Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Remote sensing
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Spatial Statistics - GeoSpatial Information Modeling and Thematic Mapping (Paperback)
Loot Price: R1,327
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Spatial Statistics - GeoSpatial Information Modeling and Thematic Mapping (Paperback)
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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: An overview of the geospatial information sciences and
technology and spatial statistics Sampling methods and
applications, including probability sampling and nonrandom
sampling, and issues to consider in sampling and plot design Fine
and coarse scale variability Spatial sampling schemes and spatial
pattern Linear and spatial correlation statistics, including
Moran's I, Geary's C, cross-correlation statistics, and inverse
distance weighting Geospatial statistics analysis using stepwise
regression, ordinary least squares (OLS), variogram, kriging,
spatial auto-regression, binary classification trees, cokriging,
and geospatial models for presence and absence data How to use R
statistical software to work on statistical analyses and case
studies, and to develop a geospatial statistical model
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