Spatial statistics : geospatial information modeling and thematic mapping / Mohammed A. Kalkhan

By:

Kalkhan, Mohammed A

Material type: Text

TextPublication details: Boca Raton, FL : CRC Press, 2011Description: xiv, 166 p., [2] p. of col. plates : ill., maps ; 24 cmISBN:

9781420069761
1420069764

Subject(s):

Contents:

1. Geospatial information technology -- 2. Data sampling methods and applications -- 3. Spatial pattern and correlation statistics -- 4. Geospatial analysis and modeling-mapping -- 5. R statistical package -- 6. Working with geospatial information data

Summary: 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

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Holdings ( 1 )
Title notes ( 3 )

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Open Shelf	UMPLIB GAMBANG	QA278.2 .K35 2011 (Browse shelf(Opens below))	1	Available		0000063633

Includes bibliographical references and index

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