Open Source GIS (eBook)

Foreword 6
Preface third edition 9
Acknowledgments 11
Contents 13
Open Source software and GIS 18
Open Source concept 18
GRASS as an Open Source GIS 20
The North Carolina sample data set 22
How to read this book 22
GIS concepts 24
General GIS principles 24
Geospatial data models 24
Organization of GIS data and system functionality 28
Map projections and coordinate systems 30
Map projection principles 30
Common coordinate systems and datums 33
Getting started with GRASS 37
First steps 37
Download and install GRASS 37
Database and command structure 39
Graphical User Interfaces for GRASS 6: QGIS and gis.m 42
Starting GRASS with the North Carolina data set 43
GRASS data display and 3D visualization 46
Project data management 50
Starting GRASS with a new project 53
Defining the coordinate system for a new project 56
Non-georeferenced xy coordinate system 60
Coordinate system transformations 60
Coordinate lists 61
Projection of raster and vector maps 63
Reprojecting with GDAL/OGR tools 64
GRASS data models and data exchange 68
Raster data 69
GRASS 2D and 3D raster data models 69
Managing regions, raster map resolution and boundaries 71
Import of georeferenced raster data 73
Import and geocoding of a scanned historical map 81
Raster data export 84
Vector data 85
GRASS vector data model 85
Import of vector data 88
Coordinate transformation for xy CAD drawings 93
Export of vector data 95
Working with raster data 98
Viewing and managing raster maps 98
Displaying raster data and assigning a color table 98
Managing metadata of raster maps 101
Raster map queries and profiles 103
Raster map statistics 105
Zooming and generating subsets from raster maps 106
Generating simple raster maps 107
Reclassification and rescaling of raster maps 109
Recoding of raster map types and value replacements 112
Assigning category labels 114
Masking and handling of no-data values 118
Raster map algebra 120
Integer and floating point data 122
Basic calculations 123
Working with ``if'' conditions 124
Handling of NULL values in r.mapcalc 125
Creating a MASK with r.mapcalc 126
Special graph operators 127
Neighborhood operations with relative coordinates 128
Raster data transformation and interpolation 130
Automated vectorization of discrete raster data 130
Generating isolines representing continuous fields 133
Resampling and interpolation of raster data 134
Overlaying and merging raster maps 139
Spatial analysis with raster data 141
Neighborhood analysis and cross-category statistics 141
Buffering of raster features 148
Cost surfaces 150
Terrain and watershed analysis 155
Landscape structure analysis 168
Landscape process modeling 170
Hydrologic and groundwater modeling 170
Erosion and deposition modeling 173
Final note on raster-based modeling and analysis 181
Working with voxel data 181
Working with vector data 184
Map viewing and metadata management 184
Displaying vector maps 184
Vector map metadata maintenance 187
Vector map attribute management and SQL support 188
SQL support in GRASS 6 189
Sample SQL queries and attribute modifications 196
Map reclassification 200
Vector map with multiple attribute tables: layers 201
Digitizing vector data 202
General principles for digitizing topological data 202
Interactive digitizing in GRASS 204
Vector map queries and statistics 207
Map queries 207
Raster map statistics based on vector objects 209
Point vector map statistics 211
Geometry operations 211
Topological operations 212
Buffering 218
Feature extraction and boundary dissolving 219
Patching vector maps 220
Intersecting and clipping vector maps 221
Transforming vector geometry and creating 3D vectors 224
Convex hull and triangulation from points 226
Find multiple points in same location 227
Length of common polygon boundaries 229
Vector network analysis 231
Network analysis 231
Linear reference system (LRS) 236
Vector data transformations to raster 242
Spatial interpolation and approximation 245
Selecting an interpolation method 245
Interpolation and approximation with RST 250
Tuning the RST parameters: tension and smoothing 252
Estimating RST accuracy 256
Segmented processing 259
Topographic analysis with RST 262
Working with lidar point cloud data 264
Volume based interpolation 272
Adding third variable: precipitation with elevation 273
Volume and volume-temporal interpolation 276
Geostatistics and splines 277
Graphical output and visualization 278
Two-dimensional display and animation 278
Advanced map display in the GRASS monitor 278
Creating a 2D shaded elevation map 281
Using display tools for analysis 282
Monitor output to PNG or PostScript files 284
Creating hardcopy maps with ps.map 286
Visualization in 3D space with NVIZ 288
Viewing surfaces, raster and vector maps 288
Querying data and analyzing multiple surfaces 294
Creating animations in 3D space 295
Visualizing volumes 298
Coupling with an external OpenGL viewer Paraview 299
Image processing 301
Remote sensing basics 301
Spectrum and remote sensing 301
Import of image channels 305
Managing channels and colors 306
The feature space and image groups 309
Data preprocessing 311
Radiometric preprocessing 311
Deriving a surface temperature map from thermal channel 314
Radiometric transformations and image enhancements 317
Image ratios 317
Principal Component Transformation 319
Geometric feature analysis with matrix filters 321
Image fusion 324
Introduction to RGB and IHS color model 324
Image fusion with the IHS transformation 325
Image fusion with Brovey transform 327
Thematic classification of satellite data 328
Unsupervised radiometric classification 330
Supervised radiometric classification 333
Supervised SMAP classification 336
Multitemporal analysis 337
Segmentation and pattern recognition 340
Notes on GRASS programming 344
GRASS programming environment 344
GRASS source code 345
Methods of GRASS programming 346
Level of integration 347
Script programming 348
Automated usage of GRASS 351
Local mode: GRASS as GIS data processor 351
Web based: PyWPS -- Python Web Processing Service 353
Notes on programming GRASS modules in C 354
Using GRASS with other Open Source tools 359
Geostatistics with GRASS and gstat 360
Spatial data analysis with GRASS and R 365
Reading GRASS data into R 367
Kriging in R 370
Using R in batch mode 375
GPS data handling 376
WebGIS applications with UMN/MapServer and OpenLayers 377
Appendix 379
Selected equations used in GRASS modules 379
Landscape process modeling 393
Definition of SQLite-ODBC connection 395
References 396
Index 404