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All-Inclusive List of Electronic Theses and Dissertations

Articles 1 - 17 of 17

Full-Text Articles in Geographic Information Sciences

Wavelet Analysis For Aboveground Biomass Estimate In Temperate Deciduous Forests, Xiaofang Wei Aug 2008

Wavelet Analysis For Aboveground Biomass Estimate In Temperate Deciduous Forests, Xiaofang Wei

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The ever-increasing concentration of anthropogenic greenhouse gases (C02, CH4, and CFCs) has been identified as a likely (greater than 90% confidence) cause of the observed increase of global mean temperatures since the mid-20th century (IPCC, 2007). The effect of human-induced climate change could be unprecedented and far-reaching. Carbon sequestration into trees and forests is an effective and inexpensive way for mitigating the C02 level in the atmosphere. Hence, accurate measurement of biomass will be of great importance to global carbon cycle and climate change. This study performed a wavelet-based forest aboveground biomass estimation approach in a temperate deciduous forest, the …

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Integration Of Remote Sensing And Census Data For Land-Use And Land Cover Classification And Population Estimation In Indianapolis, Indiana, Guiying Li May 2008

Integration Of Remote Sensing And Census Data For Land-Use And Land Cover Classification And Population Estimation In Indianapolis, Indiana, Guiying Li

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Increasing population and economic growth has resulted in rapid urban expansion in the past decades. Timely and accurately mapping urban land-use and land-cover (LULC) and associated population dist1ibution are often required for many applications such as urban management and planning, and environmental monitoring and assessment. Although many techniques have been developed, urban LULC classification is still a challenge based on remote sensing data. This research explored the integration of Landsat ETM+ image and census data for improving urban LULC classification accuracy, focusing on the distinction of different densities of residential use. The housing data were examined for use at three …

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Relationships Between Landscape Pattern And Land Surface Temperature And Their Applications To The Study Of West Nile Virus: As Case Studies In Cities Of Indianapolis And Chicago, United States, Hua Liu Aug 2007

Relationships Between Landscape Pattern And Land Surface Temperature And Their Applications To The Study Of West Nile Virus: As Case Studies In Cities Of Indianapolis And Chicago, United States, Hua Liu

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A new synthesis of remote sensing and landscape ecology approaches was developed to establish relationships between the landscape patterns and land surface temperatures (LST) in the city of Indianapolis, Indiana, United States. Land use and land cover (LULC) and LST images were derived from Terra Satellite's Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. An analytical procedure using landscape metrics was developed, applying configuration analysis oflandscape patterns and land surface temperature zones. Detailed landscape pattern analyses at the landscape and class scales were conducted using landscape metrics in the City of Indianapolis. The effects of spatial resolution on the …

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Modeling Of Culicidae Population Capacity Using Remote Sensing, Gis, And Fractal Geometry, Daniel Patrick Johnson May 2007

Modeling Of Culicidae Population Capacity Using Remote Sensing, Gis, And Fractal Geometry, Daniel Patrick Johnson

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A remote sensing and fractal geometric approach is proposed for the surveillance of mosquito population. The spread of vector-borne pathogens is becoming increasingly important with recent discussions of extensive human urbanization and global climate change. To date most studies dealing with mosquito transmitted disease surveyed by remote sensing and Geographic Information Systems have been conducted in tropical homogenous locales. This study approached the issue in a rapidly suburbanizing county in the Midwestern portion of the United States. Adult mosquitoes were trapped over a several year period and the landscape of the surrounding patches analyzed via remote sensing, fractal geometry, and …

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Biomass Estimation And Classification Of Secondary Succession Using Radar And Optical Remote Sensing Data Based On Textural And Spectral Analysis In Amazonia, Ping Jiang Dec 2006

Biomass Estimation And Classification Of Secondary Succession Using Radar And Optical Remote Sensing Data Based On Textural And Spectral Analysis In Amazonia, Ping Jiang

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Deforestation that happened during past decades in the Amazon Basin has been potentially affecting the global climate and carbon-cycle by contributing a vast amount of carbon into the atmosphere. Above-ground biomass (AGB) estimation of secondary successional and mature forests using remote sensing technology has been attracting scientists' attention. Optical sensor data are sensitive to forest canopies only, and therefore have limitations in AGB estimation, especially for tropical forests with complex structures and abundant species. Radar signals have the ability to penetrate canopies to detect the sub-layers of forests, and therefore potentially have a better performance in AGB estimation. Based on …

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People, Pixels, & Weights: Some Novel Applications Of Remote Sensing And Geographically Weighted Regression For Evansville, Indiana, Eric W. Lafary May 2006

People, Pixels, & Weights: Some Novel Applications Of Remote Sensing And Geographically Weighted Regression For Evansville, Indiana, Eric W. Lafary

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The exploration of urban-environmental changes and how those transformations co-vary with observed socio-economic realities is currently a major research initiative in geography. To that end, this thesis develops an urban-environmental assessment regime that examines how environmental change co-varies with observed socio-economic conditions. Research has demonstrated existing linkages between observed conditions in regard to socio-economic status (SES) and a particular greenness index, as represented by, normal difference vegetation index (NDVI). However, a gap within the literature has been identified concerning the current methodologies that propose to predict SES using remotely sensed data. Therefore, this thesis addresses this gap within the related …

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Biomass Estimation Using Statistical And Neural Network Analysis Of Aster Data, Vijay O. Lulla Dec 2005

Biomass Estimation Using Statistical And Neural Network Analysis Of Aster Data, Vijay O. Lulla

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This study assessed the performance of different biomass estimation methods using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) lll data in a temperate forest. Multiple linear regression statistics of spectral band data and derived indices with biomass values were compared with advanced neural network models created with spectral band data and indices to model biomass values. Biomass for the study area was estimated using both of these methods and the results were discussed. The data were analyzed using multivariate statistical analysis. Correlation analysis and regression analysis were employed to understand the relationship of biomass to the spectral data and …

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A Multi-Scale Analysis Of Census-Based Land Surface Temperature Variations And Determinants In Indianapolis, Indiana, Bingqing Liang May 2005

A Multi-Scale Analysis Of Census-Based Land Surface Temperature Variations And Determinants In Indianapolis, Indiana, Bingqing Liang

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Mapping urban temperatures are one of the major foci in urban climatology studies due to its close relationships with environmental, economic, and social issues. Most previous urban temperature studies were based on a single scale. This study utilized remote sensing and GIS data to perform a multiple scale analysis of urban temperatures. Land surface temperatures (LST) data derived from a Landsat Enhanced Thematic Mapper Plus (ETM+) image were used to examine census-based variations and to model their numerical relationships with urban morphology in Marion County, Indiana. Selected variables for the urban morphology include Normalized Difference Vegetation Index (NOVI), buildings, roads, …

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Classifying Mollisol Soils Using Hyperspectral Remote Sensing Data, Adil M. Wadia Aug 2004

Classifying Mollisol Soils Using Hyperspectral Remote Sensing Data, Adil M. Wadia

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Soil classification is a complex task that involves several factors. Soil classifications that have been published usually need to be updated as soil series definitions and boundaries change over time. Most existing soil classification surveys in the United States, although often very good, lack the required accuracy for selected applications such as precision agriculture. 111 Hyperspectral remote sensing data, with its 100+ bands and very high spectral resolution can help facilitate soil classification detail not achieved through traditional remote sensing methods. The study area selected for research was Wolf Field, near Homer, Champaign County, Illinois, which is a very agriculturally …

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Accuracy Of Neural Network Classifiers In Humid Tropical Areas, Genong Yu Aug 2004

Accuracy Of Neural Network Classifiers In Humid Tropical Areas, Genong Yu

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This research develops a better understanding of the use of neural networks in the context of tropical land cover characterization using multiple scale remotely sensed data. Results of the research contributed to developing a robust neural network classifier suitable to use for humid tropical land cover classification in areas such as Altamira, Brazil. Research was focused upon the following: (1) performance ofneural networks with different ancillary data- such as DEM (digital elevation model) and its derivatives; (2) effect of spatial scale on neural network classifiers using remote sensing data from IKONOS, Landsat TM, ASTER, and MODIS; (3) accuracy of neural …

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Identification Of Spatial And Temporal Patterns Of Secondary Succession Changes In Altamira, Brazil: Integrating Remote Sensing And Gis Technology, Hui Li Dec 2003

Identification Of Spatial And Temporal Patterns Of Secondary Succession Changes In Altamira, Brazil: Integrating Remote Sensing And Gis Technology, Hui Li

All-Inclusive List of Electronic Theses and Dissertations

There has been extensive use of remote sensing to study secondary succession of moist tropical forests in the Amazon Basin. However, scientists have not totally understood the dynamic processes of secondary succession of Amazon forests. A lack of consensus remains about what is the best approach for biomass estimation in the Amazon Basin using remotely sensed data. It is not clear which spectral wavelength bands have the best relationship with biomass values and what are the specific relationships between biomass and TM satellite radiance. The strategies in this research, based on analysis of detailed ground-based data and satellite TM image …

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Satellite Estimation Of Population And Housing Density In Marion County, Indiana, Guiying Li Dec 2003

Satellite Estimation Of Population And Housing Density In Marion County, Indiana, Guiying Li

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The world population and associated housing area have experienced a high growth rate in the past century and generated great pressure on Earth resources and environments. Accurate and timely population and housing estimates and distributions become important for many applications, such as regional design and development, policy-making, etc. This research reviewed four categories of methods to estimate population and housing using remotely sensed data in a previous study and explored the potentials of integration of Landsat ETM+ data with census data to estimate population and housing density in Marion County, Indiana. Spectral signatures, principal components, vegetation indices, fraction images, texture, …

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Identification Of Spatial And Temporal Patterns Of Secondary Succession Changes In Altamira, Brazil: Integrating Remote Sensing And Gis Technology, Hui Li Dec 2003

Identification Of Spatial And Temporal Patterns Of Secondary Succession Changes In Altamira, Brazil: Integrating Remote Sensing And Gis Technology, Hui Li

All-Inclusive List of Electronic Theses and Dissertations

There has been extensive use of remote sensing to study secondary succession of moist tropical forests in the Amazon Basin. However, scientists have not totally understood the dynamic processes of secondary succession of Amazon forests. A lack of consensus remains about what is the best approach for biomass estimation in the Amazon Basin using remotely sensed data. It is not clear which spectral wavelength bands have the best relationship with biomass values and what are the specific relationships between biomass and TM satellite radiance. The strategies in this research, based on analysis of detailed ground-based data and satellite TM image …

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Estimation Of Forest Stand Parameters And Application In Classification And Change Detection Of Forest Cover Types In The Brazilian Amazon Basin, Dengsheng Lu May 2001

Estimation Of Forest Stand Parameters And Application In Classification And Change Detection Of Forest Cover Types In The Brazilian Amazon Basin, Dengsheng Lu

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This research focuses on measurement of forest stand parameters using remote sensing which is applied to classification and change detection of tropical successional and mature forests in selected areas in the Brazilian Amazon Basin. Three study areas, Altamira, Bragantina, and Pedras, each with different biophysical environments, were selected for this research. Previous research has indicated that relationships between selected stand parameters and remotely sensed data are not clearly understood, especially in tropical areas. Rarely has remote sensing research been successfully conducted in quantitative estimation of forest stand parameters (e.g. biomass) and identification of vegetation growth stages. In this research, atmospherically …

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Gis-Based Decision Support For Drained Wetland Resoration In The Eel River Watershed Of N. E. Indiana, Xiangheng Yang Dec 2000

Gis-Based Decision Support For Drained Wetland Resoration In The Eel River Watershed Of N. E. Indiana, Xiangheng Yang

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The objective of this research is to develop cost-effect and accurate methods to identify optimal restorable drained wetland cropland sites. Landsat Thematic Mapper (TM) data analysis was used to identify the potential cropland candidate sites in the initial step. The result of digital TM data analysis shows that the overall classification accuracy in identifying classes of potential restoration candidate hydric soils is 86.7%. This accuracy shows that the TM data digital analysis is a cost-effective method for identifying poorly drained cropland hydric soils potentially suitable for wetland conversiOn. To support multi-factorial analysis in the final site screening, a Spatial Decision …

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Intelligent Visualization And Automated Processing For Large Scale Geographic Information Systems, Yu Jiang Dec 1999

Intelligent Visualization And Automated Processing For Large Scale Geographic Information Systems, Yu Jiang

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This research focuses on developing a new output system that compacts maps in multiple projections into a single Geographic Information System (GIS) without visual errors, through constructing a discrete GIS database that is managed by a Relational Data Base Management System (RDBMS). Unlike in a traditional large GIS database, the data are "physically discrete but logically continuous." In a new discrete GIS database, every map keeps its individuality without a relationship to any other map, and the relationships among the maps are centrally managed by a RDBMS. A study site was chosen at the boundary of the state of Indiana …

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Postfire Vegetation Change Detection Using Landsat Mss And Tm Data, Mark Edward Jakubauskas Aug 1988

Postfire Vegetation Change Detection Using Landsat Mss And Tm Data, Mark Edward Jakubauskas

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Three dates of Landsat digital data were classified and then analyzed using a geographic information system (GIS). The intent of this study was to determine if differences in burn severity relate to later vegetative cover within a northern pines forest. The May 5, 1980, Mack Lake Fire in the Huron National Forest, Michigan, was selected as the study site for this research. This wildfire burned over 9000 hectares of jack pine, red pine, and mixed deciduous forest within a six-hour period. Landsat MSS data from June 1973 and TM data from October 1982 were classified using an unsupervised approach to …

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