A geographic information system (GIS) was used to create landform measurements and maps for elevation, slope, aspect, landform index, relative phenologic change, and slope position for 3 topographic quadrangles in Virginia. A set of known observation points of the Northern dusky flying squirrel (Glaucomys sabrinus) was used to build 3 models to delineate sites with landform characteristics equivalent to those known points. All models were built using squirrel observation points from 2 topographic quadrangles. The first model, called "exclusionary", excluded those pixels with landform characteristics different from the known squirrel pixels based on histogram analyses. Logistic regression was used to create the other 2 models. Each model resulted in an image of pixels considered equivalent to the known squirrel pixels. Each model excluded approximately 65% of the Highland study area, but the exclusionary model excluded the fewest known squirrel pixels (12.62%). Both logistic regression models excluded approximately 10% more known squirrel pixels than the exclusionary approach. The models were tested in the area of a third quadrangle with points known to be occupied by squirrels. After the model was applied to the third topographic quadrangle, the exclusionary model excluded the least amount of full-area pixels (79.30%) and only 14.81% of the known squirrel pixels. The second logistic regression excluded 81.16 % of the full area and no known squirrel pixels. All models proved useful in quickly delineating pixels equivalent to areas where wildlife were known to occur. / Master of Science

The purpose of this study consists of gaining an understanding about Augmented Reality (AR) and if this technology can help land-surveyors to visualize cadastral parcels using an iOS app. In addition, the app is also used to get insights of what it takes for an AR system to replace 2D paper maps completely. In land-surveyors daily work, they usually bring annotated 2D paper maps to locate their assets when they do field work. However, the 2D paper map can be cumbersome to use because the map visualizes assets in 2D while the working environment for land-surveyors is in 3D. Therefore, this study presents an AR app that can visualize cadastral parcels in 3D in collaboration with a company called InfoTrader. This dissertation utilizes a qualitative methodology with a design and creation strategy as well as semi-structured interviews. To get feedback and evaluate the proposed app it was tested with professionals with experience in the land-surveying business. The findings from testing the app indicated that the app could be very useful in different scenarios. Nevertheless, to completely replace the 2D paper map, the AR system should integrate all the layers of information that the 2D map provides.

In partnership with the USDA Forest Service and the Utah Division of Forestry, Fire, and State Lands, a geographic information system (GIS) was used to create a wildland fire assessment methodology. GIS layers (or themes) include topography, infrastructure, vegetation, climate, "sensitive" natural values, and fire history. Two phases of assessment are presented: a preliminary analysis designed for planning use at the landscape level, and a detailed analysis for site-specific use. Results of the phase 1 assessment are density grids delineating areas of high fire occurrence and suggesting to managers where a phase 2 assessment is needed. By using the environmental, human, and topographic information listed earlier, probability maps of wildland fire occurrence were developed with a GIS and multiple logistic regression. In both cases, high fire danger areas can be overlaid with protection areas (natural or human-made value areas) to identify critical fire danger areas. Because GIS is commonly used in land management, it facilitates the sharing and updating of geographic information between resource professionals of different agencies and organizations. Local officials will be able to use GIS spatial and tabular data for planning, zoning, and fire ordinance development. Land management specialists can locate, prioritize, and target high and critical fire danger areas for presuppression mitigation efforts such as prescribed fires, defensible-space projects, and fire-break construction (e.g., greenbelts, parkways). Furthermore, GIS assessment layers can be manipulated and exported to create the required raster GIS data themes for FARSITE (a fire growth simulator). Fire managers will be able to spatially predict fire spread, intensity, and behavior under complex topographic and climatic conditions. This method, combined with the expertise of fire specialists, offers an improved and cost-effective assessment technique for wildland fire management.

This research demonstrates the ability to integrate a computer simulation model with a geographic information system (GIS) to predict forest community dynamics in both the spatial and temporal dimensions. A landscape scale computer simulation model, LANDSIM, was coupled with the Arc/Info GIS to simulate the interaction of forest fires and forest succession at Bryce Canyon National Park, Utah, and to produce maps of the predicted community types. The sensitivity of the model was tested with respect to the fire return interval, maximum neighbor spread, and the effect of slope upon the spread of simulated fires. The model predicts that each fire return interval will result in an unique distribution of community types upon the landscape. The model's results are discussed in terms of their implications for management alternatives at Bryce Canyon National Park.

Southeast Louisiana is susceptible to the impact of subsidence due to natural and anthropogenic processes including sediment compaction and loading, fluid withdrawal, and faulting. Subsidence rates in Southeast Louisiana are higher than anywhere else in the United States, and the impact of subsidence rates on industrial complexes has not been studied. Spatial interpolation methods were analyzed to determine the best fit for subsidence rates and to create a predictive surface for the lower Mississippi River Industrial corridor (LMRIC). Empirical Bayesian kriging, ordinary kriging, universal kriging, and inverse distance weighted interpolation methods were applied to the 2004 National Oceanic and Atmospheric Administration (NOAA) published Technical Report #50 dataset and cross-validation methods were utilized to determine the accuracy of each method. The mean error and root mean square error were calculated for each interpolation method, then used to detect bias and compare the predicted value with the actual observation value. Cross-validation estimates are comparable for each method statistically and visually; however, the results indicate the empirical Bayesian kriging interpolation method is the most accurate of the methods using the lowest mean error and root mean square error scores. Digital elevation models for the years 2025, 2050, and 2075 were developed based on the predictive surface of subsidence rates using the results from the empirical Bayesian kriging interpolation method. Results indicate that by 2025, 31.4% of landmass in the LMRIC will be below 0 m NAVD88, with 40.4% below 0 m NAVD88 by 2050, and 51.8% by 2075. Subsidence rates in the LMRIC range from approximately 16 mm to less than one mm per year. Nine of the 122 industrial complexes located in the LMRIC are estimated to be below 0 m NAVD88 by the year 2075. Limited economic impacts can be inferred based on the number of facilities impacted; however, service disruptions due to subsidence impacting infrastructure surrounding these industrial complexes would have catastrophic economic impacts on a regional, state, and national level.

Scene mapping is an integral part of processing a forensic scene with scattered human remains. By utilizing the appropriate mapping technique, investigators can accurately document the location of human remains and maintain a precise geospatial record of this evidence at a scene. Global positioning system (GPS) units have been used for years to survey the spatial distribution of large-scale archaeological sites. However, differential global positioning (DGPS) unit now provide decreased positional error suitable for small-scale surveys, such as forensic scenes. Because of the lack of knowledge concerning this utility in mapping a scene, controlled research is necessary to determine the practicality of using DGPS in mapping scattered human remains in different environments. The purpose of this research is to quantify the accuracy of a DGPS unit for mapping skeletal dispersals and to determine the applicability of this utility in mapping dispersed remains. First, the accuracy of the DGPS unit was determined using known survey markers in different environments. Secondly, several simulated scenes were constructed and mapped in open, tree-covered, and structure-obstructed environments using the DGPS. Factors considered included the extent of the dispersal, data collection time, and the use of offsets. Data were differentially postprocessed and compared in a geographic information system (GIS) to evaluate the most efficient recordation methods. Results of this study show that the DGPS is a viable option for mapping human remains in open areas. Furthermore, guidelines for accurate scene mapping using a DGPS unit will be provided, along with a discussion concerning the integration of DGPS into GIS for scene analysis and presentation

Myers first identified the world’s 25 biodiversity hotspots and pioneered innovative ideas about the usefulness of biodiversity models for establishing long-term resource conservation strategies at global scales. Since Myers, most of the subsequent studies using hotspot science for biodiversity modeling have used large spatial scales like countries, provinces or states, and other biogeoraphic regions. The California Floristic Province continues to be one of the recognized global biodiversity hotspots. Our study site, San Luis Obispo County is within this hotspot and we created a map of plant biodiversity hotspots at the county scale using GIS technology. We wanted to determine the effectiveness and applicability of biodiversity hotspot mapping at this scale with anticipation that the map will serve as a new tool for establishing long-term resource conservation strategies in the County. Our plant biodiversity hotspot map is based on distribution data collected from herbarium specimens of San Luis Obispo County’s rare flora. These data were extracted from the Hoover Herbarium at Cal Poly and manually digitized into GIS. We built a model with GIS to identify, locate, and quantify the resultant hotspots from the data. The overall approach was successful at identifying and quantifying the attributes and geographic extents of plant biodiversity hotspots at the county scale. Our results are highly applicable for establishing local and regional plant conservation priorities at lower resolutions, which is frequently where land acquisition and reserve establishment occurs. We conclude that biodiversity hotspot modeling with GIS is an effective tool that can be applied to many other finer-scale biological inventories for conservation purposes.

The Yorkshire Dales National Park contains some of the UK’s most extensive and well-preserved prehistoric landscapes. Of particular interest are a number of coaxial field systems, which cover hundreds of hectares and exhibit significant time-depth, yet remain little studied and poorly understood in relation to comparable resources elsewhere in Britain and north western Europe. This research aims to address this situation, bringing together existing disparate source materials for the first time, alongside supplementary field observation, to develop a detailed record of the coaxial landscapes. Using a Geographic Information System to manage, interpret and interrogate the combined datasets, analysis focuses on form and character, and explores prehistoric use of the iconic landscape. The study seeks to enhance our knowledge and understanding of the landscapes’ place in space and time, setting them against the backdrop of systems elsewhere, and attempts to place them within the context of later prehistoric society. The research, conducted in association with the Yorkshire Dales National Park Authority, also informs the management and public understanding of the archaeological resource of the Dales via the Historic Environment Record. / Arts and Humanities Research Council Collaborative Doctoral Award.

A geodatabase and a data management program have been created to store and manipulate cave and karst feature data from the Bahamas. A geographic information system was used to recognize any spatial patterns in the cave and karst data from San Salvador Island. Elevation data for banana holes, vadose pits and flank margin caves were obtained from a digital elevation model and are consistent with values predicted by the Carbonate Island Karst Model. The slope and aspect of the hill on which a flank margin cave is found showed no relationship to cave sizes and shapes, emphasizing the hypogenic nature of flank margin caves. The digital elevation model further demonstrated the position of lakes on San Salvador Island during the last interglacial (OIS 5e) highstand, and the lack of flank margin caves along the shores of these lakes provides evidence for a paleoclimate on San Salvador Island similar to today?s.

West Nile virus has become a major risk to humans since its first appearance in New York City in 1999. Physicians and state health officials are interested in new and more efficient methods for monitoring disease spread and predicting future outbreaks. This study modeled habitat suitability for mosquitoes that carry West Nile virus. Habitat characteristics were used to derive risk maps for the entire state of Mississippi. Statistical significance tests yielded objective evidence for choosing among many habitat variables. Variables that were significantly correlated with diagnosed human cases for 2002 were combined in weighted linear algebraic models using a geographic information system (GIS). Road density, slope, and summer precipitation minus evaporation (P-E) were the most significant variables. GIS-based model results were compared with results from logistic regression models. The algebraic model was preferred when validated by 2003 human cases. If adopted, GIS-based risk models can help guide mosquito control efforts.