MGIS Projects

MGIS Projects

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BACK 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).

BACK 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.

BACK 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 ESRI’s 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.

BACK 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.

BACK Bruce Burwell Implementing a Geographic Information System Using ESRI’s 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 ESRI’s (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 Microsoft’s 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 ESRI’s object oriented database is superior to previous methods of GIS development.

BACK 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.

BACK 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 (74°8′N, 81°13′). 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.

BACK 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.

BACK Jon Connick Benchmarking a Geospatial Store: ArcSDE and Oracle Spatial • This manuscript describes an evaluation of the spatial storage capabilities of ESRI’s ArcSDE and Oracle’s 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.

BACK 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 V=0.515(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 V=0.055 (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.

BACK 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 materials—especially those designed for use in higher education—be 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.

BACK 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.

BACK 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.

BACK 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 1980’s, 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 1990’s 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?

BACK 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 (E&P) 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.

BACK 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.

BACK 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.

BACK 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.

BACK 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 Microsoft’s Component Object Model to enable Selective Client-Server Feature Updating in ESRI’s 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.

BACK 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 user’s 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.

BACK 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.

BACK 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.

BACK 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.

BACK 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.

BACK 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.

BACK 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 Calgary’s 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.

BACK 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.

BACK 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 resort’s 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.

BACK 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

BACK 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 Akaike’s 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.

BACK 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.

BACK 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.

BACK 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.

BACK 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 (Akaike’s 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; O’Donoghue 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.

BACK 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 and spatial approach is presented for the study area on how the population viability of sage grouse can be assessed over time using MARS for species predictions and Markov chain models for deriving future landscape scenarios in the year 2011. The population viability of the species is based on the ability of a changing landscape to support its breeding habitat. This model indicates that the future available sage grouse habitats remain approximately constant. However, the spatial arrangement of the preferred habitats is becoming more centrally concentrated increasing potential risks to the population.

BACK Aaron Osicki Predicting the past: using GIS for archeological site distribution analysis and prediction modelling within Jasper National Park • This study investigates the spatial distribution of prehistoric aboriginal archaeological sites within Jasper National Park, so as to identify spatial patterns within the data, which in turn can be integrated into the creation of site prediction models for the area. The project is divided into two main sections. The first section discusses the current state of GIS use in archaeology, highlighting its application to archaeological site prediction modeling. Within this discussion, two of the more common predictive models used by archaeologists thus far, logistic regression and variable classification models, are focused on in regards to their structure and limitations. An alternate approach, site distribution analysis, is suggested which attempts to bypass some of the major limitations associated with these other models. In the second section, site distribution analysis methodology is applied to archaeological data for Jasper. Through the use of GIS and statistical software, the archaeological site data is spatially analyzed as to the nature of its distribution. Results of this analysis identify a significant trend in the distribution of prehistoric aboriginal archaeological sites within the geographic landscape of Jasper in relation to the natural resource availability of the region.

BACK Sergio Palladini ArcObject Development in Zone Design Using Visual Basic for Applications (VBA) • The Modifiable Areal Unit Problem is commonplace in the realm of geographical analysis. The MAUP presents issues concerning scale and configuration of geographic partitions that are representative of finer resolution spatial data. In order to compensate for the MAUP an Automated Zoning Procedure (AZP) has been suggested. In theory this algorithm manipulates spatial partitions into a set of zones that optimize a function of interest. There have been attempts to implement this procedure in a Geographical Information Systems (GIS) software environment. However, the AZP has not been implemented for the latest version of ArcGIS 8.3 desktop. As a result, this research is primarily focused on the construction of an Automated Zoning Procedure using ArcObjects development with Visual Basic for Applications (VBA). The constructed AZP program is executable in the ArcMap extension within the ArcGIS 8.3 platform. The program aggregates n number of zones into a smaller number of m zones where the Moran’s I statistic of spatial autocorrelation is the primary function under optimization.

BACK Joan Pereverzoff Development of a Rapid Assessment Technique for Identifying Human Disturbance Features in a Forested Landscape • Accurate and up to date inventories of natural and anthropogenic features in northern Canadian landscapes are critical for effective resource and wildlife management. Images derived from remote sensing offer the advantage of providing wide coverage of inaccessible areas at a variety of spatial resolutions. Panchromatic data from satellite images or aerial photographs are abundant, cover a large time period and are available at a range of prices. However, challenges exist in the efficient processing of high spatial resolution panchromatic data. The large volume of data and limited spectral characteristics contribute to lower accuracies in computerized image processing. This paper examines object-oriented image classification techniques as an alternative to the traditional pixel-based classification techniques. Object-oriented image classification works by first segmenting an image into meaningful image objects that can then be classified with a set of spectral and shape characteristics as well as logical statements (e.g., adjacency rules). Object-oriented image processing techniques were applied to two types of panchromatic data: a 0.75 m spatial resolution orthophotograph and a 5 m IRS image of a forested landscape in northern Alberta. The orthophotograph was segmented and the natural and anthropogenic features such as clearcuts, wellsites, and roads were classified with a high overall accuracy (88%, kˆ = 0.77). The larger IRS scene was more difficult to segment and detect the features of interest (82%, kˆ = 0.49). Results indicate that while expert input is required and the learning curve is steep, object-oriented image analysis is an improvement over manual aerial photograph interpretation and pixel-based image classification.

BACK Elizabeth Podgurny Habitat Modeling of Ord’s Kangaroo Rat for Southeastern Alberta • Ord’s kangaroo rat (Dipodomys ordii) is currently listed as an endangered species within the Province of Alberta. Although their presence is well documented within Alberta, some uncertainty remains regarding their distribution throughout the southeastern portion of the province. Knowledge of species distribution is essential for creating and implementing successful conservation management plans. Satellite imagery and a geographic information system (GIS) were used to accurately and efficiently model kangaroo rat habitat within southeastern Alberta. The model was designed using kangaroo rat presence data collected in the C.F.B. Suffield National Wildlife Area and adjacent areas. The presence data was related to GIS habitat layers to create a resource selection function model that describes the probability of use of an area by the species. The input habitat variables consisted of various GIS layers depicting exposed dunes and other sandy areas, roads, topography (i.e. slope), and measures of vegetation reflectance derived from multispectral satellite imagery (i.e. greenness, wetness and brightness). The resource selection function was estimated using logistic regression. Akaike Information Criteria (AIC) was used to select the habitat variables that provided the best logistic model to explain the presence data. Logistic regression provided the function coefficients, which were used to estimate resource use by kangaroo rats within the study area. The model was validated using a sub-set of the presence data that were not used to estimate the resource selection function. After verifying the reliability of the model, it was then applied to the study area to predict the relative abundance of the species. A map of the predicted distribution of kangaroo rats across their range in Alberta is one product of this work.

BACK Arthur Poon A SDSS approach to assessing land suitability for agriculture northeast China • Agriculture plays an important role in food production for the People’s Republic of China. Agricultural products are used as capital for international trade, as well as to feed the population. Despite this, the country’s arable land area is small, making it difficult to continually meet China’s needs. This project is intended to classify the land area of a designated study site into varying degrees of agricultural potential. This is achieved using a Spatial Decision Support System (SDSS), in which a land suitability assessment is performed by evaluating multiple criteria. The paper is presented in two parts. Part I, the literature review, discusses the theoretical issues about the concept of using SDSS in land suitability assessment. This part defines what SDSS is and how it has been used in past studies. It examines the background of the study site, and the rationale for performing this study. The study site is located in northeast China, where the staple cereal crop is spring wheat. Six spatial data sets will be analyzed and incorporated into the decision-making process: vegetation cover, mean annual temperature, slope gradient, hydrology, soil type and soil texture. These will be the criteria that will indicate whether a particular region is considered suitable or unsuitable for cultivation. Part II, the project implementation, describes the methodology in detail. The technique that will be employed is a Suitability Index Computation (SIC), a computer-based technique that assesses the various regions using a numerical scoring system.

BACK Wendy Proudfoot Comparison of Automatic & Manual Extraction of Wetland & Drainage Features, East Central Alberta • There is a need to monitor the amount of anthropogenic drainage in the Prairie Pothole Region (PPR) of Canada. Detection and mapping of drained wetlands and drainage features in the PPR has been conducted to date by stereoscopic interpretation of air photographs and/or manual digitization of features into a Geographic Information System. An accurate, automated method of extracting wetland, drained wetland, and drainage features would be beneficial because it would save time and thus translate into lower mapping costs. Traditional, pixel-based classification methods are not effective in extracting drained/dry wetlands and drainage ditches; the spectral characteristics of these features are similar, because the surface materials that comprise them are not distinct. A classification method that employs shape and context is necessary for successful feature extraction. The object-oriented classification software eCognition offers an alternative to pixel-based classifications. Pixels are grouped into objects; thus shape and context can be incorporated into the classification. The software attempts to approximate the way humans perceive the environment. The goal of this study was to conduct a preliminary evaluation of eCognition’s ability to extract wetlands, dry wetlands, drained wetlands, and drainage ditches from panchromatic air photographs of two study sites, with the aid of ancillary data. Band 4 of an orthorectified Landsat 7 ETM+ image, a binary “depressions” layer derived from a DEM, and a vector roads layer aided the classification. Accuracy assessment was performed using a pixel-based confusion matrix and an object-oriented method developed for this study. Both accuracy assessments yielded low accuracies in the drained wetland, dry wetland, and ditch classes, but showed that open water areas were successfully extracted. It was determined that although an object-oriented classifier such as eCognition provides more potential than pixel-based methods for automatically extracting drained/dry wetlands and ditches, the methodology fell short in approximating human perception and reasoning in extracting the features of interest in this study.

BACK Rebecca Rittson-Bennett Assessing the Effects of a Heli-portable 3D Seismic Survey on Grizzly Bear (Ursus Arctos) Distribution • Since the introduction of European settlers to North America, grizzly bear habitat has continued to shrink and undergo anthropogenic disturbance. With society’s high demand for natural resources and increasing ability to gain access to remote areas, it may prove impossible to stop human disturbance that is affecting grizzly bears and their habitat. Instead, managers must decide which activities are least distressing to grizzlies and limit disturbance. As a part of the Grizzly Bear Project within the Alberta Foothills Model Forest, this study was conducted to assess the effects of helicopter flights from heli-portable 3D seismic survey on grizzly bear movement and distribution. I analyzed GPS telemetry data collected over four summers: two years prior to the introduction of heli-surveys, one year of data collected during the summer of the surveys, and one year after the completion of the survey. Using a geographic information system (GIS), I qualitatively and quantitatively assessed the relation between the presence of helicopters on grizzly bear movement and distribution patterns. I contrasted grizzly distributions before and after the introduction of heli-surveys using kernel density estimators to approximate intensity of bear occurrence in the landscape, and to examine potential shifts in area of use between years. Helicopter intensity was measured at varying spatial scales, using a line density calculation to measure the amount of helicopter presence in an area over a predetermined amount of time. The measure of helicopter intensity was then compared to individual bear distributions in the pre-berry season. Overall, the majority of bears demonstrated varying degrees of aversion to the helicopter survey area. Of the bears that did not show aversion to the helicopter survey area, all appeared to have no detectable effects from the helicopter, meaning that they did not avoid or gravitate towards areas with high helicopter presence. As the frequency of heli-surveys increases in the future, the results of this study may prove useful in determining relationships between intense helicopter presence and grizzly bear activities.

BACK Saroj Aryal Decision Support System for Local Government in Nepal – Health Service Planning • This document studies some methodologies used in the Spatial Decision Support System and develops a decision support model that finds the suitable location for new service centres. This is a very useful tool for the local governments. Problem is studied on a remote district of Nepal. The researcher worked with the local people to collect the information and the data required. Health service accessibility was identified as a problem with the study of different published documents and by talking to the people at local level and then tried to address the problem by using simple but useful tools and techniques. This document gives some alternatives to the local decision makers in locating new health services. This model can be reutilized to address similar problem elsewhere.

BACK Rizwan Shahid Geographically Weighted Regression in Health: An Experimental Application to Cardiac Catheterization in Calgary • This study examines the local relationships between Cardiac Catheterization cases and socioeconomic variables in Calgary by using Geographically Weighted Regression (GWR), a technique developed to take into account spatial non-stationarity as well as to reduce the variance induced by non-stationarity in the model. Eight socioeconomic variables are found to be significant. The results display a spatial variation in the relationship between cases and independent variables that is modeled efficiently by GWR. Comparison of GWR with standard regression and spatial regression reveals that GWR may be a better technique; however, it does not accommodate spatial dependence completely. It is concluded that the current spatial pattern of disease can be better understood and modeled by GWR, and that this technique is eventually useful in predicting future trends of disease incidence and developing new facility locations.

BACK Jennifer Shea Impacts of Climate Change on Arctic Marine Mammals • Originating over 10,000 years ago, wine has established itself as a valuable commodity to both producers and consumers alike. Centuries of viticulture experience in Europe has resulted in a collection of vineyard regions that many vintners consider the finest conditions for growing grapes. In particular, France has taken steps to protect these regions with restrictive wine laws, claiming that the characteristics of their wine are as much a function of the geography of French vineyards as they are of the winemaker. This concept, referred to as ‘Terroir’ suggests that wine is a product of the soil, climatic and topographic environment as well as the wine making process. Recently there has been an influx of North American, Australian and South African wines to the international wine market and their success suggests conditions outside of France are equally capable of producing high quality wines. This research explores the notion of terroir in regions outside of Europe by focusing on the distribution of vineyards in the Los Carneros region of California. Logistic regression analyses is used to determine whether certain combinations of soil and microclimatic conditions influence the existence of vineyards in the Los Carneros region. Geographic Information Systems (GIS) and SPSS statistical software are used for the data processing and analysis and results indicate that topographic variables influence the location of vineyards to a greater degree than soil variables. In addition, a model with both soil and topographic variables included indicates the strongest association between vineyard location and associated variables. Further discussion of the impacts of climatic change on vineyards and their implications for geographic wine controls was also carried out.

BACK Mark Sherrington Measuring Boreal Forest Fragmentation Change in Response to Seismic Line, Wellsite and Road Revegetation with Scanned False-Colour Infrared Aerial Photography • The regeneration of resource sector disturbance (seismic lines, roads and wellsites) through forest succession reconnects the undisturbed landscape matrix when disturbance regeneration attains the pole sapling stage. The landscape matrix adjacent to disturbances regenerated to pole sapling and older stages have lower negative edge effects and fragmentation compared with less regenerated disturbances. Traditional aerial photograph interpretation and automated supervised classification of the scanned aerial photographs were applied in mapping the regeneration on disturbance. The manual interpretation of current and historic aerial photographs, combined with ground plots, was used to develop the representation of the natural-regeneration landscape (with disturbance regeneration), and a cumulative-disturbance (without regeneration) landscape. In the automated approach, supervised classification was able to separate the six structural stages characterizing forest succession on disturbance with the highest accuracy (65%) when spectral, Normalized Difference Vegetation Index (NDVI) and angular second moment (ASM) texture data were combined. The maximum likelihood classification using the ASM texture data separated the regenerating structural stages on disturbance most closely to the aerial photograph interpretation method. The automated approach achieved low separability between the shrub and young forest classes and therefore was not applied in measuring the landscape matrix fragmentation due to the low classification accuracy for the pole sapling structural stage.

BACK Robert Skakum Mountain Pine Beetle Red-attack Forest Defoliation Classification Using Stratified Landsat ETM+ Data in British Columbia, Canada • The identification and classification of mountain pine beetle, Dentroctonus ponderosa (Hopkins), red-attack defoliation patterns in a mature lodgepole pine (Pinus contorta) forest located in the Fort St. James Forest District, British Columbia, was accomplished using 1999 Landsat ETM+ satellite imagery, a 1999 field and aerial survey point dataset, and GIS forest inventory data. Unrelated variance in the observed spectral response at field and aerial survey points was reduced following image stratification with GIS forest inventory data and removal of other factors uncharacteristic to red-attack defoliation. The spectral variance at the observed points was primarily influenced by the natural variability in the forest and from a relatively small spectral influence of a few defoliated crowns within a small area. A maximum likelihood classification based on training areas developed from stratified field and aerial survey points was used to determine the percent classification accuracy with which ETM+ spectral data could predict the occurrence of red-attack beetle defoliation; a sample of healthy vegetation points was also developed in the area to train a healthy class. Classification accuracy for the red-attack class was 71% correct; the healthy class was 65% correct, which could have been higher if healthy training areas were collected in the field. An assessment of the classification was performed using 360 independent validation points. The result of the red-attack defoliation classification was a map showing stands with a high likelihood of containing small groups of red-attacked trees. Overall, the classification is consistent with the way in which mountain pine beetle infestations occurred in this area.

BACK Heng Sun GIS-based Analysis and Prediction of Residential Land Use Changes • Studying a city's past land development trend and predicting its future land use pattern are crucial for city planners to be able to make a sustainable development strategy for the city. This paper implements a land use classification for the City of Calgary, Alberta, Canada using an object-oriented approach for six Landsat TM and ETM+ images, simulates the land use pattern in the future using Markov chain analysis and cellular automata analysis, and calculates Shannon's Entropy (an urban sprawl index) based on the land use classification results. This research proves that an object-oriented approach can produce satisfactory classification results. It reveals the manner in which land use is likely to develop in the future, and demonstrates that urban sprawl continued to grow in Calgary during the years between 1985 and 2001.

MGIS Projects

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Trimble MGIS GPS Receivers

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MGIS 410 ELECTRONIC COMMERCE INFRASTRUCTURE AND MANAGEMENT

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Penn State University MGIS 596a Capstone Proposal for Kent Stanton

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MGIS 410: ELECTRONIC COMMERCE INFRASTRUCTURE AND MANAGEMENT

MGIS 410: ELECTRONIC COMMERCE INFRASTRUCTURE AND MANAGEMENT

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Sara Holm Penn State MGIS Program

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