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Determining the Suitability of Functional Landscapes and Wildlife Corridors Utilizing Conservation GIS Methods in Denton County, Texas.

Description: Denton County's unique cultural and natural landscape has undergone dramatic transformations during the past two centuries due to agricultural, urban and suburban processes which accelerated the loss and removal of native habitat and wildlife. This research sought out to identify the remaining natural areas which retain their natural features and support wildlife. Research methodology included fundamental principles of Conservation Planning, Geographical Information Systems, and Habitat Evaluation Procedures for identifying remnant functional landscapes and wildlife corridors. The final results suggest that Denton County's rural landscape retains the functional properties and elements suitable for habitat conservation and wildlife corridors, while also pointing to the fundamental obstacles to conservation posed by continued growth and private landownership.
Date: August 2007
Creator: Sales, Joshua
Partner: UNT Libraries

Developing a Wildlife Tracking Extension for ArcGIS

Description: Wildlife tracking is an essential task to gain better understanding of the migration pattern and use of space of the wildlife. Advances in computer technology and global positioning systems (GPS) have lowered costs, reduced processing time, and improved accuracy for tracking wild animals. In this thesis, a wildlife tracking extension is developed for ArcGIS 9.x, which allows biologists and ecologists to effectively track, visualize and analyze the movement patterns of wild animals. The extension has four major components: (1) data import; (2) tracking; (3) spatial and temporal analysis; and (4) data export. Compared with existing software tools for wildlife tracking, the major features of the extension include: (1) wildlife tracking capabilities using a dynamic data layer supported by a file geodatabase with 1 TB storage limit; (2) spatial clustering of wildlife locations; (3) lacunarity analysis of one-dimensional individual animal trajectories and two-dimensional animal locations for better understanding of animal movement patterns; and (4) herds evolvement modeling and graphic representation. The application of the extension is demonstrated using simulated data, test data collected by a GPS collar, and a real dataset collected by ARGOS satellite telemetry for albatrosses in the Pacific Ocean.
Date: May 2009
Creator: Chen, Cai
Partner: UNT Libraries

The Study of Temporal and Spatial Variability of Degree Day Factor of Snowmelt in Colorado

Description: Snowmelt is one of the major sources of surface water supply and ground-water recharge in high elevation areas and can also cause flooding in snow dominated watersheds. Direct estimation of daily snowmelt requires daily snow water equivalent (SWE) measurements that are not always available, especially in places without monitoring stations. There are two alternative approaches to modeling snowmelt without using direct measurements of SWE, temperature-based and energy-based models. Due to its simplicity, computational efficiency, and less input data requirement, the temperature-based method is commonly used than the energy-based method. In the temperature-index approach snowmelt is estimated as a linear function of average air temperature, and the slope of the linear function is called the degree-day factor (DDF). Hence, the DDF is an essential parameter for utilizing the temperature-based method to estimate snowmelt. Thereby, to analyze the spatial properties of DDF, 10 years DDF from the entire state of Colorado was calculated for this research. Likewise, to study the temporal properties, DDFs for 27 years from the White Yampa water basin and the Colorado Headwaters water basin were calculated. As a part of the spatial analysis, the calculated DDFs were correlated with spatial variables (slope, aspect, latitude and elevation) and a spatial correlation graph was created to observe the possibility of predicting DDF. Also a multivariate regression model was prepared using these spatial variables to predict the DDF using spatial variables. Further, the DDFs calculated from Colorado headwaters and the White Yampa water basins were correlated for annual temporal variation, daily variation, variation with peak snow water equivalent and variation with important temporal cycles like accumulation period and melting period of snowmelt. The result obtained from this study showed that the variability of DDF is more dependent upon temporal factors compared to the spatial factors. Also, the results showed that predicting ...
Date: May 2016
Creator: Pokhrel, Pranav
Partner: UNT Libraries

County Level Population Estimation Using Knowledge-Based Image Classification and Regression Models

Description: This paper presents methods and results of county-level population estimation using Landsat Thematic Mapper (TM) images of Denton County and Collin County in Texas. Landsat TM images acquired in March 2000 were classified into residential and non-residential classes using maximum likelihood classification and knowledge-based classification methods. Accuracy assessment results from the classified image produced using knowledge-based classification and traditional supervised classification (maximum likelihood classification) methods suggest that knowledge-based classification is more effective than traditional supervised classification methods. Furthermore, using randomly selected samples of census block groups, ordinary least squares (OLS) and geographically weighted regression (GWR) models were created for total population estimation. The overall accuracy of the models is over 96% at the county level. The results also suggest that underestimation normally occurs in block groups with high population density, whereas overestimation occurs in block groups with low population density.
Date: August 2010
Creator: Nepali, Anjeev
Partner: UNT Libraries

Parcel-Based Change Detection Using Multi-Temporal LiDAR Data in the City of Surrey, British Columbia, Canada

Description: Change detection is amongst the most effective critical examination methods used in remote sensing technology. In this research, new methods are proposed for building and vegetation change detection using only LiDAR data without using any other remotely sensed data. Two LiDAR datasets from 2009 and 2013 will be used in this research. These datasets are provided by the City of Surrey. A Parcel map which shows parcels in the study area will be also used in this research because the objective of this research is detecting changes based on parcels. Different methods are applied to detect changes in buildings and vegetation respectively. Three attributes of object –slope, building volume, and building height are derived and used in this study. Changes in buildings are not only detected but also categorized based on their attributes. In addition, vegetation change detection is performed based on parcels. The output shows parcels with a change of vegetation. Accuracy assessment is done by using measures of completeness, correctness, and quality of extracted regions. Accuracy assessments suggest that building change detection is performed with better results.
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Date: December 2016
Creator: Yigit, Aykut
Partner: UNT Libraries

Spatial Analysis of North Central Texas Traffic Fatalities 2001-2006

Description: A traditional two dimensional (planar) statistical analysis was used to identify the clustering types of North Central Texas traffic fatalities occurring in 2001-2006. Over 3,700 crash locations clustered in ways that were unlike other researched regions. A two dimensional (x and y coordinates) space was manipulated to mimic a one dimensional network to identify the tightest clustering of fatalities in the nearly 400,000 crashes reported from state agencies from 2003-2006. The roadway design was found to significantly affect crash location. A one dimensional (linear) network analysis was then used to measure the statistically significant clustering of flow variables of after dark crashes and daylight crashes. Flow variables were determined to significantly affect crash location after dark. The linear and planar results were compared and the one dimensional, linear analysis was found to be more accurate because it did not over detect the clustering of events on a network.
Date: December 2010
Creator: Rafferty, Paula S.
Partner: UNT Libraries

GIS application in emergency management of terrorism events on the University of North Texas campus.

Description: This thesis presents a Web-based geographic information system (GIS) application for campus emergency management that allows users to visualize, integrate, and analyze student population, facilities, and hazard data for efficient emergency management of University of North Texas before, during, and after a terrorism event. End-users can locate and search the source area of an event on a digital map from the ArcIMS-based Website. The website displays corresponding population information and attributes of impacted facilities in real time. School officials and first responders including police, firefighters and medical personnel can promptly plan the appropriate rescue and response procedures according to the displayed results. Finally, the thesis outlines the limitations of Web-based GIS in the arena of campus emergency management.
Date: August 2008
Creator: Tsang, Yuenting
Partner: UNT Libraries

Selecting Optimal Residential Locations Using Fuzzy GIS Modeling

Description: Integrating decision analytical techniques in geographic information systems (GIS) can help remove the two primary obstacles in spatial decision making: inaccessibility to required geographic data and difficulties in synthesizing various criteria. I developed a GIS model to assist people seeking optimal residential locations. Fuzzy set theory was used to codify criteria for each factor used in evaluating residential locations, and weighted linear combination (WLC) was employed to simulate users' preferences in decision making. Three examples were used to demonstrate the applications in the study area. The results from the examples were analyzed. The model and the ArcGIS Extension can be used in other geographic areas for residential location selection, or in other applications of spatial decision making.
Date: December 2006
Creator: Tang, Zongpei
Partner: UNT Libraries

Using Geographic Information Systems for the Functional Assessment of Texas Coastal Prairie Freshwater Wetlands Around Galveston Bay

Description: The objective of this study was to deploy a conceptual framework developed by M. Forbes using a geographic information system (GIS) approach to assess the functionality of wetlands in the Galveston Bay Area of Texas. This study utilized geospatial datasets which included National Wetland Inventory maps (NWI), LiDAR data, National Agriculture Imagery Program (NAIP) imagery and USGS National Land Cover data to assess the capacity of wetlands to store surface water and remove pollutants, including nitrogen, phosphorus, heavy metals, and organic compounds. The use of LiDAR to characterize the hydrogeomorphic characteristics of wetlands is a key contribution of this study to the science of wetland functional assessment. LiDAR data was used to estimate volumes for the 7,370 wetlands and delineate catchments for over 4,000 wetlands, located outside the 100-yr floodplain, within a 2,075 square mile area around Galveston Bay. Results from this study suggest that coastal prairie freshwater wetlands typically have a moderate capacity to store surface water from precipitation events, remove ammonium, and retain phosphorus and heavy metals and tend to have a high capacity for removing nitrate and retainremove organic compounds. The results serve as a valuable survey instrument for increasing the understanding of coastal prairie freshwater wetlands and support a cumulative estimate of the water quality and water storage functions on a regional scale.
Date: May 2010
Creator: Enwright, Nicholas
Partner: UNT Libraries

Comparison of IKONOS Derived Vegetation Index and LiDAR Derived Canopy Height Model for Grassland Management.

Description: Forest encroachment is understood to be the main reason for prairie grassland decline across the United States. In Texas and Oklahoma, juniper has been highlighted as particularly opportunistic. This study assesses the usefulness of three remote sensing techniques to aid in locating the areas of juniper encroachment for the LBJ Grasslands in Decatur, Texas. An object based classification was performed in eCognition and final accuracy assessments placed the overall accuracy at 94%, a significant improvement over traditional pixel based methods. Image biomass was estimated using normalized difference vegetation index (NDVI) for 1 meter resolution IKONOS winter images. A high correlation between the sum of NDVI for tree objects and field tree biomass was determined where R = 0.72, suggesting NDVI sum of a tree area is plausible. However, issues with NDVI saturation and regression produced unrealistically high biomass estimates for large NDVI. Canopy height model (CHM) derived from 3-5m LiDAR data did not perform as well. LiDAR typically used for digital elevation model (DEM) production was acquired for the CHM and produced correlations of R = 0.26. This suggests an inability for this particular dataset to identify juniper trees. When points that registered a tree height where correlated with field values, an R = 0.5 was found, suggesting denser point spacing would be necessary for this type of LiDAR data. Further refining of the methods used in this study could yield such information as the amount of juniper tree for a given location, fuel loads for prescribed burns and better information for the best approach to remove the juniper and ultimately management juniper encroachment into grasslands.
Date: December 2009
Creator: Parker, Gary
Partner: UNT Libraries

High Resolution Satellite Images and LiDAR Data for Small-Area Building Extraction and Population Estimation

Description: Population estimation in inter-censual years has many important applications. In this research, high-resolution pan-sharpened IKONOS image, LiDAR data, and parcel data are used to estimate small-area population in the eastern part of the city of Denton, Texas. Residential buildings are extracted through object-based classification techniques supported by shape indices and spectral signatures. Three population indicators -building count, building volume and building area at block level are derived using spatial joining and zonal statistics in GIS. Linear regression and geographically weighted regression (GWR) models generated using the three variables and the census data are used to estimate population at the census block level. The maximum total estimation accuracy that can be attained by the models is 94.21%. Accuracy assessments suggest that the GWR models outperformed linear regression models due to their better handling of spatial heterogeneity. Models generated from building volume and area gave better results. The models have lower accuracy in both densely populated census blocks and sparsely populated census blocks, which could be partly attributed to the lower accuracy of the LiDAR data used.
Date: December 2009
Creator: Ramesh, Sathya
Partner: UNT Libraries

Urban surface characterization using LiDAR and aerial imagery.

Description: Many calamities in history like hurricanes, tornado and flooding are proof to the large scale impact they cause to the life and economy. Computer simulation and GIS helps in modeling a real world scenario, which assists in evacuation planning, damage assessment, assistance and reconstruction. For achieving computer simulation and modeling there is a need for accurate classification of ground objects. One of the most significant aspects of this research is that it achieves improved classification for regions within which light detection and ranging (LiDAR) has low spatial resolution. This thesis describes a method for accurate classification of bare ground, water body, roads, vegetation, and structures using LiDAR data and aerial Infrared imagery. The most basic step for any terrain modeling application is filtering which is classification of ground and non-ground points. We present an integrated systematic method that makes classification of terrain and non-terrain points effective. Our filtering method uses the geometric feature of the triangle meshes created from LiDAR samples and calculate the confidence for every point. Geometric homogenous blocks and confidence are derived from TIN model and gridded LiDAR samples. The results from two representations are used in a classifier to determine if the block belongs ground or otherwise. Another important step is detection of water body, which is based on the LiDAR sample density of the region. Objects like tress and bare ground are characterized by the geometric features present in the LiDAR and the color features in the infrared imagery. These features are fed into a SVM classifier which detects bare-ground in the given region. Similarly trees are extracted using another trained SVM classifier. Once we obtain bare-grounds and trees, roads are extracted by removing the bare grounds. Structures are identified by the properties of non-ground segments. Experiments were conducted using LiDAR samples and Infrared imagery ...
Date: December 2009
Creator: Sarma, Vaibhav
Partner: UNT Libraries

Water systems, water policy, and Karst terrain: An analysis of the complex relationships between geology, economy, public perceptions, and policy in southern Trelawny, Jamaica.

Description: Jamaica has an abundance of freshwater resources, however, a lack of infrastructure makes treated, piped water inaccessible in many areas. Through literature reviews and site visits, this thesis is an analysis of how the people and land, and money and policy, interact with one another in relation to Jamaica's freshwater resources and water infrastructure. Special attention is given to the island's type-example Cockpit karst geology; tourism, mining, and farming's relation to this karst; types of water delivery systems in rural southern Trelawny's Cockpit Country; southern Trelawny residents' perceptions of the water situation; and policy and development goals in the context of Jamaica and southern Trelawny. I hope to bring attention to the unique social, geologic, and developmental context of water in Jamaica, and more specifically to garner attention for major water infrastructure improvements in south Trelawny. A number of recommendations for improvements with policy and infrastructure are made.
Access: This item is restricted to the UNT Community Members at a UNT Libraries Location.
Date: December 2005
Creator: McCall, Sarah
Partner: UNT Libraries

Finding Terroir in Southwest Iowa

Description: Terroir combines the physical landscape of the vineyard with the grapevines and the methods and techniques used to produce wine from the grapes. This study used a GIS to identify the characteristics of the physical landscape in Pottawattamie, Mills, Montgomery, Fremont, and Page counties in southwestern Iowa. The components were combined in the GIS using a weighted linear index to identify areas suitable for vineyard development and to identify the general characteristics of the area. Vineyard owners were interviewed to help determine the weighting system to use in the GIS and to determine their perceptions of how the physical landscape impacts their vineyards, as well as to determine what grape varieties they plant in their vineyards and their decisions on making wine from these grapes. This information was collected to identify whether the vineyard owners had developed a sense of place for their vineyards and how this sense might aid them in the development of a terroir for their wines. The resulting perceptions about the individual wineries were then considered in conjunction with the results from the GIS modeling to understand how the physical landscape influences the concepts of sense of place and terroir in southwest Iowa. The physical landscape of southwest Iowa was fairly uniform, as were the grape varietals planted in the vineyards. This created a measure of similarity among the wineries, while individuality between wineries was then created by the wine-makers as they used different techniques to produce wine from the grapes. This allows each winery to develop a sense of place, yet be part of a larger sense of place that encompasses multiple wineries within the area.
Date: August 2013
Creator: Deines, Dory
Partner: UNT Libraries

Automated Treetop Detection and Tree Crown Identification Using Discrete-return Lidar Data

Description: Accurate estimates of tree and forest biomass are essential for a wide range of applications. Automated treetop detection and tree crown discrimination using LiDAR data can greatly facilitate forest biomass estimation. Previous work has focused on homogenous or single-species forests, while few studies have focused on mixed forests. In this study, a new method for treetop detection is proposed in which the treetop is the cluster center of selected points rather than the highest point. Based on treetop detection, tree crowns are discriminated through comparison of three-dimensional shape signatures. The methods are first tested using simulated LiDAR point clouds for trees, and then applied to real LiDAR data from the Soquel Demonstration State Forest, California, USA. Results from both simulated and real LiDAR data show that the proposed method has great potential for effective detection of treetops and discrimination of tree crowns.
Date: May 2013
Creator: Liu, Haijian
Partner: UNT Libraries

Quantitative Comparison of Lidar Data and User-generated Three-dimensional Building Models From Google Building Maker

Description: Volunteered geographic information (VGI) has received increased attention as a new paradigm for geographic information production, while light detection and ranging (LiDAR) data is widely applied to many fields. This study quantitatively compares LiDAR data and user-generated 3D building models created using Google Building Maker, and investigate the potential applications of the quantitative measures in support of rapid disaster damage assessment. User-generated 3D building models from Google Building Maker are compared with LiDAR-derived building models using 3D shape signatures. Eighteen 3D building models are created in Fremont, California using the Google Building Maker, and six shape functions (distance, angle, area, volume, slope, and aspect) are applied to the 18 LiDAR-derived building models and user-generated ones. A special case regarding the comparison between LiDAR data and building models with indented walls is also discussed. Based on the results, several conclusions are drawn, and limitations that require further study are also discussed.
Date: August 2012
Creator: Liu, Yang
Partner: UNT Libraries

Gis, Modeling And Human Civilization: The Birth Of Geo-social Engineering

Description: Computer-based, mathematical models have significant value in describing the processes behind urban development and its inhabitants. The following research describes the theories and concepts behind modeling and offers insight into the potential future of the field. First, the research covers a brief history of applicable modeling strategies. This is followed by a summary of current popular approaches. The numerical background of geo-social engineering is developed through mathematical techniques. Geo-social engineering is the integration of modeling into the basic design human civilization. The mathematical models will be incorporated into a design of a computer program. From this, a possible geo-social model structure is presented and its architecture is described.
Date: December 2011
Creator: Morris, E. Scott
Partner: UNT Libraries

Assessment of Post-earthquake Building Damage Using High-resolution Satellite Images and LiDAR Data - a Case Study From Port-au-prince, Haiti

Description: When an earthquake happens, one of the most important tasks of disaster managers is to conduct damage assessment; this is mostly done from remotely sensed data. This study presents a new method for building detection and damage assessment using high-resolution satellite images and LiDAR data from Port-au-Prince, Haiti. A graph-cut method is used for building detection due to its advantages compared to traditional methods such as the Hough transform. Results of two methods are compared to understand how much our proposed technique is effective. Afterwards, sensitivity analysis is performed to show the effect of image resolution on the efficiency of our method. Results are in four groups. First: based on two criteria for sensitivity analysis, completeness and correctness, the more efficient method is graph-cut, and the final building mask layer is used for damage assessment. Next, building damage assessment is done using change detection technique from two images from period of before and after the earthquake. Third, to integrate LiDAR data and damage assessment, we showed there is a strong relationship between terrain roughness variables that are calculated using digital surface models. Finally, open street map and normalized digital surface model are used to detect possible road blockages. Results of detecting road blockages showed positive values of normalized digital surface model on the road centerline can represent blockages if we exclude other objects such as cars.
Date: August 2014
Creator: Koohikamali, Mehrdad
Partner: UNT Libraries

Effects of Vegetation Structure and Canopy Exposure on Small-scale Variation in Atmospheric Deposition Inputs to a Mixed Conifer Forest in California

Description: Data on rates of atmospheric deposition is limited in many montane ecosystems, where high spatial variability in meteorological, topographic, and vegetation factors contributes to elevated atmospheric inputs and to the creation of deposition hotspots. Addressing the ecological consequences of increasing deposition in these areas will require a better understanding of surface controls influencing atmospheric deposition rates at both large and small-scales. The overarching objective of this thesis research was to understand the influence of vegetation structure and canopy exposure on small-scale patterns of atmospheric sulfate, nitrate, and chloride deposition inputs to a conifer forest in the Santa Cruz Mountains, California. Throughfall ion fluxes (i.e., ions delivered in water that pass from the forest canopy to the forest floor), bulk deposition (i.e., primarily wet deposition), and rainfall data were collected during the rainy period from October 2012 to May 2013. Throughfall SO42-, Cl-, and NO3- fluxes were measured beneath eight clusters of Douglas fir (Pseudotsuga menziesii) trees (three trees per cluster) differing in tree size (i.e., diameter at breast height; DBH) and canopy exposure. In each cluster, a throughfall collector was placed 1-meter from the bole of an individual tree, for a total of 24 individual collectors. The position of each throughfall collector was recorded with a Trimble® GPS. In addition, tree height, tree diameter, and leaf area index, were measured for all trees. LiDAR data were obtained from GeoEarthScope’s Northern California Airborne LiDAR project and used to model the elevation (DEM), canopy surface height (DSM), tree height (CHM), slope, and curvature of the canopy surface across the entire study area. Over the rainy season, total throughfall flux of SO42--S, a conservative tracer of total deposition (wet + dry + fog), to Douglas fir clusters ranged from 1.44 - 3.84 kg S ha-1 wet season-1, while dry and fog deposition ranged ...
Date: May 2014
Creator: Griffith, Kereen
Partner: UNT Libraries

Estimating Buruli Ulcer Prevalence in Southwestern Ghana

Description: Mycobacterium ulcerans is sweeping across sub-Saharan Africa, but little is known about the mode of transmission and its natural reservoirs. Since the only effective treatment is excision of the infection and surrounding tissue, early diagnosis and treatment is the only way to reduce the havoc associated with Buruli ulcer. Using data from a national case search survey conducted in Ghana during 2000 and suspected risk factors this study tests the hypothesized factors and probes the challenges of developing a spatial epidemiological regression model to explain Buruli ulcer prevalence in the southwestern region of Ghana representing 42 districts. Results suggest that prevalence is directly related to the degree of land cover classified as soil, elevation differential, and percent rural population of the area.
Date: August 2007
Creator: Denton, Curtis James
Partner: UNT Libraries

Archaeological Site Vulnerability Modeling for Cultural Resources Management Based on Historic Aerial Photogrammetry and LiDAR

Description: GIS has been utilized in cultural resources management for decades, yet its application has been largely isolated to predicting the occurrence of archaeological sites. Federal and State agencies are required to protect archaeological sites that are discovered on their lands, but their resources and personnel are very limited. A new methodology is evaluated that uses modern light detection and ranging (LiDAR) and historic aerial photogrammetry to create digital terrain models (DTMs) capable of identifying sites that are most at risk of damage from changes in terrain. Results revealed that photogrammetric modeling of historic aerial imagery, with limitations, can be a useful decision making tool for cultural resources managers to prioritize conservation and monitoring efforts. An attempt to identify key environmental factors that would be indicative of future topographic changes did not reveal conclusive results. However, the methodology proposed has the potential to add an affordable temporal dimension to future digital terrain modeling and land management. Furthermore, the methods have global applicability because they can be utilized in any region with an arid environment.
Date: August 2015
Creator: Helton, Erin King
Partner: UNT Libraries

Exceedance Frequency Analysis of Urban Stormwater Quality and Its Relation to Land Use Change, Denton, Texas

Description: Urbanization causes various environmental issues including water pollution, air pollution, and solid waste. Urbanization of watersheds has a profound influence on the quality of stormwater runoff. The quality of stormwater runoff is highly associated with land use. This study analyzed the exceedance frequency of stormwater quality in five watersheds of Denton over eleven years and also analyzed the relationship between stormwater quality and land use/cover of each watershed. The results showed that the most of the water quality parameters that were examined in the Lower Pecan watershed exceeded their threshold most frequently. The higher frequency of exceedance in this watershed can be attributed to the wastewater treatment plant and landfill site. Total suspended solids and turbidity were frequently exceeded in Hickory and Clear Creek watersheds. Conductivity was found to have highest percentage of exceedance in Upper Pecan and Cooper watersheds. Thus, rural watersheds were related with higher exceedance of TSS and turbidity whereas urban watersheds were related with higher exceedance of conductivity.
Date: August 2015
Creator: Shrestha, Manjul
Partner: UNT Libraries

Influence of the Choice of Disease Mapping Method on Population Characteristics in Areas of High Disease Burdens

Description: Disease maps are powerful tools for depicting spatial variations in disease risk and its underlying drivers. However, producing effective disease maps requires careful consideration of the statistical and spatial properties of the disease data. In fact, the choice of mapping method influences the resulting spatial pattern of the disease, as well as the understanding of its underlying population characteristics. New developments in mapping methods and software in addition to continuing improvements in data quality and quantity are requiring map-makers to make a multitude of decisions before a map of disease burdens can be created. The impact of such decisions on a map, including the choice of appropriate mapping method, not been addressed adequately in the literature. This research demonstrates how choice of mapping method and associated parameters influence the spatial pattern of disease. We use four different disease-mapping methods – unsmoothed choropleth maps, smoothed choropleth maps produced using the headbanging method, smoothed kernel density maps, and smoothed choropleth maps produced using spatial empirical Bayes methods and 5-years of zip code level HIV incidence (2007- 2011) data from Dallas and Tarrant Counties, Texas. For each map, the leading population characteristics and their relative importance with regards to HIV incidence is identified using a regression analysis of a CDC recommended list of socioeconomic determinants of HIV. Our results show that the choice of mapping method leads to different conclusions regarding the associations between HIV disease burden and the underlying demographic and socioeconomic characteristics. Thus, the choice of mapping method influences the patterns of disease we see or fail to see. Accurate depiction of areas of high disease burden is important for developing and targeting appropriate public health interventions.
Date: December 2015
Creator: Desai, Khyati Sanket
Partner: UNT Libraries