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By: (Author) Mohammed A. Kalkhan
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Geospatial information modeling and mapping have become important tools for the investigation and management of natural resources at the landscape scale. This book reviews the types and applications of geospatial information data, such as remote sensing, GIS, and GPS, as well as their integration into landscape-scale geospatial statistical models and maps. Readers will learn the requirements and limitations of each geospatial tool. Along with case studies and statistical data analysis methods, the text includes laboratory exercises using ArcInfo, ArcGIS, ArcView, ERDAS-IMAGINE, and other popular software for geospatial modeling.
Geospatial information modeling and mapping has become an important tool for the investigation and management of natural resources at the landscape scale. Spatial Statistics: GeoSpatial Information Modeling and Thematic Mapping reviews the types and applications of geospatial information data, such as remote sensing, geographic information systems (GIS), and GPS as well as their integration into landscape-scale geospatial statistical models and maps.
The book explores how to extract information from remotely sensed imagery, GIS, and GPS, and how to combine this with field data—vegetation, soil, and environmental—to produce a spatial model that can be reconstructed and displayed using GIS software. Readers learn the requirements and limitations of each geospatial modeling and mapping tool. Case studies with real-life examples illustrate important applications of the models.
Topics covered in this book include:
The book includes practical examples and laboratory exercises using ArcInfo, ArcView, ArcGIS, and other popular software for geospatial modeling. It is accessible to readers from various fields, without requiring advanced knowledge of geospatial information sciences or quantitative methods.
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