MGIS Projects

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MGIS Projects
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Clickable Collage
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Ulrich Aeschlimann
Environmental controls on glacier distribution
and the influence of spatial resolution of base
data on terrain analyses

• In the context of global climate modifications,
  the monitoring of glaciers is a key instrument to
  quantify changes and to predict any resulting
  adverse impacts on alpine environments. This
  study examines data from the Revelstoke area
  (Glacier National Park, British Columbia) and the
  Kananaskis region (Peter Lougheed Provincial
  Park, Alberta) to address three issues that are
  paramount in any GIS-based, elevation model
  operations. The three modules of the study
  include Glacier parameter inventory, DEM -
  Resolution considerations, Climate Modeling.
  The glacier parameterization module extracts and
  compares elevation related factors (e.g., Mean
  elevation, ELA) as well as topographic parameters
  such as slope angles, aspect and curvature. The
  comparison of the glacier parameters of the two
  study areas indicates significant differences in
  the average glacier mean elevation and the
  average ELA. However, there is no statistical
  difference in average glacier area, length, shape
  index, and overall slope gradient between the two
  study areas. The second module, DEM resolution
  considerations, compares elevations extracted
  from different grid resolutions (30 m, 100 m, 200
  m, and 500 m) to determine if certain parameters
  (e.g., mean elevation) are less problematic if
  obtained from low resolutions than other
  parameters, for example minimum and maximum
  elevations. The assessment shows that the average
  glacier mean elevation is similar (a maximum of 7
  m difference) between values extracted from a 30
  m grid and values extracted from a 500 m grid.
  However, the maximum and minimum elevations are
  considerably different between the 30 m and 500 m
  grids, particularly in the Kananaskis study area.
  As such, caution is recommended when using
  glacier parameters obtained from low resolution
  DEMs. In particular, grid resolutions of 500 m
  and larger may cause considerable errors in
  parameters measured. The third module, climate
  models for the two study areas, explores general
  ways of evaluating the role of climate under
  different climatic regimes. The chosen method
  includes extrapolation of 30-year data sets from
  climate stations using linear regression
  analysis. The climatic parameters assessed in
  this study are temperature and precipitation
  (i.e., snow depth). For the Revelstoke area, the
  temperature/elevation results indicate that there
  was a decrease of 0.53 C in the mean July
  temperature with at every 100 m elevation
  increase (intercept 20.3 C). The mean January
  temperature decreased by 0.48 C at every 100 m
  elevation increase (intercept 8.4 C). Due to a
  lack of alpine climate data in the Kananaskis
  area, the model was based on a constant gradient
  of 0.6 C/100 m with intercepts of 22.3 C for
  July and 11.4 C for January. The intercepts were
  extrapolated from climate stations close to the
  study area. The Revelstoke data indicates an
  overall increase of 72 cm in snow depth per 100 m
  increase in elevation (intercept 89 cm). In the
  Kananaskis area the average increase in snow
  depth is 29 cm per 100 m increase in elevation
  (intercept 132 cm).

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Adriana Aguilar
A Multi Criteria Evaluation approach using Fuzzy
Set Theory

• A computerized decision support tool implementing
  a multiple criteria evaluation approach using
  fuzzy set theory is programmed in Arc/Info as a
  prototype. To aid and evaluate lynx habitat
  selection in Southern Alberta by developing a
  surface of possibility, following three different
  approaches and comparing the results.
• The prototype presented herein has been
  programmed in Arc/Info macro language (AML)
  following a modular approach and presented in a
  series of easy to use menus.
• By combining geographic information systems (GIS)
  and multiple criteria evaluation (MCE)
  capabilities and in the context of analyzing
  geographic data the union of these methodologies
  appears to be instrumental in the design of
  efficient tools for spatial decision-making.

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Catherine Bow
A GIS Based Study of Address and Postal Code
Location and Street Network Files and their use
in Medical Geography Research

• Medical Cardiac Catheterization Data supplied
  from the APPROACH (Alberta Provincial Project for
  Outcome Assessment in Coronary Heart Disease)
  database was reviewed and analyzed to determine
  the amount of error propagation inherent within
  the database. The error was found by comparing
  the address and postal code information in the
  database to the postal code and address
  information found in the 2001 Edition City of
  Calgary telephone book. A 16.32 percent error
  rate was found, excluding missed values and minor
  spelling errors. The database was corrected,
  postal code converted to find the longitude and
  latitude of the postal code, and geocoded into a
  GIS (Geographic Information Systems), namely
  ESRIs ArcView 3.2. Two street network files were
  compared, the City of Calgary 2001 file and the
  Statistics Canada 1996 file. The address and
  postal code locations were found for both of
  these files in meters and subtracted. In SPSS
  (Statistical Package for Social Scientists),
  scattergrams and histograms were created to
  compare these two files. It was found that the
  Statistics Canada street network file was less
  accurate and had more errors within the database.
  The City of Calgary street network file was
  deemed to be very accurate as it was used and
  updated daily within the City. The subtraction of
  the address and postal code led to similar
  results in terms of the mean and standard
  deviation, but the Statistics Canada file created
  an unusually linear pattern at the 25 and 25
  meter x and y-axis. This linear pattern is due to
  the block-face representative postal code point
  location of 20 meters from the centre of the
  street. Depending on the application, the postal
  code was deemed to be a fairly good
  representation of the address location.

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Wesley Burrows
A 3-D Steady-state groundwater model for West
Nose Creek watershed

• A 3-dimensional, steady-state, numerical
  groundwater model for the West Nose Creek
  watershed is proposed in this project. Hydraulic
  conductivity values are derived from summaries of
  pump test data from domestic and stock water
  wells. Spatially distributed hydraulic
  conductivity is interpolated from water well
  point estimates and imported to MODFLOW. For
  this, a loose-couple between ArcGIS and MODFLOW
  is implemented through Visual Basic and
  ArcObjects and is demonstrated to perform
  correctly. Calibration of the numerical model was
  not possible, as convergence was not achieved. An
  inability to model stream leakage and complex
  heterogeneities in hydraulic conductivity fields,
  has led to an ill-conditioned problem and
  ultimately non-convergence of this
  finite-difference solution.

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Bruce Burwell
Implementing a Geographic Information System
Using ESRIs Geodatabase Model A Case Study in
Archaeological Research

• This research demonstrates the conceptual design
  and system implementation of a Geographic
  Information System for archaeological research
  using ESRIs (Environmental Systems Research
  Institute) Geodatabase model. The Geodatabase
  model uses an Object-Oriented approach to
  database design in comparison with other data
  basing techniques which utilize
  Entity-Relationship design methodology. Based on
  research conducted in current practices of data
  modeling and implementation in archaeology, a
  spatial data model was created using Microsofts
  Visio 2000 drawing and modeling package. The
  model was then imported into ArcGIS and populated
  with data available from archaeological research
  previously conducted in Yemen. To complement the
  database, a wide variety of public domain image
  and vector data was also processed and modeled in
  the database. An application was then created
  that would facilitate a preconceived workflow for
  database updating, data mining, mapping and
  reporting. The result is a fully functional GIS
  (geographic information system) database
  management system with supporting model and
  documentation. This project also provides an
  effective methodology for designing and deploying
  an archaeological data model and proves that
  ESRIs object oriented database is superior to
  previous methods of GIS development.

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Nicola Bywater
Cumulative Effects of Hurricane Iris (2001) on
Belizean Black Howler Monkey Habitat

• This study integrated remote sensing and
  geographic information systems (GIS) to quantify
  landscape fragmentation and habitat change
  resulting from Hurricane Iris (2001) in the Stann
  Creek District of Belize. There are few studies
  that integrate remote sensing, GIS, primates, and
  tropical forests. Ground surveying was performed
  in January 2003, which identified 15 major land
  cover types in this area. The ground survey data
  was used to classify a pre hurricane Landsat 5
  image and a post hurricane Landsat 7 image.
  Habitat change was quantified by comparing the
  pre and post hurricane classified images using
  FRAGSTATS version 3.3 software. Class and
  landscape level metrics were used to quantify
  habitat change and fragmentation. It was found
  that the landscape has become more fragmented,
  specifically increase in patch numbers, increase
  in total edge, decrease in average patch size,
  decrease in patch extent, significant loss of
  core area, decrease of functional connectivity,
  increased interspersion, and an increase of
  aggregation for some patch types. These findings
  could have significant implications for howlers,
  particularly a loss of habitat quality and
  connectivity.

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Christopher Caschera
Multiresolution Wavelet Based Satellite Image
Fusion Application to examining Arctic sea ice
concentration

• In this document the application of wavelet
  theory to fuse disparate multiresolution
  satellite images is performed for evaluating the
  results against Canadian Ice Service ice chart
  derived estimates. The primary images will be
  RADARSAT-1 ScanSAR products (100m) from the
  Canadian Data Processing Facility (CDPF), NOAA
  AVHRR Thermal band 4 (1100m) provided by the
  National Snow and Ice Data Center (NSIDC), and
  passive microwave from the DMSP SSM/I at 25km
  resolution. The temporal scale for this study
  ranges from Julian Day 137 (May 17) to 204 (July
  23), 2002. The study area is located in Lancaster
  Sound between Borden Peninsula, Baffin Island and
  Cape Warrender, Devon Island (748'N, 8113').
  The images are decomposed into their multi-scale
  edge representation, using Daubechies wavelet
  transformation. The fusion process is built by a
  pixel by pixel selection of the coefficients with
  maximum amplitude. Finally, the fused image is
  computed by the appropriate reconstruction
  scheme.
• The wavelet image fusion results in a
  non-redundant image representation providing a
  photointerpretive and statistical assessment of
  wavelet based fusion of sea ice in the study
  area. Results indicate that the fusion of
  RADARSAT-1 ScanSAR to NOAA AVHRR is comparable
  and in some instances provides additional data
  over Canadian Ice Service (CIS) ice charts.
  Specifically, fusion conducted on JD 180 and 200
  illustrate the strength and applicability of this
  method. The fusion of RADARSAT-1 ScanSAR to an
  SSM\I algorithm of sea ice concentration
  (Bootstrap) illustrated no benefit over current
  methods employed by the CIS. Pixel size appears
  to be a major constraint for the successful
  fusion of images based on this method.

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Sam Coiro
Spatial Analysis of Enterprise Customer Data

• The construction of trade areas for retail
  selling channels bound by a fixed location in
  space, such as the traditional bricks-and-mortar
  selling unit, has been extensively reviewed in
  literature over the past 50 years. Although the
  catalog selling channel is the topic of much
  literature, attempts to describe, explain, and
  predict trade areas of such channels have yet to
  be made. Unlike traditional channels, catalog
  ones are not bound by fixed spatial locations and
  thus the methodologies used to derive
  bricks-and-mortar trade areas cannot be directly
  applied to catalog channels. This paper proposes
  the use of trend surface analysis (and the
  creation of visualization maps) to identify
  catalog trade areas at varying scales of
  geography. Four product division groups are
  studied and results indicate that for the most
  part, the trade area formations are dependent
  directly on the type of product in questions. In
  general, trend surfaces created for hard-line
  merchandise (e.g. tools, furniture, etc.) heavily
  underpredict transaction amounts across space.
  Trend surfaces created for soft-line merchandise
  (i.e. clothing, bedding, etc.) heavily
  overpredict transaction amounts across space.
  Regardless of the observed inadequacies however,
  the products of this paper are excellent
  first-steps that retail marketers can use to
  render the most return on investment possible
  from catalog campaigns, distributions, and
  promotions.

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Jon Connick
Benchmarking a Geospatial Store ArcSDE and
Oracle Spatial

• This manuscript describes an evaluation of the
  spatial storage capabilities of ESRIs ArcSDE and
  Oracles Oracle8i Spatial. The prime objective of
  this evaluation is to understand how to implement
  and manage a spatial store in an Oracle DBMS
  using ArcGIS as the client. The evaluation was
  completed through the implementation of the
  SEQUOIA 2000 Storage Benchmark and Paradise
  Geo-Spatial DBMS Benchmark.
• The benchmarks provided insight into performance
  differences between ArcSDE and Oracle8i Spatial
  storage and indexing options, in addition to
  overall functionality of the ArcGIS client in
  completing the queries. A chapter devoted to
  ArcSDE and Oracle8i Spatial functionality is
  provided to outline the common and differing
  aspects of both softwares.
• This study showed that data stored as ArcSDE
  Binary Geometry - Long Raw datatype, performed
  better overall in completing the queries and
  required less storage table space than the ArcSDE
  Binary Geometry - BLOB datatype and all other
  Oracle8i Spatial options.

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Kathleen Donovan
Snowmelt Run-off modeling of Prairie Depressions

• Understanding and quantifying snowmelt retention
  in depressions is an important component of
  modeling their role in groundwater interactions
  such as infiltration, soil moisture recharge, and
  the overall hydrologic properties of the
  watershed such as regional aquifer recharge, and
  stream discharge. The potential volume of
  snowmelt runoff was estimated using average snow
  water equivalent, depression area estimates, and
  depression depth measurements. The area of
  surface water runoff retained in the depressions
  after snowmelt was estimated from supervised
  classification of infrared aerial photographs
  with an accuracy of 15 compared to the detailed
  elevation surfaces, and 10 compared hand
  digitized polygons of the depressions on the
  photographs. Using 10 detailed elevation
  surfaces, the relationship between depression
  volume (V) and depression area and depth (Ah) was
  defined as V0.515(Ah). The error for this
  relationship compared to the volume estimated
  from the elevation surfaces was 10. The
  classified area and measured depth of 101
  depressions were applied to this equation to
  determine the overall relationship between
  depression area and volume. The relationship
  between depression area and volume was defined
  using least squared regression as V0.055
  (A)1.17. The cumulative error associated with
  this model is estimated to be approximately 25.
  Application of the volume model to all the
  classified depressions indicated that 40 to 70
  of the snow water available for runoff was
  retained by depressions. This assessment
  indicates that depressions in the West Nose Creek
  basin provide a significant contribution to the
  storage component of the water balance in the
  watershed.

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Rebecca Evans
GIS and on-line learning pedagogical issues and
tutorial development

• This project is a study of Geographic Information
  Systems (GIS) and online learning. The study is
  presented in two parts. Part One, Theoretical
  Issues (GIS and Online Learning Pedagogical
  Issues), is an examination of the broader,
  conceptual issues surrounding online GIS
  learning. It is argued that online,
  computer-based tutorials are an effective way to
  teach the concepts, applications, and technical
  skills required of a competent GIS user. However,
  it is important that GIS online learning
  materialsespecially those designed for use in
  higher educationbe based on a strong foundation
  of psychological learning theory. Thus,
  constructivism and the various approaches to
  constructivist learning and teaching are
  discussed. It is demonstrated how the use of
  technology, in combination with constructivist
  learning principles and the careful consideration
  of instructional design can produce quality,
  pedagogically sound, online GIS learning
  materials. Part Two, Implementation (An Online
  GIS Tutorial Development Project), is the
  practical application of the concepts, theories,
  and approaches regarding GIS and online learning
  discussed in Part One of this report. A series of
  GIS tutorials that demonstrate the use of GIS as
  a cartographic tool for thematic mapping are
  developed and implemented in an online
  environment. The tutorials are customized for use
  in an existing course offered in the Department
  of Geography, University of Calgary, and
  incorporate the key elements of quality online
  pedagogical principles and instructional design.
  Two primary software products, ArcView GIS and
  WebCT, are utilized to accomplish this goal.
  Preliminary results are obtained by having two
  anonymous volunteers test the tutorials and offer
  their comments and recommendations. The results
  of these tests indicate a high degree of success
  and it is concluded that the GIS tutorials hold
  considerable promise as an instructional/learning
  tool.

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Neil Farries
Study Wildlife Overpasses Crossing TransCanada

• This project begins with an overview of the
  history and operation of Cellular Automata (CA)
  as a tool for predictive change modeling. Several
  diverse projects from a number of disciplines are
  presented as examples of the vast amount of
  research that has been completed in this area.
  Next, an application project is presented in
  which the CA modeling capabilities of the Idrisi
  CELLATOM module are tested. This project entails
  a predictive model of Mountain Pine Beetle (MPB)
  infestation in the Bow Valley Corridor near
  Canmore, Alberta.

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Wenonah Fraser
Airborne laser scanning for measuring trees in
the boreal forest theoretical issues and
implementation

• Airborne laser scanning is a developing
  technology with many application possibilities.
  The first part of this document focuses on
  theoretical issues about using airborne laser
  scanning (also known as lidar) for assessing and
  monitoring forests. A review of forest structure
  is followed by an introduction to light detecting
  and ranging techniques and characteristics, with
  a review of applications in other fields. After
  explaining some of the challenges unique to
  lidar, issues regarding grid cell sampling are
  explored. Finally, potential interpretation
  techniques to identify individual trees by
  filtering are discussed. The second part
  demonstrates an application using lidar data.
  First and last returns from seventeen plots in
  the boreal forest in northwestern Alberta were
  used to generate estimates of tree heights.
  Kriging was used to interpolate surfaces of the
  tree canopy. The estimated tree heights were
  compared to tree heights determined from
  high-resolution aerial photographs. Although the
  relative tree heights within each plot compared
  well, lidar underestimated tree heights somewhat.
  Others have found similar results with different
  techniques.

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Roger Gauvin
Object-based Terrain Classification of a High
Resolution Elevation Model

• Terrain is accredited as one of the largest
  factors controlling surface and atmospheric
  processes on the earth (Hutchinson and Gallant,
  2000). Terrain landforms are defined to be the
  resulting morphology and characterization of
  slopes and slope patterns caused by physical
  processes on the earth (Whittow, 2000). Terrain
  itself can be said to be the spatial arrangement
  of landforms into a repeatable pattern. These
  patterns of terrain can be explained by the
  catena concept of landscape soil process was
  first described by Milne (1935) and later
  expanded with Spreight (1974) as the realization
  that sequences of slope forms were intrinsically
  related with soil series in a predictable way.
  Before the advent of spatially enabling
  technologies such as Geographic Information
  Systems (GIS), the science of geomorphometry
  involved either qualitative description or
  quantitative field measurements. Purely
  qualitative descriptions are problematic due to
  the lack of standardization of descriptive labels
  required to extend global classification.
  Quantification of landscape attributes required
  for terrain classification prior to the practice
  of computer automation required detailed field
  measurements involving laborious human
  intervention and limited analytical capability.
  Soon after the common adoption of the computer
  representations of terrain in the digital
  elevation models in the late 1980s, earth
  scientists and ecologists became intrigued with
  the potential of using elevation models to create
  specific topographic attributes that have a
  predictable relationships to both biotic and
  abiotic landscape processes. Better understanding
  of these key processes was to generate interests
  in applications for hydrology, soil conservation
  and forestry creating benefits for improved
  environmental management. In the 1990s the
  advent of high resolution Digital Elevation
  Models (DEMs), created with Light Detecting and
  Ranging (LIDAR), Inferometric RADAR or automated
  softcopy photogrammetric techniques, created new
  challenges and opportunities for the extraction
  of detailed landscape information for
  applications using terrain modeling techniques.
  In this review, quantitative methods that employ
  the use of GIS and spatial analysis techniques
  for the purpose of terrain analysis will be
  highlighted. Geostatistical exploration with
  spatial statistics of the digital terrain models
  attributes is argued to be essential for
  determining the structure, domain and range of
  these attributes. The determination of the
  spatial domain and range of terrain derivatives
  are necessary to approximate the scale of
  landform entity phenomena and how they might
  relate to complex landscape processes. As it is
  widely accepted that different landscape
  processes operate at different scales and the use
  of hierarchical object-based schemes may be the
  best method to model these complex relationships.
  This review will outline some of the theoretical
  issues of scale, hierarchies and the practical
  realities of designing a spatially aware modeling
  framework for modeling. This research area began
  with simple morphometric characterization of
  landscape and terrain, but is now moving to
  incorporate contextual methods that may better
  describe the spatial arrangement inherit of
  hierarchical schemas where a variety of landscape
  scales and processes interact. Recently, there
  has been much interest in using automatic
  landform segmentation and classification for
  practical applications in geotechnical
  engineering, agricultural and the environmental
  field. With these advancements, large amounts of
  data (and large tracts of landscape) have the
  potential to be analyzed. The question is as
  these new technologies become adopted will the
  statistical quantification in this field
  accelerate faster than the semantic labels to
  make practical sense of the relationships between
  processes and forms?

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James Gebert
ArcGIS migration to support upstream oil and gas
applications

• This project was undertaken to examine the
  migration from ArcView 3.x to ArcGIS 8.x in
  petroleum exploration and production (EP)
  companies. The major focus was to investigate how
  previously developed customization in ArcView 3.x
  can be implemented in ArcGIS 8.x. A custom tool
  was developed to automatically plot and symbolize
  wells from a standard petroleum industry
  database. The development of this tool
  demonstrates one aspect of ArcGIS customization.
  Other customization options for the creation of
  an oil and gas GIS are also summarized. As would
  be expected, petroleum specific functionality
  developed for ArcView 3.x can be replicated in
  ArcGIS 8.x, although at the considerable expense
  of time and effort. Development is more difficult
  in ArcGIS 8.x because of the increased complexity
  of the system architecture. However, this
  increased complexity allows ArcGIS 8.x to be
  customized to a much greater extent than ArcView
  3.x. A major benefit of migration is the
  geodatabase, which is a more robust format for
  the storage and maintenance of spatial data. The
  collaborative development of petroleum specific
  data models may facilitate the loading of data
  into the geodatabase, and make data access more
  efficient. There are limited short-term benefits
  to migration for the exploration business unit
  although the long-term benefits may be
  significant. The ability to customize ArcGIS 8.x
  will no doubt lead to the future development of
  additional tools that will directly benefit the
  exploration business unit. This will allow GIS to
  make incremental progress in the transition from
  its current role as a tool of data visualization
  towards a future role as a tool of spatial
  analysis and modeling.

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Nicole Hopkins
Analysis of wetlands in Scotty Creek basin, NWT,
using IKONOS and Landsat imagery

• Wetlands are an important part of the hydrology
  of the Scotty Creek basin, near Fort Simpson,
  North West Territories, because of their ability
  to hold water which affects the spring flood on
  the Liard and Mackenzie Rivers. The 30-meter
  resolution Landsat Thematic Mapper and the finer
  resolution IKONOS imagery (4 meters) were used to
  classify the Scotty Creek basin into six classes
  lakes, channel fens, wetlands, coniferous,
  deciduous and mixed forest. The percentage of the
  basin occupied by wetlands was also determined
  using commercially available computer programs.
  The IKONOS imagery was only available for the
  east portion of the basin. Therefore, the
  objective of the study was to classify the east
  portion of the basin using the finer resolution
  IKONOS imager and classify the entire basin with
  the Landsat image using the common training
  sites, compare the results and evaluate the
  accuracy. The overall accuracy for the hydrology
  landcover classes, which includes lakes, channel
  fens, and wetlands, was 78 for the IKONOS image
  and 67 for the Landsat classification. Both
  classifications resulted in confusion between the
  conifer and mixed vegetation classes. The
  accuracy for the Landsat classification was lower
  because of greater confusion between the conifer,
  channel fen and wetlands classes due to the
  coarser resolution of Landsat imagery. The IKONOS
  classification resulted in smaller patches (i.e.,
  interconnected pixels having the same class)
  which were closer together than the Landsat
  patches and determined that 41 of the east
  portion of the basin was occupied by the
  hydrology classes whereas the Landsat showed that
  46 of the basin was occupied by the hydrology
  classes. The IKONOS classification resulted in a
  greater accuracy and provided a better
  representation of the hydrology and connectivity
  of wetlands in the Scotty Creek Basin.

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Luigi Iannuzzi
Socio-economic application of geographic
information systems, calculations and spatial
analysis of the Human Development Index for
Honduras

• In 1990 the United Nations Development Program
  published the first world Human Development
  Report. This report refocused the attention of
  developmental practitioners on people. It also
  reminded us that economic growth is only a means
  to improve people's lives and not an end in
  itself. Human development is and should be the
  goal for any development. The Human Development
  Index (HDI) was developed as a new aggregate
  indicator, which would make it possible to
  compare the level of development of individual
  countries. It is always difficult to construct
  such aggregate indicators for it requires a
  number of theoretical questions to be resolved
  and open criticism to be answered (Banuri, 1994).
  The HDI has been undergoing this process over the
  last five years. There are many different ways
  that such an indicator can be constructed and if
  it is to be used as a means of comparing
  different countries throughout the world, the
  availability and reliability of data must be
  taken into account. After the methodology of
  calculating the indicator was developed, its
  three basic components remained unchanged. One
  was the per capita gross domestic product (GDP)
  which is an indicator of the economic level of
  the country, this being one of the basic
  preconditions for human development. When
  calculating the HDI it is adjusted for parity of
  purchasing power. The second component for
  directly measuring human development is life
  expectancy at birth as an average for both sexes,
  and the third is the level of literacy of the
  adult population, recently supplemented by the
  average period of school attendance. This first
  Development Index for Honduras at the municipal
  level was produced for the Field office of the
  United Nations Development Programme in
  Tegucigalpa Honduras. This will be the base
  document to be used in the development of this
  project.

20
Keila Johnston
Archeological Predictive Model for the Souris
River Basin Region of Saskatchewan

• This study employs GIS and statistical analysis
  in an effort to construct an archaeological
  predictive model for determining potential site
  locations in the Souris River Basin of
  Saskatchewan. Archaeological predictive modeling
  involves the use of environmental correlates with
  site presence or known human behaviour patterns
  in an attempt to locate likely areas of site
  presence. Inductive predictive modeling, or
  environmental correlates of site location are
  used to determine the probability of site
  occurrence throughout the Souris River region.
  Chosen environmental variables include distance
  to water, elevation, slope and land cover.
  Predictive modeling can prove to be a valuable
  aid in cultural resource management work because
  the time, money and manpower required to
  undertake extensive surveys can be greatly
  reduced. Statistics used in this study include
  nearest neighbour analysis, chi-square analysis
  and Dempster-Shafer theory. Nearest neighbour and
  chi-square analysis were used to determine the
  spatial patterning found in the region and to
  determine the association of archaeological sites
  with environmental variables. The Velief Module
  in Idrisi employs Dempster-Shafer theory and was
  used to construct a predictive model for the
  area. The Relative Operating Characteristic (ROC)
  Module in Idrisi was used to validate the results
  of the Belief Module. The sites of the Souris
  River Basin are clustered. A clustered pattern
  can be indicative of an abundance of good
  resources. Distance to water, elevation, slope
  and land cover are correlated with site location.
  Dempster-Shafer theory can be used to accurately
  reconstruct site location in the Souris River
  region. High probability areas are areas of
  possible site location, not areas of definite
  site location.

21
Christopher Jordan
Client Server Feature Streaming in ArcGIS 8

• Large corporations such as those in the Petroleum
  industry amass a vast quantity of spatial
  information. Data accuracy and currency is
  paramount in these organizations, with
  problematic data frequently leading to poor
  decision-making and a substantial loss of
  capital. An efficient process of maintaining data
  currency over the web has been developed and is
  appropriately named Feature Streaming.
  Web-based Feature Streaming allows limited data
  to be delivered from a Web Server to a client
  computer only when required, thereby resulting in
  increased efficiency. Just as web-based Feature
  Streaming effectively removes the internet
  bottleneck, Selective Client-Server Feature
  Updating removes the data transfer bottleneck
  associated with the corporate intranet. Visual
  Basic code has been developed using ArcObjects
  and Microsofts Component Object Model to enable
  Selective Client-Server Feature Updating in
  ESRIs ArcGIS 8.3 software. This program has been
  developed for EnCana Corporation to be used with
  ArcSDE. The code facilitates transparent data
  currency by regularly updating client machines
  with modifications, additions and deletions to
  the tables of spatial datasets. By eliminating
  the redundancy involved in the updating of entire
  records, the bottleneck created by the intranet
  is effectively removed, allowing massive datasets
  to be refreshed on client machines without delay.

22
Hejun Kang
Remote Sensing and GIS Applications in Lynx
Habitat Suitability Modeling

• Geographical Information Science (GIS), with its
  versatility and potential in addressing
  ecological issues, has had numerous methods for
  modeling wildlife habitat use and suitability.
  The first goal of this research was to identify
  the habitat preference of both lynx and snowshoe
  hare, and to determine relationships between the
  two species. Secondly, predict the lynx
  occurrence through different modeling methods
  Logistic regression, Multiple-Criteria
  Evaluation (MCE), and Dempster-Shafer, and then
  compare the prediction power of each model. Based
  on the overall accuracy, the best model is
  logistic regression (74.51), then the MCE
  (unequal weights), MCE (equal weights), and
  finally the D-S model (29.90). However, using
  only the users accuracy, the rank is completely
  reversed the best one is the D-S model (100),
  and the worst one is the logistic regression
  model (27.07). There are two main factors
  affecting the reliability of models. One is the
  combination of absence points, which inflated the
  overall accuracy of both the logistic regression
  model and the MCE (unequal weights), and
  decreased that of the other two models. Another
  is the choice of the threshold value. Logistic
  regression, which is more objective, can help
  decide how to choose prediction factors for both
  the MCE and D-S models. Future research should
  increase sampling on areas with higher slopes for
  both the MCE and D-S models. For the logistic
  regression model, spatial autocorrelation should
  be incorporated to increase the model performance.

23
Maria Komierowski
Using GIS to Identify Wind Erosion Risk and to
Recommend Sustainable Land Management Practices
in the Taber Irrigation District of Southern
Alberta

• Soil erosion is a predominant problem in Southern
  Alberta, especially with the strong chinook winds
  that are characteristic in the area. Additional
  problems exist on fields where specialty crops
  (potatoes, sugar beets, dry beans) are grown.
  Soil erosion poses a threat to human health and
  safety by air-borne particulate matter as well as
  reducing visibility on highways. Soil erosion
  also poses a threat to the sustainability of
  agricultural land and the agricultural industry.
  This work presents a state of the land report
  that identifies areas that are of concern to wind
  erosion, as well as locating areas that allow for
  sustainable expansion of the potato industry.
  This report also discusses various methods and
  practices that could reduce the risk of a wind
  erosion event. Using a Pairwise Comparison Matrix
  and ArcView 3.2, factors that affect wind erosion
  were identified. These factors were then used to
  locate the aforementioned areas of interest. The
  study found that areas of concern and highest
  priority for mitigation are those that have
  easily erodible soil textures (sands and clays)
  but have highly suitable land for potato
  production. It was determined that 48 of the
  Table Irrigation District fell within this
  category. Areas suitable for expansion included
  those that had inherent soil properties that have
  a reduced risk of wind erosion (loams and silts),
  had land suitable for potato production, and were
  in proximity to land with existing irrigation
  rights. Mitigation practices such as proper
  education, residue covers, shelterbelts, and
  emergency control methods were identified.

24
Dae Won Kwon
An Analysis of the Impacts on Travel Behavior
during the Transit Strike in Calgary using
Discrete Choice Methods

• Mode choice models are used to analyze and
  predict the choices that individuals or groups of
  individuals make in the selecting the
  transportation modes that are used for particular
  types of trips. This study describes an
  investigation of the impacts on mode choice
  travel behavior during the transit strike in
  Calgary using logit models. A utility function is
  formed which includes attributes that describe
  socioeconomic characteristics of households and
  individuals. The binary logit models and
  multinomial logit models based on this utility
  function are developed in cases of Home Based
  Work trip and Home Based Other trip before and
  during the transit strike. The developed logit
  models are evaluated using an individual level
  (disaggregate) data set and a zone level
  (aggregate) data set. The parameter estimation
  and model evaluation are performed using GIS
  software (TransCAD). The models that result and
  the model evaluation provide indications of the
  impacts on travel behavior of Calgarians during
  the transit strike.

25
Dana Lampi
Aboriginal GIS

• Aboriginal groups in Canada are taking an
  increasingly active stance in the definition and
  control of their traditional territories. This is
  occurring through two major processes land claim
  settlements and resources management /
  co-management. Each of these activities has a
  large spatial component and Aboriginal
  communities are turning to Geographic Information
  Systems (GIS) to address these issues. GIS is
  being used as a tool to provide a non-western
  view of the traditional territories in the face
  of development and is not only building capacity
  within Aboriginal communities but also providing
  community members with an in depth look at their
  culture, both past and present. The second part
  of this paper provides the course materials for
  an Aboriginal GIS course to be offered as part of
  the GIS Applied Degree program at the Southern
  Alberta Institute of Technology (SAIT). The
  purpose of the course is to introduce students to
  the different ways that GIS is being used by
  Aboriginal groups and to provide students with an
  introduction on GIS implementation in Aboriginal
  communities.

26
Joe Lee
An exploration into the use of digital cameras
for remote sensing studies of live vegetation in
Grasslands National Park

• The movement of animals across a landscape has
  been of interest to landscape ecologists for
  years. One way of studying this movement is
  through the development of simulation programs.
  These programs attempt to mimic the movement of
  animals in real life through the use of various
  algorithms and models. More recently, the
  development of object-oriented models for
  software design has lead to new approaches to
  this problem. Artificial intelligence has
  provided the framework for intelligent agents,
  programs that actively work to achieve a goal
  using knowledge and resources at its disposal.
  This project examines the complexities involved
  in the design of such simulations by developing
  an animal movement simulation that attempts to
  capture the effects of habitat patch
  configuration upon animal movement.

27
Nancy Lee
A Spatially Explicit, Object-oriented Simulation
Model of Animal Movementulation Model of Animal
Movement

• The use of digital photography to gather data for
  remote sensing studies on vegetation has a number
  of advantages over data collected in air or
  space. Digital cameras are small and easily
  transportable which makes the technology readily
  available for fieldwork. Likewise it is
  relatively inexpensive as compared to airphotos
  and satellite imagery. Photos can be taken of any
  areas at any time and can instantly be
  transferred to a computer for analysis with
  remote sensing software packages. Unfortunately,
  the majority of digital cameras take photos in
  the RGB wavelengths only. This is limiting with
  respect to vegetation analyses because the
  spectral reflectance curves of live and dead
  vegetation and bare soil are note very different
  in the VIS wavelengths. Consequently, procedures
  such as PCA, supervised classification,
  unsupervised classification and ANNs performed
  poorly at classifying these features whose
  spectral information was taken with the VIS
  spectrum. Reflectance information for vegetation
  in the VIS wavelengths was not sufficient to
  enable good spectral separability of the features
  in data space. The average blue radiance values
  for live grass were extracted from the
  classifications and plotted against the total
  green biomass clipped and weighed for the plots.
  Additionally the percent area of live grass and
  forbs was plotted against the total green biomass
  weights. No relationships were found. Vegetation
  indices such as the NDVI and the NDVI with the
  blue and green bands (referred to as the NBVI)
  were done to extract the live vegetation
  features. The values for the NDVI calculations
  were collected using s spectroradiometer and the
  MODEL function in PCI Works. These values were
  also plotted against the total green biomass
  weights and no relationships were seen. However,
  sample sizes were too small to allow solid
  conclusions.

28
Kaidong Li
Case-based reasoning, traffic safety and GIS

• This paper reviewed previous studies on the
  application of geographic information systems
  (GIS) and case-based reasoning (CBR) in traffic
  safety research, and demonstrated the methodology
  and results of a study that used GIS and CBR to
  analyze and manage traffic safety at light rail
  transit (LRT) grade crossings in the City of
  Calgary. GIS have generated an increasing amount
  of attention in the traffic safety community due
  to their capabilities for storing and analyzing
  spatially distributed data, such as traffic
  collisions. The information-retrieval methods,
  adaptation capabilities and learning processes of
  the CBR systems are considered more advanced than
  other database and reasoning systems. Therefore,
  the integration of CBR and GIS is highly likely
  to be beneficial in developing an intelligent
  system for traffic safety analysis. In this
  project, traffic collision history and
  site-specific data at Calgarys LRT grade
  crossings were manipulated and analyzed in
  ArcGIS. This data was then put into a CBR system,
  eGain Knowledge, to establish a case base for
  future LRT crossing studies. An example from the
  case base was provided.

29
Travis Logan
Large mammal habitat modelling Logistic
regression and model selection using GIS

• Cougar habitat suitability was modeled as a
  function of a number of landscape variables,
  describing features of topography, vegetation, as
  well as prey and competitor species densities.
  Geographic Information Systems (GIS) and Remote
  Sensing (RS) technology were used to create
  habitat models that related species presence and
  landscape characteristics. Habitat models were
  created for cougar, as well as wolf, deer and
  elk, for four different winter periods. Logistic
  regression and Akaike Information Criterion (AIC)
  were used for model construction and model
  selection respectively. Model accuracy was
  assessed using the Receiver Operating
  Characteristic (ROC) curve. Model predictions
  were used to describe cougar habitat suitability,
  as well as to infer the degree of competition and
  resource partitioning between the two top
  carnivores over the winter season. Cougar habitat
  selection was shown to be variable over the
  winter season, selecting for rugged regions of
  high elevations in early winter, while late
  winter selection indicates a shift in selection
  for areas lower on the hillslope, skirting the
  valley bottoms. Results indicate that competition
  and resource partitioning between cougars and
  wolves likely increases over the winter season,
  as predicted cougar distributions show increased
  overlap with the other species as winter
  progresses.

30
Julia LoVecchio
Site analysis for wind turbines

• This study employs the spatial analysis and
  decision support functionality of geographic
  information systems (GIS) to select the most
  appropriate site for the installation of wind
  energy at the Sunshine Village Ski Resort in
  Banff National Park, Alberta. The study uses
  environmental features, such as those included as
  valued ecosystem components under the Canadian
  Environmental Assessment Act (CEAA), as
  constraints to the placement project, and
  identifies sites for turbine(s) in an area with
  winds exceeding average rates of 5 metres per
  second (m/s). Results indicate that 11 sites are
  available to the ski area for further analysis
  and investigation. None of these sites is located
  further than 500m from an electrical grid tie-in
  nor are they visible from the Trans-Canada
  Highway, Town of Banff, or the other ski areas in
  the National Park. Using one full-year of derived
  wind data from weather stations within the ski
  area and on Rundle Mountain, an economic analysis
  of the wind energy project was undertaken through
  the use of HOMER, a free-ware package created by
  the US National Renewable Energy Lab. Results
  indicate that the ideal turbine selection would
  be three Vestas V47s, 660kW systems producing
  roughly 6,420,305kWh of energy annually and
  reducing the ski resorts carbon emissions by
  over half. The wind mapping procedure used in the
  project is a simplified multivariate regression
  equation that reduces a complex physical
  phenomenon to three elements namely slope,
  aspect and elevation. Should the ski area choose
  to move forward with installing wind energy, a
  more sophisticated wind assessment will be
  required.

31
Nathalie Lowry
Mining effects on Yukon boreal forest

• The Keno Hill mining district in central Yukon is
  located in the Boreal Cordillera Ecozone and has
  been subject to mining activity for more than
  eight decades. Using a combination of historical
  sediment metal concentrations, benthic
  invertebrate data and temporal Landsat satellite
  imagery collected from the Keno Hill district, an
  assessment of the effect of metal contamination
  on the boreal forest was made. The sediment
  metals and benthic invertebrates were evaluated
  on the basis of a control/impact experimental
  design to show that metals were having an effect
  on the stream ecosystem. The Landsat images were
  evaluated to detect changes in the forest over
  time using pseudo-supervised classification and
  post classification change detection analysis.
  The two were then used to see if a connection
  between metal contamination and forest change
  could be made. The sediment metal concentrations
  were higher at the affected sites and remained
  consistently high over the study period. Overall
  there was no difference detected in the benthic
  invertebrate communities over time though the
  site with the highest metal concentrations
  consistently had the lowest number of individuals
  and taxonomic richness. There was a change in
  vegetation between the two Landsat images where
  mixed spruce forest increased at the affected
  sample sites and decreased at the control sites.
  While it can be shown that there is evidence of
  metal contamination and a change in forest
  classification, a link between the forest and the
  metals cannot be made without access to forest
  classification information prior to mining
  activity. As this is not possible, future work
  using a similar analysis at different mine sites

32
Melanie Luinstra
Howler Monkey Habitat / Hurricane Regeneration

• This study examines a population of howler
  monkeys (Alouatta pigra) in Monkey River, Belize
  whose habitat was affected by a hurricane in
  October 2001. Habitat models were created and
  selected for both the pre and post-hurricane time
  periods, using logistic regression and Akaikes
  Information Criteria applied at two different
  scales. Remote Sensing (RS) and Geographic
  Information System (GIS) techniques were employed
  to derive the independent variables and create
  the models. It was found that the monkeys were
  selecting for areas further away from rivers at
  the smaller study scale, but closer to these
  types of areas at the larger scale, they were
  selecting for different types of vegetation in
  the different time periods, and that their
  habitat was less homogeneous after the hurricane.
  The spatial extrapolation of these regression
  models was less successful. However, it is
  possible that areas to the east in the smaller
  study site were more suitable after the
  hurricane. More data collection is needed over
  the larger area, and more scale appropriate data
  may be used for the smaller area to attain
  generalizable spatial models.

33
David MacDonald
Classification of mixed prairie pasture types in
southern Alberta using Landsat TM and RADARSAT
imagery

• Having a means of accurately classifying pasture
  types over large areas is important to ranchers
  and to conservation organizations interested in
  preserving native prairie. Radar imagery has been
  shown to be complementary to optical imagery with
  respect to providing information about rangeland.
  The purpose of this study was to use satellite
  imagery to assess the differences in radar and
  optical digital number (DN) values for different
  mixed prairie pasture types in southeastern
  Alberta and to develop a means of classifying
  them based on these differences. The images used
  included a Landsat TM image (acquired July 25th
  1998), and five RADARSAT standard beam mode
  images (acquired in September of 1996 and May of
  1998). Four pasture types were assessed,
  including native, Russian wildrye, crested
  wheatgrass, and a pasture that was originally
  cultivated and seeded to Russian wildrye but has
  reverted to native vegetation (referred to as
  native/Russian wildrye). The native and
  native/Russian wildrye pastures were found to
  have significantly lower average DN values for
  the Landsat image than the crested wheatgrass and
  Russian wildrye. Normalized difference vegetation
  index (NDVI) values were low for all classes
  indicating that there was little live healthy
  vegetation at the time of acquisition (i.e. the
  grasses had already senesced). Average radar
  backscatter was found to be significantly higher
  for the seeded pastures compared to native, the
  largest differences being between native vs.
  Russian wildrye and native/Russian wildrye. The
  fact that the native/Russian wildrye class
  (cultivated but with native vegetation) had
  average radar DNs most similar to those of
  Russian wildrye indicated that the roughness of
  the soil surface was dictating backscatter. Using
  the Landsat image alone for classification led to
  poor separability of the pasture classes.
  RADARSAT images alone, or together, also provided
  poor separability. Using a combination of the two
  types of imagery greatly increased the
  separability of the classes. The S7 image
  acquired in September was found to be the most
  useful for distinguishing between native and
  seeded pastures when added to the Landsat image
  but the September S1 image was found to provide
  the best increase in separability between crested
  wheatgrass and Russian wildrye. The S7 image
  acquired in May proved to be the least useful
  with respect to providing separability between
  classes. A combination of the Landsat bands (3,4,
  and 5), an NDVI transformation, Frost filtered
  RADARSAT images, Mean texture measure for
  RADARSAT images, Angular 2nd Moment and Standard
  Deviation texture measure images run on both the
  September RADARSAT images and band 4 of the
  Landsat image provided the best overall
  separability of pasture classes. Unsupervised
  classification showed the influence of geological
  features on the imagery but failed to
  discriminate pasture types. For the supervised
  classification, overall accuracy for the optimal
  combination of imagery and transformations was
  84.0, Kappa hat 76.7 for training sites, and
  73.5, Kappa hat 61.9 for randomly selected
  points. Although this level of accuracy does not
  allow for automated quantitative measurement of
  pasture areas by type, the classification
  obtained provides a means of visually identifying
  pasture species type for pure paddocks of
  Russian wildrye and native but less so for
  crested wheatgrass (accuracy for this class was
  low). In summary, the combination of C-band radar
  imagery and medium resolution optical imagery
  allows reasonable separation of Russian wildrye
  pasture from native pasture. This tested
  combination was not able to adequately separate
  native from crested wheatgrass it is suggested
  that optical imagery at a different phenological
  stage or radar imagery with a smaller wavelength
  (e.g. X-band), or with multiple polarization
  might be more profitably employed.

34
Shilong Mei
Making features movable in ArcGIS A
functionality of paleogeographic reconstruction
developed using ArcObjects and VBA

• In current GIS software and GIS applications,
  features, once digitized into a vector layer,
  have fixed present day locations in a selected
  coordinate system. To deal with paleogeographic
  information, there is a need to restore the past
  locations of features of interest. A few
  Paleocontinent Reconstruction software packages
  have been developed for geologists independently
  from GIS. These software packages do not have the
  powerful functionalities in data management, data
  display and spatial analysis of the conventional
  GIS software. Current GIS software packages,
  however, do not have the function to restore past
  locations of geological features, but do have the
  potential to realize it. Paleogeographic
  Information System (PGIS), proposed by Mei and
  Henderson (2002), is an approach to incorporate
  the Paleocontinent Reconstruction function into
  GIS. This approach has been realized in ArcMap by
  developing a Paleogeographic Reconstruction
  functionality using ArcObjects and Visual Basic
  for Application (VBA) embedded in ArcMap.

35
Sunghuan Moon
DSS traffic issues

• Calgary is one of the fastest growing cities in
  North America. The growth is expected to continue
  until the middle of 2030. As the city continues
  to grow, many new public facilities will be
  necessarily needed over the next 30 years.
  Locating new schools, and in particular high
  schools for grades 10 12, is a significant and
  political issue in City of Calgary. Site planning
  of schools can be examined in the context of
  spatial modeling methodologies focusing on
  maximizing students accessibility to their
  schools and minimizing the accessibility costs
  based on different algorithms. To solve these
  various accessibility patterns, several location
  models and spatial analysis methods have been
  used in geography, operational research and other
  disciplines. This paper presents an integrated
  spatial solution to the school site problem by
  combining location-allocation modeling and
  spatial interaction methodologies. Student
  population projections are analyzed in various
  aspects before implementing these models. The
  location-allocation modeling is used for locating
  new high schools depending on various situational
  parameters such as efficiency, equity, number of
  schools, and scale of economies. The spatial
  interaction model is used to estimate the new
  school location sensitivity, that is, variability
  of accessibility if the new locations change. GIS
  is used to solve various complex spatial
  problems. Powerful and flexible spatial modeling
  integration within GIS can contribute to
  extending the potential scope of GIS toward not
  only determining school locations, but also other
  spatial analysis and modeling applications.

36
Rupa Mukherjee
Spatial Analysis of Meso-Carnivores and Prey in
the Rocky Mountains

• Wildlife conservation in the Canadian Rockies is
  complex in nature, and present a challenge to
  conservationists. One method of understanding the
  dynamics of an ecological system is to model what
  is occurring in nature. Habitat suitability
  modelling attempts to replicate the wildlife
  habitat processes that occur in nature. Two goals
  were present within this study (1) To determine
  how the community species affect habitat
  suitability for the Canada lynx (Lynx canadensis)
  and (2) To determine changes in the use of lynx
  habitat over a period of three years using a
  Geographic Information System (GIS), coupled with
  logistic regression and AIC (Akaikes Information
  Criteria) statistical techniques. Species are
  part of a sophisticated network of community
  interactions, which introduces complexity in
  modelling the system. Three key species within
  the lynx community were identified for analysis
  Snowshoe hare (Lepus americanus), coyote (Canis
  latrans) and American marten (Martes americana).
  Hare is considered the most important source of
  prey for lynx (Buskirk and Ruggiero, 1994).
  Coyote and marten are regarded as common
  competitors of lynx for prey (hare) (Lachowski,
  1997 ODonoghue et al., 1998). All three species
  along with landscape attributes were incorporated
  into the lynx model for the three-year study
  period (1997, 1998 and 1999). Image comparisons
  between the three habitat suitability maps showed
  that models varied annually in their predictions
  of total high suitability habitat. All three
  species (hare, coyote and marten) were integral
  to the top models created for lynx in all three
  years. Northness, greenness and terrain
  ruggedness were found to be the most influential
  landscape attributes among the top lynx models.

37
Anthonia Onyeahialam
Assessment Modeling of Sage Grouse Breeding
Habitats in North Natrona, Wyoming A RS, SS and
Predictive Modeling Approach Towards

• This project presents results from an exploratory
  approach studying sage grouse breeding habitat,
  leks, in North Natrona County, Wyoming USA, using
  spatial statistical analysis, predictive
  modelling and Geographic Information Systems
  (GIS). It was found that sage grouse breeding
  locations present a pattern derived from a
  specific habitat selection process. Contributing
  habitat predictor variables in the models were
  generated from Landsat imageries using advanced
  image processing methods such as hierarchical
  classification, spectral pixel unmixing,
  knowledge based classification etc. Further, GIS
  was used extensively in data generation and
  analysis. Four final models that describe sage
  grouse breeding habitat selection were developed
  for multiple scales using logistic regression and
  multivariate adaptive regression splines (MARS).
  AIC, AICc and model averaging were used to aid
  the model selection process in identifying
  relevant predictors for lek locations and
  choosing the most appropriate model. Two of the
  models developed on the home range scale improved
  these predictions. Based on a large set of 83
  candidate models, important habitat predictor
  variables in the final models were elevation,
  distance to human development, slope, distance to
  roads, NDVI and distance to water. Sagebrush
  vegetation was not found among the most important
  predictor variables. Finally, a cumulative