1 Open Source software and GIS 1
1.1 Open Source concept 1
1.2 GRASS as an Open Source GIS 3
1.3 The North Carolina sample data set 5
1.4 How to read this book 5
2 GIS concepts 7
2.1 General GIS principles 7
2.1.1 Geospatial data models 7
2.1.2 Organization of GIS data and system functionality 11
2.2 Map projections and coordinate systems 13
2.2.1 Map projection principles 13
2.2.2 Common coordinate systems and datums 16
3 Getting started with GRASS 21
3.1 First Steps 21
3.1.1 Download and install GRASS 21
3.1.2 Database and command structure 23
3.1.3 Graphical User Interfaces for GRASS 6: QGIS and gis.m 26
3.1.4 Starting GRASS with the North Carolina data set 27
3.1.5 GRASS data display and 3D visualization 30
3.1.6 Project data management 34
3.2 Starting GRASS with a new project 37
3.2.1 Defining the coordinate system for a new project 40
3.2.2 Non-georeferenced xy coordinate system 44
3.3 Coordinate system transformations 44
3.3.1 Coordinate lists 45
3.3.2 Projection of raster and vector maps 47
3.3.3 Reprojecting with GDAL/OGR tools 48
4 GRASS data models and data exchange 53
4.1 Raster data 54
4.1.1 GRASS 2D and 3D raster data models 54
4.1.2 Managing regions, raster map resolution and boundaries 56
4.1.3 Import of georeferenced raster data 58
4.1.4 Import and geocoding of a scanned historical map 66
4.1.5 Raster data export 69
4.2 Vector data 70
4.2.1 GRASS vector data model 70
4.2.2 Import of vector data 73
4.2.3 Coordinate transformation for xy CAD drawings 78
4.2.4 Export of vector data 80
5 Working with raster data 83
5.1 Viewing and managing raster maps 83
5.1.1 Displaying raster data and assigning a color table 83
5.1.2 Managing metadata of raster maps 86
5.1.3 Raster map queries and profiles 88
5.1.4 Raster map statistics 90
5.1.5 Zooming and generating subsets from raster maps 91
5.1.6 Generating simple raster maps 92
5.1. 7 Reclassification and rescaling of raster maps 94
5.1.8 Recoding of raster map types and value replacements 97
5.1.9 Assigning category labels 99
5.1.10 Masking and handling of no-data values 103
5.2 Raster map algebra 105
5.2.1 Integer and floating point data 107
5.2.2 Basic calculations 108
5.2.3 Working with "if" conditions 109
5.2.4 Handling of NULL values 110
5.2,5 Creating a MASK with 111
5.2.6 Special graph operators 112
5.2.7 Neighborhood operations with relative coordinates 113
5.3 Raster data transformation and interpolation 115
5.3 .1 Automated vectorization of discrete raster data 115
5.3.2 Generating isolines representing continuous fields 118
5.3.3 Resampling and interpolation of raster data 119
' 5.3.4 Overlaying and merging raster maps 124
5.4 Spatial analysis with raster data 126
5.4.1 Neighborhood analysis and cross-category statistics 126
5.4.2 Buffering of raster features 133
5.4.3 Cost surfaces 135
5.4.4 Terrain and watershed analysis 140
5.4.5 Landscape structure analysis 153
5.5 Landscape process modeling 155
5.5.1 Hydrologic and groundwater modeling 155
5.5.2 Erosion and deposition modeling 158
5.5.3 Final note on raster-based modeling and analysis 166
5.6 Working with voxel data 166
Working with vector data 169
6.1 Map viewing and metadata management 169
6.1.1 Displaying vector maps 169
6.1.2 Vector map metadata maintenance 172
6.2 Vector map attribute management and SQL support 173
6.2.1 SQL support in GRASS 6 174
6.2.2 Sample SQL queries and attribute modifications 181
6.2.3 Map reclassification 185
6.2.4 Vector map with multiple attribute tables: layers 186
6.3 Digitizing vector data 187
6.3.1 General principles for digitizing topological data 187
6.3.2 Interactive digitizing in GRASS 189
6.4 Vector map queries and statistics 192
6.4.1 Map queries . 192
6.4.2 Raster map statistics based on vector objects 194
6.4.3 Point vector map statistics 196
6.5 Geometry operations 196
6.5.1 Topological operatio 197
6.5.2 Buffering 203
6.5.3 Feature extraction and boundary dissolving 204
6.5.4 Patching vector maps 205
6.5.5 Intersecting and clipping vector maps 206
6.5.6 Transforming vector geometry and creating 3D vectors 209
6.5.7 Convex hull and triangulation from points 211
6.5.8 Find multiple points in same location 212
6.5.9 Length of common polygon boundaries 214
6.6 Vector network analysis 216
6.6.1 Network analysis 216
6.6.2 Linear reference system (LRS) 221
6.7 Vector data transformations to raster 227
6.8 Spatial interpolation and approximation 230
6.8.1 Selecting an interpolation method 230
6.8.2 Interpolation and approximation with RST 235
6.8.3 Tuning the RST parameters: tension and smoothing 237
6.8.4 Estimating RST accuracy 241
6.8.5 Segmented processing 244
6.8.6 Topographic analysis with RST 247
6.9 Working with lidar point cloud data 249
6.10 Volume based interpolation 257
6.10.1 Adding third variable: precipitation with elevation 258
6.10.2 Volume and volume-temporal interpolation 261
6.10.3 Geostatistics and splines 262
7 Graphical output and visualization 263
7.1 Two-dimensional display and animation 263
7.1.1 Advanced map display in the GRASS monitor 263
7.1.2 Creating a 2D shaded elevation map 266
7.1.3 Using display tools for analysis 267
7 .1.4 Monitor output to PNG or PostScript files 269
7.2 Creating hardcopy maps with ps.map 271
7.3 Visualization in 3D space with NVIZ 273
7.3.1 Viewing surfaces, raster and vector maps 273
7.3.2 Querying data and analyzing multiple surfaces 279
7.3.3 Creating animations in 3D space 280
7.3.4 Visualizing volumes 283
7 .4 Coupling with an external OpenGL viewer Paraview 284
8 Image processing 287
8.1 Remote sensing basics 287
8.1.1 Spectrum and remote sensing 287
8.1.2 Import of image channels 291
8.1.3 Managing channels and colors 292
8.1.4 The feature space and image groups 295
8.2 Data preprocessing 297
8.2.1 Radiometric preprocessing 297
8.2.2 Deriving a surface temperature map from thermal channel 300
8.3 Radiometric transformations and image enhancements Image ratios 303
8.3.2 Principal Component Transformation 305
8.4 Geometric feature analysis with matrix filters 307
8.5 Image fusion 310
8.5.1 Introduction to RGB and IRS color model 310
8.5.2 Image fusion with the IRS transformation 311
'8.5 .3 Image fusion with Brovey transform 313
8.6 Thematic classification of satellite data 314
8.6.1 Unsupervised radiometric classification 316
8.6.2 Supervised radiometric classification 319
8.6.3 Supervised SMAP classification 322
8.7 Multitemporal analysis 323
8.8 Segmentation and pattern recognition 326
9 Notes on GRASS programming 331
9.1 GRASS programming environment 331
9.1.1 GRASS source code 332
9.1.2 Methods of GRASS programming 333
9.1.3 Level of integration 334
9.2 Script programming 335
9.3 Automated usage of GRASS 338
9.3.1 Local mode: GRASS as GIS data processor 338
9.3.2 Web based: PyWPS - Python Web Processing Service 340
9.4 Notes on programming GRASS modules in C 341
10 Using GRASS with other Open Source tools 347
10.1 Geostatistics with GRASS and gstat 348
10.2 Spatial data analysis with GRASS and R 353
10.2.1 Reading GRASS data into R 355
10.2.2 Kriging in R 358
10.2.3 Using R in batch mode 363
10.3 GPS data handling 364
10.4 WebGIS applications with UMN/MapServer and OpenLayers 365
A Appendix 367
A.l Selected equations used in GRASS modules 367
A.2 Landscape process modeling 381
A.3 Definition of SQLite-ODBC connection 383
References 385
Index 393