
Research Site
6. Abstract:
The Long Term Ecological Research (LTER) Network is a collaborative effort
aimed at facilitating ecological research over longer temporal scales and
larger spatial scales than those normally addressed in ecological studies.
Within LTER, the North Temperate Lakes (NTL) site is comprised of two
distinct research sites: the Trout Lake and Madison Lakes Sites. The Trout
Lake Site is located in Vilas County, in north-central Wisconsin. It is
composed of seven core lakes located within a glacial landscape
characterized by abundant forest cover, wetlands and lakes. The Madison
Lakes Site in south-central Wisconsin is composed of four core lakes
characterized by agricultural and, increasingly, urban land uses.
The Land Use/Land Cover Change component of the NTL-LTER project is aimed
at examining the interactions between lakes, their landscapes, and humans
over the 20th century in our two study sites by asking the following question:
"How have human uses of the lakes and the landscape affected lake
ecosystems? In particular, how have changes in land use and land cover
impacted lakes?"
To address this question, we are reconstructing historical land use/land
cover in selected sub-watersheds of the two NTL-LTER sites. To this end, we
are producing high-resolution digital orthophotos using a unique softcopy
photogrammetric solution. Land use/land cover is then interpreted within a
GIS environment based on ortho-rectified aerial photography dating back to
1937 (the year of the first statewide aerial survey). Interpretation is
performed at two different scales, characterized by the size of their
minimum mapping unit: 160 m2 for watersheds, and 40 m2 within 30m riparian
zones. A set of 20 mixed land use/land cover classes is employed with
land-water interactions in mind.
Many of the project's impacts may stem specifically from the unique
methodology employed. By developing and utilizing an in-house softcopy
photogrammetric solution for producing historical orthophotos, we were able
to create a low-cost and highly accurate GIS database of historical land
use/land cover change for the research sites. The methods employed to
perform this task could serve as a model for other entities interested in
asking geospatial questions about a given landscape over a broad temporal
scale.
Additional impacts will arise from specific uses of the GIS land use/land
cover database itself. Upon its completion, we will correlate historical
changes in land use/land cover with changes in lake chemistry over time. In
addition, the database will be utilized to create a landscape-level model
to capture the nature of the observed landscape changes over time. It is
hoped that this model could be used to project future land use/land cover
changes within the study sites under alternative planning scenarios.
To date, we have finished creating the historical orthophotos and the GIS
land use/land cover database for the Madison Lakes region, and we are in
the process of performing preliminary analyses the impacts of these
landscape changes on the area lakes using historical limnological data, and
examining landscape-level modeling methodologies for their utility in
modeling the long-term landscape change within the region.
BACK TO LIST OF TRAVEL GRANTS
1- Full Name: Tarek M. G. E. Rashed
2- Affiliation : doctoral student at SDSU/UCSB joint program -
Department of Geography, San Diego State University (SDSU).
3- Mailing Address: 5330 Adobe Falls Road, Apt. C., San Diego, CA 92120
4- Phone: 619 265 8541, fax: 619 594 4938, email: trashed@mail.sdsu.edu
5- Title: Assessing Human Vulnerability to Natural Hazards in the Urban
Environment: a Remote Sensing and GIS Methodology=20
6- Abstract:(500 words)
The proposed research will develop a methodological framework for
modeling human/hazards interaction in urban environments based on remote
sensing, GIS and spatial analysis techniques. Emphasis is placed on
providing an integrated understanding of variations in human
vulnerability to natural hazards by linking socio-economic
characteristics, geophysical processes and urban dynamics into a
spatially explicit model of urban areas. The research plan consists of
four interrelated tasks. Task One develops the theoretical and technical
infrastructure needed for understating the interrelationships between
various systems that influence human vulnerability in the contemporary
realm of American cities on the local level. Task Two demonstrates and
tests the validity of remote sensing imagery in compensating for
disadvantages associated with census data. I examine applications of
spectral mixture analysis (SMA) technique to AVIRIS data in order to
extract a number of dependent variables which can be statistically
analyzed to add timely and otherwise unobtainable information about
human characteristics associated with urban vulnerability. Task Three
focuses on assessing vulnerability levels in selected urban areas in
Southern California by coupling remotely sensed surrogates with other
ancillary data and vulnerability assessment rules in a GIS environment.
Techniques include multi-criteria decision analysis, correlation
analysis, and local spatial statistics and regression analysis. Task
Four demonstrates and tests the validity of this approach by
implementing and evaluating a spatial decision support system (SDSS) for
policy makers in order to assess vulnerability and explore the links
between various components of the urban system. This task will adopt
'OpenGIS Specification' as the modeling technique, taking into account
the needs of the disaster management community as indicated by OGC
Disaster Specialty Group. In addition, I propose the use the Cooperative
Requirements Capture (CRC) approach in order to translate the technology
for assessing vulnerability into procedures for easy use by local
governments, taking into account the full spectrum of the stakeholders
of the proposed system.
The broader contributions of the research are theoretical and empirical.
From a theoretical perspective, the research will contribute to emerging
currents in natural hazard research calling for a broader environmental
approach to understand human/hazards interaction. Specifically, I will
seek to provide a sufficient understanding of how socio-economic
differences are connected to variations in physical and natural settings
of the urban environment, and how such connections might decrease or
increase the risks from natural hazards. From an empirical viewpoint,
the approach will take advantage of the contiguous spectral channels,
and high spectral and spatial resolutions of AVIRIS data BE taking them
beyond their current use in applied sciences, towards applications that
address concerns of social science. By generating new remotely sensed
measures for human vulnerability, this research can enhance the impacts
of remotely sensed data, and provide a basis for assessing data
requirements for future sensors involved in population monitoring. In
addition, this work will contribute to hazard mitigation efforts by
providing a set of specifications (data dictionary and process details)
that could be the basis of establishing interoperable database design
and operational GIS modules for urban vulnerability assessment and
sustainable hazard mitigation.
BACK TO LIST OF TRAVEL GRANTS
1. Deana D. Pennington
2. Department of Geosciences, Oregon State University
3. 318 11th Ave. SW, Albany, OR 97321
4. (541) 812-0221, penningtond@geo.orst.edu
5. Knowledge-based approach to spatial analysis of forest landscape dynamics
6. Abstract. Spatiotemporal change of forested landscapes is the result of
vegetation succession, interrupted by anthropogenic and/or natural
disturbance. Comparison of dynamic landscape patterns produced by varying
disturbance processes is of interest, since a divergence in landscape
structure may have important consequences for ecosystem processes. In the
Pacific Northwest, most natural forest disturbance has historically been the
result of wildfire; most anthropogenic disturbance is the result of timber
harvest. The objective of this study is to develop knowledge-based methods
for spatiotemporal modeling of landscape patterns produced by fire and timber
harvest, creation of datasets that highlight structural differences between
resultant landscape patterns, and analysis of the effects of varying patterns
through time on selected ecosystem processes. Spatial patterns of wildfire
disturbance depend of fuel accumulation and moisture, and may be stratified
into several fire regimes with specific characteristics, the distribution of
which are related to elevation and topography. Boundaries between regimes
shift spatially through time in response to climatic change. Spatial patterns
of timber harvest may also be stratified as regimes, controlled by land
management objectives, which differ by owner and by land use. Unlike fire
regimes, however, the boundaries between regimes have been stagnant through
time, while characteristics of a given harvest regime have changed through
time in response to changing policies and socioeconomics. The challenge is to
create a knowledge based system that will model both fire and harvest
disturbance regimes, one of which changes boundaries through time and the
other of which changes characteristics through time, with multiple parameter
sets applied spatially. To accomplish this, boundaries and characteristics of
each regime must be quantified and entered into a database coupled to the GIS
via macro. An analysis of regime boundaries and characteristics is currently
being conducted, and has revealed interesting spatial scaling effects related
to pattern size and variability. A new approach is being developed for the
analysis of forest edge, which forms a boundary network, with relevant flow
direction transverse to network segments rather than along network segments.
It is anticipated that regime characterization will be complete by the summer
assembly, along with much of the conceptual basis of the knowledge-based
system, possibly with initial results from simulations. Modelled landscape
change under different disturbance scenarios will be analyzed for the
trajectories and rates of change of relevant properties through time. An
analysis of landscape differences that impact biodiversity, hydrology and
carbon sequestration will be conducted, including sensitivity of differences
to temporal scale of analysis. Novel methods of visualizing landscape
differences will be explored. It is anticipated that analysis of the
historical response of wildfire-produced landscape pattern to climatic change,
and the historical response of harvest-produced landscape pattern to policy
change, will inform analysis of the potential consequences of anticipated
co-mingling of climatic and policy change.
BACK TO LIST OF TRAVEL GRANTS
1. Rob Porter
2. Department of Recreation and Leisure Studies, University of Georgia
3. University of Georgia
Department of Recreation and Leisure Studies
300 River Road
Athens, GA 30602-6555
4. (706) 542-6551, Fax: (706) 542-7917, rporter@coe.uga.edu
5. Using GIS to Examine Federal Tourism Sites in an Environmental Justice
Context
6. Abstract:
Purpose and Objectives
This study examines environmental justice using the context of
outdoor recreation based tourism through the application of geographic
information systems (GIS). It examines the following two objectives:
1.To describe, for Southern Appalachia, five socioeconomic
characteristics--median household income, race, education, heritage, occupa=
tion--of CBG=92s contained within 1500 meters of each of six types of feder=
al tourism sites.
2.To identify the relationship between CBG=92s within a 1500-meter radiu=
s
of federal tourism lands and facilities (e.g., campgrounds, wilderness
areas, National Forests etc.) and those outside this radius to
determine whether any environmental injustice exists in the siting of
these federal areas.
Methods
Data were spatially defined and displayed (all CBG=92s and a selected
group of federal tourism sites) in ArcView. Then, CBG's within 1500
meters of each federal tourism site were identified (n=3D5487). This was
done using the theme-on-theme function in ArcView. 1500 meters was
chosen as the proximity criterion to be consistent with recent
environmental justice studies which have used GIS techniques and one
mile distances to select and/ or compare population characteristics
across geographic regions.
Once the relevant census block groups were selected, they were
analyzed using logistical regression in SPSS version 6.1 (Norusis,
1994). In this analysis, the dependent variable was set to equal 1 if a
CBG was within 1500 meters of an outdoor recreation site (e.g.,
campground, wilderness area etc) and equal to 0 for those CBGs where no
sites were located. The independent variables were percent nonwhite,
percent white-collar occupation, percent local, percent college
educated, and household income in dollars. A significance level of
p=3D.05 was used for all statistical tests.
Descriptive Results
The sample was comprised of mostly whites (mean =3D 91.0%, S.D.
18.0), local heritage (mean =3D 81.2%, S.D. =3D 13.1), and non-college
graduates (mean =3D 66.4%, S.D. =3D 18.3). The mean household income was
almost $25,000 (S.D. =3D 9,704) and slightly more than half of the sample
was made-up of blue-collar workers (mean =3D 53.9%, S.D. =3D 17.4).
Model Results
Race was found to be a factor in the spatial distribution of
the recreation sites (r=3D0.09 to 0.15); the CBG=92s surrounding the
selected sites had a higher percentage of whites than did those outside
the 1 mile perimeter. Percentage white collar was negatively correlated
to a number of types of outdoor recreation sites (r=3D-0.10 to -0.12).
Negative correlation attributed to income was also observed with
respect to campsites (r=3D-0.10), National Forests (r=3D-0.06) and National=
Recreation Areas (NRA) (r=3D-0.07). The recreation areas indicating the=
most correlation were the National Forests, which demonstrated positive
correlation with percentage local, white and college (r=3D0.03 to 0.14).
Conclusions tend toward the idea that tourism, while providing
a positive impact on the local economy in terms of revenue, may not
provide positive benefits for people in terms of job quality and
personal income. Also, the occurrence of a predominantly white
population closer to federal tourism sites may indicate that some
inequality exists based on the location of these sites away from
non-white populations.
BACK TO LIST OF TRAVEL GRANTS
1. Roberta M. Robles
2. Resource Assistance for Rural Environments (R.A.R.E.) administered
through the University of Oregon Community Service Center in the
Department of Planning, Policy and Public Management.
3. 411 Madison St. The Dalles OR 97058.
4. (541)298-1089 (541) 298-3551 fax rrobles@darkwing.uoregon.edu
5. Title: Making GIS Happen in Rural Oregon!
I. Objective:
The Wasco County GIS Department was started two years ago with
funding for a full time GIS Coordinator and taxlot base layer. The
ultimate goal of the GIS Department is to provide services efficiently
to various local agencies and obtain economic self sufficiency. To
obtain this goal a partnership has been established to share in the
costs. The role I play as an intern is to deliver specialized GIS
products and services to these partners, recruit more partners, and help
with maintenance of the data library. After one year I hope to help
establish a fully functioning and sufficient GIS Department that serves
the needs of Wasco County and North Central Rural Oregon.
II. Current Resources:
*The Wasco County GIS currently has a partnership consisting of
private and public sector organizations. Current Partners include Mid
Columbia Fire and Rescue, USDA, Oregon State Fish and Wildlife,
University of Oregon, Northwest Aluminum Corporation, and Various
County Departments.
*Current Software used - ArcView, ArcInfo, AutoCad, MS Access and
possibly MapObjects
*Full time GIS Coordinator
*Data Layers - Tax lot coverage developed from DOR data, Digital
Ortho-Photos, Various Administrative Boundaries, and various other
coverages collected from many sources.
III. Projects:
Technical assistance will be provided to the partners through
various GIS projects as needed and described; creation of a set of map
books used in emergency vehicles, weather and fluoride tracking for
orchards in real time provided on the web, county roads classification
digitally tied to state and federal data, network maintenance,
integration of 911 data with county data, and development of county wide
intranet to disperse data to county employees. To effectively use this
data specialized dialog boxes and easy user-interface applications will
be developed and training provided. In addition, specialized maps and
data analysis provided for the Planning and Economic Department as needs
arise.
Current accomplishments include ready to publish map books for
emergency vehicles including large maps to be place in the fire station,
updated road coverage with current features and attributes, procedure
identified in which to link to federal and state data to the road
coverage, update planning maps and data analysis provided for the
comprehensive plan, land use planning maps and spatial analysis
provided, a simple web site, and administrative boundaries established
for school, election and postal districts. At the end of my internship
I hope to have most repetitive tasks automated and most projects
promised to the GIS Partners completed.
BACK TO LIST OF TRAVEL GRANTS
1. Andrea D. Turner
2. Department of Urban Studies and Planning, Virginia Commonwealth University
3. 7345 Longview Drive, Richmond, VA 23225
4. home: 804 323-1109 office: 804 828-2489 fax: 804 828-6681 email:
s2adturn@titan.vcu.edu
5. Spatio-Temporal Changes in Historic Richmond Based on Feature Similarity
Assessments
6. This study in progress proposes to development of a methodology for
assessing spatial and semantic similarities for geographic features over
time. The purpose of this project is to assess spatio-temporal changes in the
historic district of downtown Richmond and the James River by analyzing the
similarities of dynamic and static features over time. By analysis of
historic maps and database information, similarity and changes over time may
be calculated using historical information for the specified research time
period, implementing existing and modified similarity models including
Sketcho v. 1.1 by Andreas Blaser and Similarity PPC by Andrea Rodriquez.
Datasets will be will be constructed following the Spatial Data Transfer
Standard for feature type definition and every attempt will be made to
incorporate the proposed ISO standard for temporal schema. Use of Extensible
Markup Language (XML) will further enhance transferability and compatibility
of data produced by this project. Historical maps and documentation will be
used to construct a research timeline and provide key reference points for
similarity assessment. Advances in spatio-temporal similarity assessment will
enhance our ability to model dynamic processes within geographic information
systems.
BACK TO LIST OF TRAVEL GRANTS
1. Mr. Brendan Richard Belby
2. Department of Geography, University of Illinois at Urbana-Champaign
3. Department of Geography
220 Davenport Hall
GMS Laboratory
607 South Matthews Avenue =20
Urbana, IL 61801
4. phone (217) 333-4735 fax (217) 244-1785 e-mail belby@uiuc.edu
5. GIS Modeling of Soil Loss to Enhance Watershed Management Strategies
6. Abstract
Statement of Objectives
The objective of this research is to use GIS modeling to investigate
spatial patterns of soil loss for various land use alternatives so that
local watershed associations may adopt effective conservation strategies
that are scientifically informed. This research is being conducted as
part of the Pilot Watershed Program through the State of Illinois, which
involves the interaction of multiple natural resource agencies with the
purpose of supporting community efforts at sustainable land use
management of their watersheds. Although soil loss from agricultural
fields has been greatly reduced in recent years, sedimentation in rivers
and streams is a continuing problem in Illinois. With the aid of
computational modeling, the study seeks to better understand the
interaction between overland and stream processes in a watershed that is
defined by complex terrain and diverse land uses.
Methodology
USGS 7.5 minute Digital Elevation Models and Landsat satellite imagery
serve as the base data for distributed hydrologic and erosion models
that can analyze soil loss at site-specific locations throughout the
watershed. Two different methods are being utilized. The first is the
Modified 3D USLE with a new Length Slope factor based on upslope area
and flow convergence. This method is beneficial for quickly identifying
hot spots of erosion and assumes that water has an unlimited capacity to
transport sediment, and therefore, does not account for deposition. A
more powerful method is the USPED (Unit stream power based model) that
applies a transport capacity to water within the watershed, and if this
value is exceeded, deposition will occur. It is useful for predicting
if eroded material will reach the stream. Using GIS tools such as
map-algebra and buffer zones, various conservation strategies are
designed and their impact is simulated to evaluate the most effective
methods of reducing overland soil loss and stream sedimentation.
Implications and Results
The Department of Natural Resources in Illinois has over $500,000,000 to
invest in the Conservation Reserve Program (CREP). This program creates
buffers alongside streams by leasing agricultural land from private
landowners and taking it out of production. Our research will advance
knowledge by evaluating whether the buffers created by CREP are the most
efficient and effective management practices. Preliminary results
indicate that riparian buffers do not eliminate erosion at the source;
they merely prohibit sediment from entering into the streams. Highest
areas of erosion predicted by the models are located between the upland
areas and the stream buffers. This information will be provided to
local watershed associations so they can improve their watershed plans
and Best Management Practice (BMP) approaches.
BACK TO LIST OF TRAVEL GRANTS
1. Rakesh Malhotra
2. Department of Geography, University of Georgia
3. 204 GGS Building
Department of Geography,
University of Georgia
Athens, GA 30602
4. (706)-542-2856 Fax (706)-542-2388
5. Deer-car accidents - A GIS Analysis
6. Deer-vehicle collisions are a common occurrence on highways of
Eastern United States. Although they occur year round, such collisions
are particularly frequent during the fall deer rutting season. This
study uses aerial photographs and GIS to analyze deer-vehicle
collisions at the Savannah River Site (SRS), South Carolina. Being a
restricted area, SRS personnel have collected accurate data on deer
collisions that occurred from 1991 to 1999.
Collisions were separated based on season to control for
seasonal variability in deer behavior and collisions occurring in fall
were selected for this analysis. Buffers of 250m, 500m and 1000m, were
created around collision points and information on vegetation,
topography, presence of water bodies, and road conditions were derived
from 1:16,000 true-color and color infrared aerial photographs taken
during the same time. These characteristics were then statistically
compared to control values obtained for similar buffers around random
points along roads. The analysis of data for three buffer zones
provides us with information on the resolution of influencing factors,
i.e., which factors influence deer-vehicle collisions, and at what
distance from the collision does their influence wane.
Results are then used to create a spatial model to identify
conditions conducive to deer-vehicle collisions. The spatial model is
then used to predict sites of high, medium, low potential for future
deer-vehicle collisions. It is hoped that by understanding spatial
factors related to deer-vehicle collisions, management practices can be
implemented to reduce such incidents by altering the conditions around
areas with high potential for collisions.
BACK TO LIST OF TRAVEL GRANTS
1. Shane J. Cherry
2. Geography Department, University of Idaho
3. 1123 S. Harrison #7, Moscow, ID 83843
4. (208)892-2168, cher9518@uidaho.edu
5. Improved Risk Rating of Bark Beetle Infestations Using GIS and
Remote
Sensing Integration
6. Abstract
Bark beetles are among the the most destructive of all forest insects.
North American timber losses due to bark beetles are estimated at more
than 2 billion board feet per year. Large-scale outbreaks affect the
forest ecosystems by deteriorating watershed quality and wildlife
composition, reducing recreational value, and creating an accumulation
of dead wood, which provides a major fuel source for subsequent
wildfires. Forest pest infestation risk analysis research is one of
many appropriate GIS and remote sensing integration applications related
to forest health issues. The multiple number of environmental factors
that affect the initiation and distribution of bark beetle infestations
warrant the use of an integrated analysis approach. Remotely sensed
data provides a relatively quick and cost efficient method of data
collection and evaluation while GIS provides a means for storage,
processing, retrieval, analysis, and display of data.
This project will utilize the benefits of combining these two
technologies to develop a dynamic bark beetle risk analysis tool. This
risk-rating tool would relate categories of stand characteristics to
general patterns of stand types within designated risk classes. This
would provide information that forest managers would find useful in
identifying and ranking locations or stands where increased surveillance
could greatly improve the managers ability to make pest management
decisions that are biologically and economically sound. In order to
accomplish these objectives, a number of data sets are needed as input
into the system. Some of these basic data sets include: 1) vegetation
cover, which represents the presence of suitable host type for the
insect, 2) forest stand conditions, which include stand composition,
age, stress, and density, and 3) estimates of current beetle population
activity, which are derived from U.S. Forest Service aerial sketch maps
and the collection of ground data. The data in the first two categories
will be obtained through the processing and analysis of Landsat 7
Enhanced Thematic Mapper remotely sensed imagery using previously
developed methodologies to derive the needed information. These data
layers will then be combined into a GIS model in order that spatial
comparison can be easily performed resulting in appropriate risk
classes.
The above mentioned process provides a static risk model with equal
weights being placed on each risk parameter. However, the actual risk
of an infestation occurrence is determined by the dynamic relationship
between changing forest conditions and fluctuating insect populations.
For this reason a Multi Criteria Decision-Making (MCDM) model will be
used to weight the multiple parameters to determine unique risk values
for stands relative to changing forest conditions and insect
populations. This approach will allow for a dynamic risk analysis tool
in which different weights could be given to the parameters as they
increase or decrease in relative importance for a given time period.
This project will yield a powerful decision support tool for forest
managers that will save time and money when compared to traditional
forest pest monitoring.
BACK TO LIST OF TRAVEL GRANTS
1. Name: Nadine Alameh
2. Department, University: Department of Civil and Environmental Engineering, MIT
3. Address: 540 Memorial Drive Apt 1510, Cambridge MA 02139
4. Phone,fax,email: 617- 577 5843, no fax, nadinesa@mit.edu
5. Title: Scalable and Extensible Infrastructures for Distributing
Interoperable GeoServices on the Internet
6. Abstract:
The need for distributing interoperable GIS services
in support of thin client computing is on the rise. A
carefully-architectured infrastructure supporting these
services facilitates the design and deployment of a wider
range of applications that use GIS technologies. Indeed,
the availability of such independent functional services
allows for a smoother integration of GIS with other IT
systems. It also provides a practical way for emerging
mobile handheld devices to expand their functionalities
to include location-related services.
The goal of this research is to create a framework for
building a scalable and extensible infrastructure that
can support a growing Internet-based network of distributed
interoperable GIS services. Candidate infrastructures are
identified by their basic elements (including services,
catalogs, mediators, etc.), their roles in the network and
the level of complexity pertaining to the interaction among
these elements. The issues emphasized include the dynamic
chaining of services, the middle-ware requirements, and the back-
tracing of the origin of data and services used in a transaction.
In its attempt to find a long-lasting value framework for
the infrastructure, this work is based on the architectural
choices implied by the general IT work in the areas of Internet
technology standards, distributed computing and multi-database
systems. The issues, trade-offs and implications involved will
help identify a practical pathway towards the GIS infrastructure
of the future, which will fundamentally alter the way geographic
information and geo-processing are defined and used. These
findings will be timely given today's increasing interest in
such an Internet-based infrastructure.
BACK TO LIST OF TRAVEL GRANTS
1. Elizabeth Suzanne McDonald
2. Department of Geography, Michigan State University
3. 211 East Owen, East Lansing, MI 48825
4. (517) 355-4040, mcdona79@pilot.msu.edu
5. LANDSAT Pathfinder/Humid Tropical Forest Inventory Project
6. ABSTRACT:
The Basic Science and Remote Sensing Initiative (BSRSI) is a global change
research program who's goal is to develop an interdisciplinary approach to
understanding global change through the integration of both physical and
social sciences. Our aim is to understand the inter-annual variability in
land use and cover change and how such variability affects the global carbon
cycle, greenhouse emissions, and global climate change. Remote sensing and GIS
are important research tools in the analysis of such complex problems.
An ongoing research project called the LANDSAT Pathfinder/Humid Tropical
Forest Inventory focuses on monitoring land use and land cover change in the
world's humid tropics from the 1970s to the present. It involves acquisition
and analysis of LANDSAT satellite images to produce digital maps of the rate
and geography of deforestation.
Deforestation in the tropical forests have raised global alarm because not
only are we losing beautiful areas, but many species have been wiped out and th
global climate has been altered. The rate of deforestation is difficult to
determine and has been the focus of NASA-funded scientists for years. As one
of the lead institutions of the NASA LANDSAT Pathfinder Project, BSRSI has one
of the largest LANDSAT archives, excluding the federal govenment, with
approximately 3000 scenes.
Michigan State University was selected to archive and distribute high
resolution satellite data for tropical biomes of the world. The Pathfinder
approach first involves acquiring the LANDSAT digital data set from the EROS
Data Center archive. The digital data is then analyzed to create a digital map
database in a GIS of the rate and extent of deforestation. The Pathfinder
project uses ARC/INFO, a vector-based GIS, for spatial data analysis. The
spectral information from the satellite image is combined into different
classes which include areas of forest, deforested areas, forest regrowth,
water, cloud, cloud shadow, and non-forest vegetation.
Data resulting from the digital classification polygon is then plotted on
clear vellum at 1:250,000 scale and compared with the 1:250,000 scale color
composite prints. Digitizers check the label on each and every polygon for
accuracy, make any necessary changes, and add any missing polygons. The
accepted final coverages are edge-matched together, scene by scene, to build
regional level coverages. Other projects use these regional level coverages to
spatially analyze and calculate areas of deforestation.
The LANDSAT Pathfinder/Humid Tropical Forest Inventory Project deals with
the Monitoring Land Use and Land Cover Change theme of the research at BSRSI.
This theme serves as the empirical basis for analysis of the Effects and Causes
of Land Use and Land Cover Change Themes at BSRSI.
The LANDSAT data archive for many scenes in South East Asia and the
Brazilian "Legal" Amazon can be accessed on-line at the BSRSI webpage with a
Web-GIS interface or a Web-HTML interface. Users can view the images and order
the LANDSAT data. At the present time, all the satellite data from the 1970s,
1980s, 1992, and 1996 have been processed and digitized. BSRSI has recently
begun to work on the 1999 images.
BACK TO LIST OF TRAVEL GRANTS
1. Christopher W. Solek
2. Biological Sciences Department, California State Polytechnic
University, Pomona
3. 3828 Latrobe Street, Los Angeles, CA 90031-1446
4. Phone: (323) 23-4017, FAX: (323) 223-1983, E-mail:
cwsolek@csupomona.edu
5. Territorial Dynamics and Spatial Utilization of a Fragmented Habitat
by Coastal Cactus Wrens (Campylorhynchus brunneicapillus)
6. Coastal Cactus Wrens (Campylorhynchus brunneicapillus), restricted to
the Pacific slope of southern California and northern Baja California,
represent a disjunct population of a widely distributed and relatively
common desert-inhabiting species found throughout the U.S. desert
southwest, Baja California and portions of mainland Mexico. Coastal
populations are unique in that they are obligate inhabitants of Coastal
Sage Scrub, a vegetation community confined to the mediterranean-climate
zone in North America. Ecological information on these populations is
limited. Coastal populations of the Cactus Wren have been severely
impacted by development throughout southern California, habitat loss,
degradation, and fragmentation being the major issues affecting the
viability of these populations.
This study focuses on a discrete coastal population in eastern Los
Angeles County, California and investigates the role of habitat in
shaping territorial dynamics and behavior. I intend to investigate how
territory size is correlated with both Cactus Wren behavior and various
vegetation and landscape characteristics. I am also interested in
describing inter-territory variation in regards to territory morphology
(i.e. size shape, and placement) and the vegetation characteristics
within territories, describing how territorial configurations change
over the course a year, and determining whether some territories are
preferable to others due to unique combinations of vegetation and
landscape features.
The research involves capturing and color-banding the population,
delineation and mapping of individual territories, behavioral
observation, and vegetation characterization of the habitat. The
project serves as a good example of an application of GIS to studies of
wildlife/habitat relationships. I am utilizing ESRI software,
specifically ArcView GIS, as a tool to evaluate my specific
ecological questions about the species. ArcView will be used to
create a spatial database from aerial orthophotographs of the study
site. The vegetation cover of the habitat will be analyzed and
classified using the ArcView Image Analysis extension. The ArcView
Spatial Analyst extension will be applied in the data analyses as a
means to interpret and quantify the effects of habitat edges and
small-scale fragmentation on the spatial utilization and territorial
behavior of this population of birds. Data analyses will include
multivariate statistical approaches to quantify inter-territory
variation and correlation /regression techniques to examine
relationships between territory morphology, vegetation structure, and
behavior.
The goal of the research is to elucidate the specific habitat
requirements of the species and the role these play in shaping
territorial selection and utilization patterns, aspects of the ecology
which have not been previously investigated in coastal populations.
Information of this type, especially as it relates to the spatial
aspects of habitat utilization, foraging behavior, and the effects of
localized fragmentation, will be particularly useful in developing
future species management and conservation plans.
BACK TO LIST OF TRAVEL GRANTS
1.Full name:
Anne Elizabeth Dunning
2.Name of department and university:
MIT Center for Transportation Studies
3.Mailing address:
Massachusetts Institute of Technology
127 Massachusetts Ave, 35-217
Cambridge, MA 02139-4800
4.Phone, fax, e-mail:
(617) 253-1820
Fax available upon request
adunning@mit.edu
5.Title of poster/paper presentation:
A Methodology for Analyzing Correlations of Spatial Attribute Clustering
with Airline Routing and Passenger Willingness to Pay
6.Abstract - The abstract should not exceed 500 words and should
describe a proposed, ongoing, or completed research investigation or
project. The abstract should include a statement of objectives,
methods employed, potential impact of the project on advancing
knowledge, science, education, or resource development, and should
report any findings to date.
Since U.S. airline deregulation, the competitive airline environment has
created complex fare structures that mystify both passengers and airline
professionals. Price discrimination is intended to target passengers
according to their willingness to pay. In practical terms, business
passengers generate the greatest revenue for airlines, while less expensive
services extended to leisure passengers fill overcapacity.
Designing fare structures to target needs according to business and
employment characteristics in origin and destination cities creates
benefits for both airlines and passengers. In the increasingly competitive
airline industry, creating the correct mix of fares for flights
differentiates route profitability from loss, which contributes to route
and frequency decisions. In the symbiotic relationship between airlines
and cities, successfully served routes can generate economic development
within the cities of origin and destination. Airlines are seeking new ways
of accommodating major industries in point locations, and startup airlines
such as Indigo Airlines in Chicago are basing their business plans on this
strategy.
This research creates a methodology for analyzing travel behavior according
to employment distributions by describing how spatial attributes
(employment and industry characteristics) cluster at specified locations
(airports or cities). Does a correlation exist between cities of origin
and destination, the industries found in those cities (particularly near
the airport), and types of business travel? Is airline revenue management
successful at isolating business travelers in different types of markets?
Who is escaping the fare restrictions?
Researchers can apply statistical methods in a spatial framework to
describe and differentiate objects according to their locations. This
research uses the SPlus module applying the Geary C statistic through
ArcView GIS on census data and the Ten Percent Ticket Sample provided from
all US airlines to the Federal Aviation Administration. Ultimately, this
research should produce a methodology for attributing census data
characteristics to origin and destination nodes on a transportation network.
Preliminary results using average fares from the second quarter of 1999 in
a twelve city network show some possible correlation between air traffic
volumes and commercial services. Continuing analysis of this question will
require expanding the network and data sets, refining the neighbor
analysis, using disaggregate air travel data (also available from the FAA
or from airlines that have agreed to participate in the study), isolating
business travelers from leisure travelers, and developing adjunct
methodologies for cities with multiple airports and airports that serve
multiple cities.
BACK TO LIST OF TRAVEL GRANTS
James A. Hanlon
Department of Geography
University of Kentucky
1457 Patterson Office Tower
Lexington, KY 405060-0027
ph. 606.257.8237
fx. 606.323.1969
jahanl1@pop.uky.edu
Archiving the digital and digitizing the archive: a historical geographical
perspective
The digital era is providing us with timely opportunities to rethink the ways
in which historical and geographical information is gathered, organized, and
represented. Geolibraries, virtual museums, on-line archival databases, and
other forays into the realm of digitality are taking advantage of increasing
telecommunication and computing speeds, expanding storage capacities,
Geographic Information Systems, and the Internet to construct widely accessible
digital archives for scholarly, pedagogical, and public uses. The archive is a
staple of historical geographical research, and this paper brings a historical
geographical perspective to the archiving of digital geographic information and
to the digital representation of historical archives.
The intention of this paper is to re-orient the manner in which digital
archives are thought about, and in so doing contribute to the enhancement of
the design, implementation, and use of digital archives. The language that is
often employed to describe digital archives tends to emphasize the ways in
which they differ from traditional archives. While the technological advances
that digital archives entail certainly warrant the drawing of such
distinctions, I argue that relevant distinctions may also be drawn between the
archiving of digital information and the digitization of archival information.
To this end, I focus on three examples of digital archives: the Digital Earth
Project, the Digital Imaging the Media Technology Initiative, and the Chicago
Imagebase Project.
The Digital Earth Project is a multi-institution research initiative which
aspires to construct a “virtual representation” of the planet. This project
will allow for the visualization and exploration of an immense range of
georeferenced natural and cultural information, and, as such, it is an
exemplary instance of the archiving of digital information. Conversely, the
University of Illinois-Chicago’s Digital Imaging and Media Technology
Initiative is a digital preservation project which utilizes multimedia
technologies to provide access to digital reproductions of its archival
collections. Between these two endeavors stands the Chicago Imagebase Project.
Also based out of the University of Illinois-Chicago, this project entails the
digitization of historical and geographical media pertaining to Chicago’s built
environment. But unlike the Digital Imaging the Media Technology Initiative,
the Chicago Imagebase Project has begun to incorporate GIS and other
Internet-based display and analysis technologies. Its georeferenced functional
framework, which allows for the integration of both archival and digital
information, offers the potential for a greatly enriched digital archival
experience.
This paper draws from my perspectives as both a historical geographer and an
interested participant in the digital era. Historical geography requires that
archival materials be situated within the contexts of their own production in
addition to regarding them as information sources in their own right. Attention
to the variations of form and context implicit within digital archives will
contribute to the understandings and practices of both historical geography and
digital archivization.
BACK TO LIST OF TRAVEL GRANTS
1. Sanjeev Arya
2. Department of City and Regional Planning, Ohio State University,
Columbus, Ohio.
3. 190 W 17th Av., Columbus, OH 43210-1320
4. (614) 688-0635 (H) / arya.7@osu.edu
5. EXPLAINING BIOTIC INTEGRITY AND STREAM HABITAT ACROSS MULTIPLE SPATIAL
SCALES
6. Abstract (word count: 497)
Objectives
Stream habitat is widely recognized as the template on which community
structures are shaped by landscape and anthropogenic factors across various
spatial scales. Earlier studies have dealt with these ecological
constructs, stream biotic integrity and stream habitat quality, separately.
The two major objectives of this study are 1) to explore and quantify
variables which explain the variations in the stream habitat as measured by
the Qualitative Habitat Evaluation Index, or QHEI, and 2) to relate stream
habitat indices and other variables to the biotic integrity of the stream
as measured by the Index of Biotic Integrity, or IBI. These numeric
indices, unlike conventional chemical measures of stream water
quality, encapsulate the impacts from multiple stressors and measure the
ecological health of a stream.
Methods
The two-stage analysis uses linear regression models. First, the variation
in QHEI is modeled as a function of local-scale natural and anthropogenic
factors and stresses. At the second stage, the QHEI model developed in the
first stage is integrated with the model for IBI which explains the
variations in biotic integrity in terms of a comprehensive, multi-scale set
of variables representing landscape, land use and land cover variables.
Data
A detailed GIS database, including 1:24,000 scale roads and
hypsography, 30m-resolution DEMs, streams, 30m-resolution land use
classified from Landsat imagery, point sources, and tract-level census
data, is compiled for the study area, comprising about 40 counties in an
Ohio ecoregion. GIS is heavily used to tackle issues of collecting,
storing, analyzing, and maintaining detailed region-wide database. GIS is
also used to derive watershed boundaries, slopes, variable-width buffers,
and reach sinuosity.
Pilot
A pilot was conducted to address the first research question - regarding
stream habitat quality. Linear regression models were used to explain the
variations in QHEI at the subwatershed and riparian scales in Big Darby
Creek and Great Miami River basins of west-central Ohio. Forest land
cover, reach sinuosity, and number of point sources in the catchment were
significant in one model. This model explained 63% of the variation in
site-specific QHEI. The whole model was significant at the 1% level. Two
other variables, watershed-scale road density and non-riparian agricultural
land use, were not significant in explaining the linkage between landscape
and stream habitat. Riparian-scale agriculture, roads, and steep slopes
have significantly negative relationship with QHEI in a
model. Riparian-scale moderate slopes has a significant positive
impact. The pilot indicates QHEI may be better explained at the
reach/riparian level rather than at the watershed level. Future
modifications in this model may incorporate ordinal logit and probit
modeling techniques, soil series data, local sinuosity instead of average
reach sinuosity, and land use dataset of higher resolution.
Conclusion
This study will 1) provide a better understanding of the spatial processes
shaping our stream habitats and biotic integrity, 2) provide justification
for watershed- and ecoregion-based data collection, planning and management
programs 3) indicate the feasibility, merits, and limitations of using
biological and habitat indicators of water quality in state monitoring,
assessment, and permit regulation programs.
BACK TO LIST OF TRAVEL GRANTS
1. Full name: Kosta Bidoshi, M.S., Ph.D. Candidate
2. Name of department and university: Center for Mapping at The Ohio State
University
3. Mailing address: 1612 Kinnear Rd
Columbus, OH - 43212
U.S.A.
4. Phone: (614) 481-3467 Fax: (614) 292-8062 E-mail: bidoshi.1@osu.edu
5. Title of paper presentation: Multimedia Visualization for Maps of the
Future
6. Abstract:
This paper describes a new look at map visualization in the context of the
advances in the computer science world. In the current Geographic
Information Systems (GIS) and Computer-Assisted Maps user's perceptual
interface with a paper map is replaced, in many cases, by analytical and
logical queries of a spatial database that represents the map in computer
form. The analytical results do not give a full account of the information
that can be represented in the map since they do not include implicit
information in the map. However, the visual display of the whole map is
very important for the user to determine what kind of information is to be
extracted and to understand the interrelationships between elements of the
map. Current visualization techniques (paper maps and their computer
replicas) do not take full advantage of the many modalities of human
perception in representing such a range of spatial information.
At the Center for Mapping at the Ohio State University we are studying
intelligent multimedia visualization including:
Spatial Cognition: Human understanding and perception of map
visualization.
3-D Visualization in Mapping: 3-D terrain representation as a means to
increase the level of perception of the real world in maps.
Sound as an Addition to the Visual Interface of a Map: Sound used to
enhance the perception of real world phenomena and 3-D stereo sound used as
a means for spatial representation.
Dynamic Visualization: Dynamic visualization is used to display real
world phenomena (like clouds, rain and movement of the cars and rivers) and
to attract the attention to the map user.
World Wide Web (WWW) Use in Map Visualization: The power of Virtual
Reality Modeling Language (VRML) and applications that can be used in
association with WWW make this environment very appropriate for this
research.
User Interaction: In conventional mapping applications there is a
separation between databases that are the foundation of a visualization
system and the visualization itself (Arc/Info, Intergraph). We are studying
the user interaction with spatial data in a 3-D environment.
Visualization on Demand: Two ways of dealing with this issue are
investigated. Firstly, the whole map display method. This display is
investigated using fly-through methods, zoom in, pan and user interaction
with the features. Secondly, the map indexed method. Multimedia
visualization including 3-D display, sounds and animation is indexed by
traditional 2-D mapping.
Augmented Reality: Representation of the new non-existing objects in the
scenery of the real world.
We are now working on a model that will be a combination of the
above-mentioned techniques for visualizing spatial information. VRML is
used for the implementation.
In all, then, this project aims at building an "augmented perceptual
reality" for mapping environments which will allow us to not only immerse
users into the mapped entities in realistic ways using somewhat
conventional desktop computers, but also to incorporate human perceptual
information processing characteristics into new cartographic media.
Lecture and slides will be the means of conveying the presentation.
BACK TO LIST OF TRAVEL GRANTS
1. Christopher Badurek
2. Department of Geography, SUNY at Buffalo
3. 717 Elmwood Ave #1
Buffalo, NY 14222
4. 716-881-3712, badurek@acsu.buffalo.edu
5. Web-Based GIS for Sex Crime Mitigation
6. Web-based GIS offers many potential applications for use in crime
analysis and prevention. An ArcView IMS based Registered Sex Offender
intranet prototype is being developed in order to demonstrate the
potential use of GI technologies by law enforcement agencies to visualize
geospatial data on sex offenders and to help mitigate sex crimes against
vulnerable populations. This prototype aims to provide the Buffalo Police
Department's Sex Offense Squad with a web-based GIS in which detectives
and commanding officers at Headquarters and at each Precinct would be able
to perform GIS functions regarding Registered Sex Offenders. Currently,
there is a public notification process underway in the City of Buffalo in
which certain "Vulnerable Entities," or institutions at risk from sexual
predators, are being notified of offenders in their vicinity. It would
benefit a police department to have all relevant geospatial information
readily available in order to respond to questions from the public and
provide data to responsible organizations such as a city school
board. The Intranet would be useful in that police officers would have
access to all required geographic information to provide answers to
inquiries as well as become more aware of potential criminal activities in
each precinct and across precincts. The advantage of the web-based
interface is the decentralization of the GIS software (officers could
access information remotely from a registered sex offender database
system) and freedom from officers taking time to learn the ArcView
software (as well as the required intermediate computer
skills). An evaluation of the efficacy of the graphical user interface
(GUI) will be performed using novice computer users as well law
enforcement personnel. The required task to be studied will be for the
user to identify potential offenders in a certain precinct by creating a
map using the server showing registered offenders and vulnerable entities,
and providing a report of the names and addresses of the mapped offenders.
In order to accomplish this task, the user must make use of an HTML-based
interface in which the user will select data sources, create a map, and
view a report of the offenders in the vicinity. This prototype aims to
provide a model for similar web-based GIS projects for crime applications.
BACK TO LIST OF TRAVEL GRANTS
1. Jessica Walker
2. Dept of Geography, University of Arizona
3. Arizona Remote Sensing Center
1955 E. 6th St.
Tucson, AZ 85719-5224
4. phone: (520) 621-8560
fax: (520) 621-3816
email: walker@u.arizona.edu
5. A GIS Model of Sonoran Pronghorn Antelope Habitat in Organ Pipe Cactus
National Monument, AZ
6. Abstract:
The primary goal of this research project was to identify and evaluate the
key physical, biogeographical, and spatial factors that characterize
habitat occupied by the endangered Sonoran pronghorn antelope (Antilocapra
americana sonoriesis) in Organ Pipe Cactus National Monument (OPCNM),
Arizona. Survival of the pronghorn has recently prompted intense debate
between environmentalists and various government agencies due to the
alarming decline of the population, whose feeding grounds extend onto the
military's live-ammunition Barry M. Goldwater Bombing Range. This
particular study focused on habitat in the adjoining Monument territory.
The tested hypothesis was whether an empirically selected range of natural
and anthropogenic factors could spatially define the animals' preferred
habitat on both a seasonal and annual basis. A database of over 500
pronghorn radio-collared sightings recorded within OPCNM territory between
1995 and 1999 formed the basis of the study. This highly-detailed,
long-term database of pronghorn locations was linked to fine-scale digital
coverages of vegetation and soil type, elevation, slope, aspect, distance
to human disturbances, and terrain ruggedness within a Geographic
Information System (GIS) environment. The variables were statistically
evaluated for the strength of their relationship with the sightings, and
the most highly correlated variables were used in logistic regression
modeling. The regression results were then used to create probability maps
of pronghorn occupation within the Monument. Although the annual model
accounted for only a small amount of habitat variability (r2 (adj) =
0.12), the binary presence/absence probability map correctly predicted
73% of the test data points at a threshold of 0.5. Of particular interest
were the effect of multicollinearity of the independent variables on the
model results and the sensitivity of the model to different strategies for
grouping categorical variable grouping strategies.
BACK TO LIST OF TRAVEL GRANTS
1. Joe Weber and Mei-Po Kwan
2. Department of Geography, Ohio State University
3. 1036 Derby Hall, 154 North Oval Mall, Columbus, OH 43210
4. Phone: (614) 292-2704, Fax: (614) 292-6213,
jweber@geography.ohio-state.edu
5. Using GIS to Model and Visualize Congestion Effects on Individual
Accessibility
6. Considerable attention has been devoted to the measurement of
accessibility to employment, shopping, educational opportunities, health
care facilities, and other services within cities. The use of Geographic
Information Systems has enormous utility for such research because of its
ability to not only represent the components of the urban environment,
such as the home locations of individuals, employment opportunities and
retail or other service locations, but also for modeling the spatial
relationships among these components through the use of computationally
intensive transport network analysis methods. The value of Geographic
Information Systems is especially apparent with the use of disaggregate
space-time accessibility measures because of their requirement for a very
high degree of temporal and spatial resolution of the urban environment,
and especially of the accurate representation of the movement
possibilities of individuals through urban networks. While considerable
attention has been directed at the representation of the urban environment
it is argued here that accessibility research has not yet taken full
advantage of the network analytical capabilities available within
Geographic Information Systems. Instead, even when detailed
representations of networks are used, potentially unrealistic measures of
travel time based on assumptions about constant travel speeds through the
network may be incorporated within studies. It can be argued that doing
so creates limitations for accessibility measures as utilizing a single
travel time for all hours of the day does not allow for the existence of
daily congestion or hourly variations in traffic volumes. Applying a
constant travel time to all areas of a city also does not allow for highly
localized congestion within transport networks so that traffic flows and
the effects of peak hour congestion are uniform throughout the entire
urban area. The ability to incorporate spatially and temporally specific
traffic congestion is therefore likely to offer considerable insight and
detail into individual accessibility. This research seeks to show how
these limitations can be overcome by measuring accessibility using
space-time concepts with a detailed street network for the Portland,
Oregon, metropolitan area, using spatially and temporally varying
estimates of highway travel times. Further, because the measurement of
accessibility is based on actual travel diary with trip data for 200
individuals, it is possible to incorporate the locations and times of day
during which travel took place for each individual. The resulting
accessibility values therefore reflect not only each individual's daily
activity patterns and constraints, the opportunities available to them in
different locations of the city, but also the uneven spatial and temporal
effects of congestion. These effects can be visualized by the use of
network potential path areas to show the areas and potential activity
opportunities which individuals would be able to reach during their
travel, both with and without congestion effects. The use of standard
ArcView GIS is fundamental to this application because of its network
analytical abilities and the need to incorporate the spatial relationships
existing between streets, activity locations, and activity opportunities
contained in multiple data sets.
BACK TO LIST OF TRAVEL GRANTS
Timothy W. Owen
Department of City and Regional Planning, University of North Carolina
at Chapel Hill
CB #3140, Howell Hall, Chapel Hill, NC 27599
(919) 942-3768, (919) 962-5206 (fax), twowen@email.unc.edu
Land Protection Planning and Scenic Quality Along the Blue Ridge
Parkway in Watauga County, North Carolina
Abstract:
As development pressures continue to build along the Blue Ridge
Parkway in North Carolina and Virginia, the need for systematic land
protection planning becomes more acute. Given the Blue Ridge
Parkway's mission emphasis on scenic quality, protection efforts in
recent years have focused on the inventory and acquisition of land
along the Parkway corridor (including the Parkway, National Park
Service property, and privately-held lands out to one mile for the
Parkway road surface). Inventories of visual sensitivity (what can be
seen; based on digital viewshed modeling) and scenic quality (how
scenic a view is; based on Landscape Architect field work) have been,
and continue to be, conducted along the Parkway corridor.
In this research, a Corridor Land Inventory Process (CLIP) was
developed by combining visual sensitivity, scenic quality, landform,
and property data sets in a GIS. CLIP consists of a sequence of
overlay analyses and geoprocessing functions that identify critical
areas for scenic protection. CLIP was applied to the 35,000-acre
Parkway corridor in Watauga County, North Carolina. In this study
area, 24 properties were identified for Park Service acquisition (56
acres located along the Blue Ridge Parkway boundary and valued at $1.5
million), and an additional 31 properties were identified for land
trust acquisition (766 acres valued at $2.2 million). CLIP was also
used to propose an overlay district for selected areas within the
Parkway corridor. This district will help local governments implement
policies, such as design guidelines and structural restrictions, that
are sympathetic to the aesthetic values of the nation's most visited
Park Service unit. Development of GIS tools, such as CLIP, are
important and timely as public interest in scenic protection along the
Blue Ridge Parkway increases and limited funds are dedicated to that
purpose. CLIP will likely be used by the National Park Service for
further GIS-based planning in the other 28 Parkway counties.
BACK TO LIST OF TRAVEL GRANTS
1. Ryan Holifield
2. Geography Department, University of Georgia
3. 145 Cole Manor Drive, Athens, GA 30606
4. Phone (706) 549-5558; Email rholifi@hotmail.com
5. A GIS Analysis of the Distribution of Environmental Hazards in
Chattanooga, Tennessee: The Implications of Topographic Variability and
Spatial Autocorrelation
6. Abstract: Statistical and GIS-based analyses of distributions of
environmental hazards among racial and socioeconomic groups have shown that
levels of unequal proximity or potential exposure vary with scale,
resolution, and aggregation. This finding has confounded attempts to make
broad generalizations about the geographic equity or inequity of
distributions. In this ongoing research project--part of a larger
exploration of environmental inequalities in the Chattanooga,
Tennessee-Georgia Metropolitan Statistical Area that will include historical
analysis--I investigate the proposition that measures of inequity based on
proximity to hazards may in areas of rugged terrain also be sensitive at
certain scales to the distortion of distance resulting from local
topographic variability. First, using GIS buffer analysis with the
assumption of a flat surface, I will determine the numbers of TRI and
Superfund sites, the total recorded emissions of certain toxic chemicals,
and the percentage of land use classified as industrial within a series of
radial distances from block group centroids. I will then repeat the
procedure, this time incorporating the topographic variability of the
Chattanooga area by estimating surface distances using slope measurements
and adjusting buffers according to those estimates. Next, I will conduct
statistical analysis to measure associations at various scales between
demographic attributes and proximities to EPA-regulated sites and industrial
land use and to test for differences between results from two-dimensional
buffer analysis and three-dimensional buffer analysis. Finally, I will test
attribute data for spatial autocorrelation at a series of lags, considering
the implications for future investigations of distributive environmental
inequalities. The project potentially offers important methodological
contributions to the growing field of GIS-based environmental inequality
analysis.
BACK TO LIST OF TRAVEL GRANTS
1. Full Name: Liu, Xiaohang
2. Name of Department and University: Geography, University of
California at Santa Barbara
3. Mailing Address: Department of Geography, 3610 Ellison Hall,
University of California, Santa Barbara, CA 93106
4. Phone: (805) 893-8652 Fax: (805) 893-8617 E-mail:
xhliu@geog.ucsb.edu
5. Title: Modeling Urban Growth as a Continuous Markov Process
6. Abstract.
Discrete-time and discrete-event are the two formalisms to model time in
GIS. Though both are applicable, usually only the
discrete-time approach is employed to model temporal dynamics. For
example, in urban cellular automata applications, time is
generally assumed to be discrete and regularly interleaved (e.g. year to
year). Given the advance in temporal GIS and
computer power, it is timely to reconsider other methods to model
temporal processes. This paper reports a study of modeling
the urban growth as a discrete-event process. Specifically, the model
perceives time as a continuous flow interrupted by the
arrival of newly urbanized area. A theoretical framework for the
proposed model will be firstly presented, followed by
numerical simulations on syntactic land use data. The paper ends with a
discussion on the implications of the model for urban
planning and the feasibility to integrate such a model with GIS as well
as their respective roles in the integrated system.
As a preliminary research, only the urban extent is concerned in this
study. In the model, urban is perceived as a system with
grid cell configuration. The state of the system at any moment is
determined by the land use of each cell. The system holds its
current state until a new development occurs. The location of the new
development is decided through a stochastic matrix. To
incorporate temporal correlation as well as to allow mathematical
tractability, the model further describes the urban growth as a
continuous Markov process. Assuming urban is absorbing, the growth can
readily be modeled as a pure birth Markov chain.
In another word, new developments arrive according to a Poisson
distribution.
Based on these assumptions, the model then generates a dynamic behavior.
Two parameters have to be estimated for
numerical simulation: the stochastic matrix and the parameter of the
Poisson distribution. Acknowledging land transition is not
spatially stationary, the model calculates the stochastic matrix for
each single cell by counting the spatial repeatability. Cells with
the same neighborhood have the same transition probability. The Poisson
distribution parameter is estimated by counting the
number of new developments during the interval. Though not stationary
throughout the whole growth, the transition matrix and
the Poisson parameter are indeed assumed to be stationary between an
interval where no data is available. For example, if no
field data is obtained between 1940 and 1960, the model will assume the
Markov chain for each cell is stationary during this
time.
Tested on synthetic land use data, the patterns emerged from this
continuous process is then compared with those generated
from discrete deterministic CA. The physical meanings of the transition
matrix as well as the Poisson parameter are interpreted
in the context of urban planning. Some implications of the result and
the methodology presented are discussed. Future work to
extend the model to simulate multiple land use transitions are briefly
explored.
BACK TO LIST OF TRAVEL GRANTS
1.. Full Name: Jong-hoon Lee
2.. Name of Department and University: Department of Information
Science and Telecommunication, School of Information Science, University
of Pittsburgh
3.. Mailing Address: 6004 Stanton Ave. APT. A14 Pittsburgh, PA 15206
4.. Phone: (412)-361-2657 Email: jhlee@sis.pitt.edu
5.. Title of Presentation: Spatial Decision Support System based on a
Bayesian Network Model
6.. Abstract:
Spatial decision support systems must take into account uncertainty
of data and models in solving real-world problems. The need to solve the
problem of how uncertainty information of spatial data results in
misinformed decisions has been established. Positional data uncertainty
plays a major role in making decision and assessing risk when spatial
decision support systems are used. We use a Bayesian network for
probabilistic reasoning in a geographic information system for the
purpose of assessing the risk involved in decision-making. In the
Bayesian network, the cause node of the positional data uncertainty is
horizontal and vertical positional uncertainties. The probability values
are calculated using the confidence level and standard deviation of the
horizontal and vertical differences between a random sample of line and
polygon data sets and a high accuracy map. To quantify positional data
uncertainty, we choose a statistical method of comparison between
spatial data sets and high accuracy maps. A number of varying width
buffers around a line is used in the method. For each width, the maps
are overlaid and statistics are computed. By plotting the results with a
Bayesian graphic tool, the usefulness of the method is demonstrated.
Results of the study can be used to improve the quality of spatial
decision-making and help manage the total quality control of spatial
decision support systems.
BACK TO LIST OF TRAVEL GRANTS
1. Name: Lu, Yongmei
2. Affiliation: Department of Geography, State University of New York at
Buffalo
3. Mailing Address: 105 Wilkeson Quadrangle, Department of Geography,
SUNY at Buffalo, Amherst, NY 14261
4. Phone: 716-645-2722 ext 44 (Office); 716-421-9903 (Home)
Fax: 716-645-2329
E-mail: yonglu@geog.buffalo.edu
5. Title of poster /paper presentation: Location Quotients verses Kernel
Density -Measurement of Spatial Pattern of Crime Occurrence
6. Abstract
Introduction
This research is an ongoing investigation on comparison of different
measurements of spatial pattern of crime occurrence. Crime occurrence is a
spatial process happening on complicated environment backcloth1.
Traditional spatial analysis is weak in inspecting the connectivity of
occurrence and its backcloth. This research aims at introducing a new
measurement to examine the relationship between point occurrence and its
context in general and crime occurrence and its environmental backcloth in
specific. The new measurement is also supposed to be effective in
investigating spatial displacement.
Objectives
(1) Exploring a new measurement of spatial pattern that is better at
accessing the relationship between point data and its spatial context.
(2) By using the new measurement on crime data, it is anticipated that the
spatial process of crime (spatial displacement) can be better described.
(3) Examine the relationship between kernel density method to identify
"hot spots" and the new measurement.
Methods
Generally speaking, there are three types of cluster analysis methods:
Hierarchical techniques, partitioning techniques, and density techniques.
It is believe that kernel density is better because density is calculated
for every point on the surface; and users can visually inspect the whole
surface to identify "hot spots" without defining subjectively where to cut
off in the process of either aggregating or partitioning. Nonetheless,
"hot spots" analysis has its own shortages in crime data analysis: (1) It
considers little about the underlying spatial process; (2) It neglects
population at risk. These shortages restrict "hot spots" analysis to
exploratory analysis.
Location Quotient of Crime is introduced into crime data analysis as a new
measurement that may help in understanding the spatial process of criminal
activity as well as the connection of environmental backcloth and crime
occurrence. Location Quotient was originally used in regional science to
measure the relative local economy activity. Mapping the general location
quotient into criminal research, crime occurrences are aggregated as an
attribute of area. Linking crime incident volume with other attribute of
study area, spatial displacement could show easily. Furthermore, the
connection of crime occurrence and environment backcloth could be observed
by investigating different attributes of study area.
Potential impact of the research
(1) LQ can be designed and used to measure spatial displacement of point
occurrence.
(2) Compare to "hot spots" analysis, LQ measurement is more explanatory,
because it assumes a relationship between the two attributes measured -
the crime occurrence and one other attribute of study area.
(3) Kernel density measurement is a special case of LQC.
Findings and Conclusions
(1) LQ is a tool for spatial pattern analysis; LQC is very indicative in
crime occurrence analysis.
(2) "Hot spots" analysis is good for investigating absolute crime
occurrence while LQC is good for examining the impact of backcloth
elements and spatial displacement of occurrence.
(3) LQC will be designed to measure unauthorized using of vehicle data of
Buffalo. Different elements of environmental backcloth will be used for
LQC measurement, and the corresponding spatial displacement as well as
backcloth elements' impact will be reported.
Note:
1 Environmental backcloth was first used by Brantingham, P. L. and
Brantingham, P. J. in 1993 to refer to the dynamic and interconnected
surrounds of a criminal event. Many social, economic, demographic, and
psychological elements make up the ever-changing but comprehensible
environmental backcloth.
BACK TO LIST OF TRAVEL GRANTS
1.
Daniel B. Haug
2.
GeoVISTA Center, Department of Geography, The Pennsylvania State University
3.
302 Walker Building
University Park PA 16802-5011
4.
Phone (814)865-3472 Fax: (814)863-7943 Email: haug@geof.psu.edu
5.
Software Tools for the Management, Exploration, and Analysis of
Geographically Referenced Qualitative Data
6.
Abstract:
The design of data structures, interfaces, and analysis tools in geographic
information science and visualization has been slow to move beyond the
natural science paradigm (Orford et.al 1999). The research reported in this
paper is an attempt to address this issue. The overarching goal of this
research is the design, implementation, and evaluation of a set of software
tools for the management, exploration, and analysis of qualitative data
produced using ethnographic methods. However, this paper will focus on one
aspect of that project: the design of the interface.
One of the key elements in the design of a user interface is clear
definition of the target users' objectives (Medyckyj-Scott 1994). GIS are
not noted for their intuitive interfaces (Egenhofer et. al 1999), however it
is imperative within qualitative research that the interface not become a
barrier between the researcher and her data (Sugita 1987). Therefore, in
order to justify my approach to designing this interface, it is necessary to
briefly present an overview of the ethnographic research practices.
Ethnography is an interpretive science in search of meaning (Geertz 1973).
Because these meanings are often subtle, and only can be uncovered in a
"naturalistic" setting, ethnographers tend to spend extended periods of time
in the field collecting data through a process known as participant
observation (see Wolcott 1999). The data collected are stored in a format
know as fieldnotes, consisting of narrative descriptions of observations
that took place in specific places at specific times (see Sanjek 1990).
However, fieldnotes often serve primarily as a reminder of the memories of
observations, as it is impossible to completely record them in a database
(Jackson 1995). These memories can be referred to as "headnotes" (Ottenberg
1990). The process of participant observation involves a near continuous
state of analysis of data, in which fieldnotes and headnotes interact in an
attempt to make sense of the meaning of specific interactions. Thus,
ethnography can be framed as both spatial and exploratory in nature.
Returning to interface design, the inherently spatial nature of ethnographic
research creates an opportunity to design the interface around spatial
metaphors. This can be accomplished both through the representation of
geographic space, and through the spacialization of information (see
Fabrikant and Buttenfield 1997 and Havre et. al 1999). Furthermore, the
exploratory nature of ethnographic research lends itself to approaches to
interface design used in constructing exploratory data analysis software
(see Springmeyer et. al 1992 or Hetzler and Miller 1998). This type of
approach would advocate the linking of multiple representations of
information (as in North and Schniedermen 1999) and the presentation of data
within its narrative context (as in Robertson and Mackinlay 1993 and Hetzler
et. al 1998). As the need for the interface to meet the users needs as been
stressed earlier, it is important to note that the these interface elements
will be evaluated using long-term iterative interaction with the target
user, as advocated by Medyckyj-Scott (1994).
BACK TO LIST OF TRAVEL GRANTS
1. Ranga Raju Vatsavai
2. Dept. of Computer Science and Eng.,
Remote Sensing and GIS Lab, Dept. of FR.
University of Minnesota.
3. 1530, N. Cleveland Ave, 115 Green Hall.
St. Paul, MN 55108.
4. Phone: 612-624-7281, Fax: 612-625-5212. E-mail: vrraju@gis.umn.edu
5. ON A ROBUST AUTOMATIC IMAGE TO IMAGE REGISTRATION
Geometric registration/rectification is the first step in integrating remote
sensing images into GIS and several other studies (change detection,
multi-sensor
data fusion, integration with other data sets etc). In this paper we present
intermediate results from an ongoing research project on automatic image to
image registration.
Objective/Problem Formulation
Let Ir be the reference image, Ii be the set of images to be co-registered
with Ir. Our objective is to identify a set of control points (features,
often termed as ground control points) in Ir and the corresponding locations
in Ii (often called as conjugate points), using a matching function M, and a
transformation t that minimizes the distance (or error criteria) between t(Ir)
and Ii.
Algorithm
Our algorithm is based on the extraction of a well distributed low level
features (modified Forstner operator), in the reference (Ir) image and area
based matching to find corresponding (conjugate) points in the images (Ii) to
be rectified. Brief description of major modules is given below.
1.Feature Selection: Basic requirement for image registration is a relatively
small but well distributed set of control points (10 to 50). After studying
several low level feature extraction techniques, we have implemented a modified
Foerstner operator which selects fairly good amount of low level features
suitable for template matching. Number of features selected can be controlled
by two thresholds, one that accounts for variance and the other
accounts for suppressing local non maxima in a neighborhood. To achieve well
distributedness of control points, we have first stratified the image into
small blocks. Our algorithm adaptively adjusts the thresholds, so that it
selects the user defined minimum number of features in each stratified unit.
2.Image Matching: Image matching is an ill-posed problem. A great amount of
matching techniques and measures have been proposed/developed in CV/DP field.
Our matching is based on the normalized cross-correlation (Cn) measure.
Cross-correlation will have its peak at template match position (proof by
RosenFeld and Kak - 82), and can be efficiently implemented as Fourier
Transform (Correlation Theorem). So it suits in the production mode, as the
tested and optimized FFT libraries are readily available. We have implemented
a two-way matching technique with additional checks, which selects high quality
conjugate points. We find that a backward template match greately eliminates
mismatches.
3.Transformation: Rectification is performed by using high-order polynomial
equations, whose coefficients are computed using the control points selected
in the above step.
Findings and Future Directions
The algorithm presented here will always leads to the selection of a well
distributed minimum set of control points which is essential for a high
accuracy image registration. Initial results are quite promising as the
overall residual error less than a pixel. Our future work will focus on
rigorous testing on a wide variety of images, and utilization of additional
matching techniques which will work with large geometric distortions.
This automated approach will eliminate manual collection of GCPs which is
often time consuming, facilitate quick processing and integration of next
generation high resolution satellite images into a GIS.
BACK TO LIST OF TRAVEL GRANTS
1. Name: Weili Wu
2. Dept and University: Department of Computer Science, University of
Minnesota.
3. Mailing Address:
Ms Weili Wu
Dept of Computer Science
200 Union Street S.E.
Minneapolis, MN 55125
4. Phone: (612) 626-7703 (Office)
(651) 738-7224 (Home)
Fax: (612) 625-0572 (Attn: Weili Wu)
e-mail: wuw@cs.umn.edu
5. Title of paper presentation:
Spatial Data Mining for Location Prediction
6. Abstract
Objectives: The goal of geo-spatial data mining is to discover interesting and
useful but implicit
geo-spatial patterns. The objective of this project is to define and explore
efficient
techniques for location prediction, which is a specific probelm of spatial data
mining.
Methods: The current approach towards solving spatial data mining problems is to
use classical data
mining tools after ``materializing'' spatial relationships. However, many
classical data mining
techniques including regression assume that the learning samples are drawn from
identical and
independent distributions(i.i.ds).This assumption is not true for spatial
attributes,
e.g. residence location. The property of samples affecting other sample values
in the neighborhood
is called spatial autocorrelation. In addition, classical data mining maximizes
classification
accuracy even though spatial accuracy may be more important for location
prediction. Spatial
statistics, a branch of classical statistics, has explored new parametric model,
e.g. spatial
autocorrelation based regression(SAR), to account for spatial autocorrelation.
These models improve
both the classification and spatial accuracy. We employed SAR model to carry out
experiments using
real-world spatial dataset (e.g. red-winged blackbird habitats in Darr and
Stubble marshes).
We also propose PLUMS, an efficient new technique for geo-spatial data mining
driven by ``map-similarity''
measures which is a linear combination of classification and spatial accuracy
measures.
Impact: Geo-spatial data mining is crucial to organizations which own, generate
and manage large
geo-spatial data sets. For example, public health organizations are interested
in geo-spatial patterns
in the spread of infectious diseases. Private companies are interested in
geo-spatial patterns in
consumer spending for marketing as well as logistical reasons. A special kind of
geo-spatial data mining
problem is Location Prediction. Public safety organizations are interested in
location prediction of
crimes to plan police patrols. Ecological and environmental organizations may be
interested in location
prediction for protecting bio-diversity.
Preliminary Results: We have carried out experiments to compare the classical
regression, spatial
autoregressive regression(SAR) models and PLUMS(A), an instance of the PLUMS
framework. Our preliminary
work with classical data mining methods and spatial statistical methods
shows the need for new spatial data mining techniques. Classical regression
methods
are based on the independent identically distribution assumption and
classification accuracy measures.
They do not capture spatial auto-correlation properties or spatial accuracy
goals of location prediction problems.
Spatial statistical methods are based on spatial autocorrelation, but are
suited for small spatial datasets
with small contiguity matrices, which are much larger than the original spatial
datasets. We have preliminary
results on appropriateness of PLUMS, a map similarity driven spatial data mining
techniques for location
prediction problems. Our experiments with location prediction on a real-world
spatial dataset indicate that
PLUMS is likely to outperform existing spatial data mining methods in terms of
spatial accuracy for location
prediction using orders of magnitude less computational resources.
Last updated on May 5, 2000
