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Open Source GIS A GRASS GIS Approach

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ISBN-10: 038735767X

ISBN-13: 9780387357676

Edition: 3rd 2008 (Revised)

Authors: Markus Neteler, Helena Mitasova

List price: $169.99
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Including material relating to GRASS6, this third edition contains sections covering database management working with attributes and SQL, reflecting the substantial extension of GRASS capabilities for managing attributes stored in various database systems.
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Book details

List price: $169.99
Edition: 3rd
Copyright year: 2008
Publisher: Springer
Publication date: 11/15/2007
Binding: Hardcover
Pages: 406
Size: 6.10" wide x 9.25" long x 0.49" tall
Weight: 3.762
Language: English

Open Source software and GIS
Open Source concept
GRASS as an Open Source GIS
The North Carolina sample data set
How to read this book
GIS concepts
General GIS principles
Geospatial data models
Organization of GIS data and system functionality
Map projections and coordinate systems
Map projection principles
Common coordinate systems and datums
Getting started with GRASS
First steps
Download and install GRASS
Database and command structure
Graphical User Interfaces for GRASS 6: QGIS and gis.m
Starting GRASS with the North Carolina data set
GRASS data display and 3D visualization
Project data management
Starting GRASS with a new project
Defining the coordinate system for a new project
Non-georeferenced xy coordinate system
Coordinate system transformations
Coordinate lists
Projection of raster and vector maps
Reprojecting with GDAL/OGR tools
GRASS data models and data exchange
Raster data
GRASS 2D and 3D raster data models
Managing regions, raster map resolution and boundaries
Import of georeferenced raster data
Import and geocoding of a scanned historical map
Raster data export
Vector data
GRASS vector data model
Import of vector data
Coordinate transformation for xy CAD drawings
Export of vector data
Working with raster data
Viewing and managing raster maps
Displaying raster data and assigning a color table
Managing metadata of raster maps
Raster map queries and profiles
Raster map statistics
Zooming and generating subsets from raster maps
Generating simple raster maps
Reclassification and rescaling of raster maps
Recoding of raster map types and value replacements
Assigning category labels
Masking and handling of no-data values
Raster map algebra
Integer and floating point data
Basic calculations
Working with "if" conditions
Handling of NULL values in r.mapcalc
Creating a MASK with r.mapcalc
Special graph operators
Neighborhood operations with relative coordinates
Raster data transformation and interpolation
Automated vectorization of discrete raster data
Generating isolines representing continuous fields
Resampling and interpolation of raster data
Overlaying and merging raster maps
Spatial analysis with raster data
Neighborhood analysis and cross-category statistics
Buffering of raster features
Cost surfaces
Terrain and watershed analysis
Landscape structure analysis
Landscape process modeling
Hydrologic and groundwater modeling
Erosion and deposition modeling
Final note on raster-based modeling and analysis
Working with voxel data
Working with vector data
Map viewing and metadata management
Displaying vector maps
Vector map metadata maintenance
Vector map attribute management and SQL support
SQL support in GRASS 6
Sample SQL queries and attribute modifications
Map reclassification
Vector map with multiple attribute tables: layers
Digitizing vector data
General principles for digitizing topological data
Interactive digitizing in GRASS
Vector map queries and statistics
Map queries
Raster map statistics based on vector objects
Point vector map statistics
Geometry operations
Topological operations
Feature extraction and boundary dissolving
Patching vector maps
Intersecting and clipping vector maps
Transforming vector geometry and creating 3D vectors
Convex hull and triangulation from points
Find multiple points in same location
Length of common polygon boundaries
Vector network analysis
Network analysis
Linear reference system (LRS)
Vector data transformations to raster
Spatial interpolation and approximation
Selecting an interpolation method
Interpolation and approximation with RST
Tuning the RST parameters: tension and smoothing
Estimating RST accuracy
Segmented processing
Topographic analysis with RST
Working with lidar point cloud data
Volume based interpolation
Adding third variable: precipitation with elevation
Volume and volume-temporal interpolation
Geostatistics and splines
Graphical output and visualization
Two-dimensional display and animation
Advanced map display in the GRASS monitor
Creating a 2D shaded elevation map
Using display tools for analysis
Monitor output to PNG or PostScript files
Creating hardcopy maps with
Visualization in 3D space with NVIZ
Viewing surfaces, raster and vector maps
Querying data and analyzing multiple surfaces
Creating animations in 3D space
Visualizing volumes
Coupling with an external OpenGL viewer Paraview
Image processing
Remote sensing basics
Spectrum and remote sensing
Import of image channels
Managing channels and colors
The feature space and image groups
Data preprocessing
Radiometric preprocessing
Deriving a surface temperature map from thermal channel
Radiometric transformations and image enhancements
Image ratios
Principal Component Transformation
Geometric feature analysis with matrix filters
Image fusion
Introduction to RGB and IHS color model
Image fusion with the IHS transformation
Image fusion with Brovey transform
Thematic classification of satellite data
Unsupervised radiometric classification
Supervised radiometric classification
Supervised SMAP classification
Multitemporal analysis
Segmentation and pattern recognition
Notes on GRASS programming
GRASS programming environment
GRASS source code
Methods of GRASS programming
Level of integration
Script programming
Automated usage of GRASS
Local mode: GRASS as GIS data processor
Web based: PyWPS - Python Web Processing Service
Notes on programming GRASS modules in C
Using GRASS with other Open Source tools
Geostatistics with GRASS and gstat
Spatial data analysis with GRASS and R
Reading GRASS data into R
Kriging in R
Using R in batch mode
GPS data handling
WebGIS applications with UMN/MapServer and OpenLayers
Selected equations used in GRASS modules
Landscape process modeling
Definition of SQLite-ODBC connection