GRASS

1. GRASS Geographic Resources Analysis Support System

2. A general purpose, raster/vector Geographic Information System… • …combined with integrated image processing and data visualization subsystems. More specifically: • geospatial data management and analysis, • image processing, • graphics/maps production, • spatial modeling, and • visualization What is GRASS?

3. Originally developed by the U.S. Army Construction Engineering Research Laboratories between 1982-1995 Primarily for scientific research: academic, commercial, government (e.g. NASA, US National Park Service, U.S. Census Bureau, USGS etc.) Raster & vector processing, data in SQL database, version 6.0, runs on Unix, Windows, MAC About GRASS

4. Community-based development: • by US agencies (core components, module integration), universities, and private companies • by any user • Since 1997 worldwide network of developers Development of GRASS

5. GRASS GIS manager Graphical user interfaces Quantum GIS Raster, vector, database formats JAVA GRASS Server: spatial processing engine Client: Graphical User Interface Typically used in remote access/production environment

6. Disadvantages • Limited user friendliness • Need substantial computer/GIS experience to use Advantages • Extensive functionality, a leading GIS package • Large and influential user/development community • Freely available, open source

7. Vector operations

8. Raster operations

9. Raster operations Imagery import Geocoding of imagery data Visualizing (true) color composites Calculation of vegetation indices Calibration of thermal channel Image classification Image fusion Time series processing

11. i.ortho.photo Menu driver for the photo imagery programs. i.pca Principal components analysis (PCA) for image processing. i.photo.2image Interactively mark fiducial or reseau points on an image. i.photo.2target Creates control points on an image to be ortho-rectified. i.photo.camera Interactively select and modify the imagery group camera reference file. i.photo.init Interactively creates or modifies entries in a camera initial exposure station file for imagery group referenced by a sub-block. i.photo.rectify Orthorectifies an image by using the image to photo coordinate transformation matrix. i.points Mark ground control points on image to be rectified. i.rectify Rectifies an image by computing a coordinate transformation for each pixel in the image based on the control points. i.rgb.his Transforms raster maps from RGB (Red-Green-Blue) color space to HIS (Hue-Intensity-Saturation) color space. i.smap Performs contextual image classification using sequential maximum a posteriori (SMAP) estimation. i.spectral Displays spectral response at user specified locations in group or images. i.target Targets an imagery group to a GRASS location and mapset. i.tasscap Tasseled Cap (Kauth Thomas) transformation for LANDSAT-TM data i.topo.corr Computes topographic correction of reflectance. i.vpoints Set registration points for an imagery group from a vector map or keyboard entry. i.zc Zero-crossing "edge detection" raster function for image processing.

12. LIDAR Import • r.in.xyz - Create a raster map from an assemblage of many coordinates using univariate statistics. • r.in.lidar - (GRASS 7 only; GRASS must be compiled with libLAS support) Create a raster map from a binary LAS format LiDAR file (*.las) using univariate statistics and filtering. • v.in.ascii - Import data from an ASCII file to GRASS vector format. • v.in.lidar - (GRASS 7 only; GRASS must be compiled with libLAS support). Creates a vector points file from a binary LAS format LiDAR file (*.las or *.laz). r.in.lidar also can create a new location based on the LAS file, and can filter the input points by return and subregion.

13. LIDAR Analysis • v.outlier - Removes outliers from vector point data. • v.lidar.edgedetection - Uses interpolation and edge detection to create a new vector points file of LiDAR data so that the resulting attribute table is reclassified with CAT=1 for points associated with the ground surface (i.e., terrain) and useful for interpolating a raster terrain (DEM) map, CAT=2 for points pertaining to edges of human-contructed objects, and CAT=3 for other points that could pertain to vegetation or other features. • v.lidar.growing - Building contour determination and region growing algorithm for determining the building inside. • v.lidar.correction - Correction of the v.lidar.growing output. It is the last of the three algorithms for LIDAR filtering.

14. LIDAR Surface generation • v.surf.rst - Spatial approximation and topographic analysis using regularized spline with tension. • v.surf.idw - Surface interpolation from vector point data by Inverse Distance Squared Weighting. • v.surf.bspline - Surface interpolation from vector point data by bicubic or bilineal interpolation with Tykhonov regularization. • r.fillnulls - Fills no-data areas in raster maps using v.surf.rst splines interpolation. • r.surf.nnbathy - Natural Neighbor interpolation using the 'nn' addon.

15. NAME v.lidar.correction - Correction of the v.lidar.growing output. It is the last of the three algorithms for LIDAR filtering. KEYWORDS vector, LIDAR SYNOPSIS v.lidar.correctionv.lidar.correction helpv.lidar.correction [-e] input=nameoutput=nameterrain=name [sce=float] [scn=float] [lambda_c=float] [tch=float] [tcl=float] [--overwrite] [--verbose] [--quiet] Flags: -e Estimate point density and distance Estimate point density and distance for the input vector points within the current region extends and quit --overwrite Allow output files to overwrite existing files --verbose Verbose module output --quiet Quiet module output Parameters: input=name Input observation vector map name (v.lidar.growing output) output=name Output classified vector map name terrain=name Only 'terrain' points output vector map sce=float Interpolation spline step value in east direction Default: 25 scn=float Interpolation spline step value in north direction Default: 25 lambda_c=float Regularization weight in reclassification evaluation Default: 1 tch=float High threshold for object to terrain reclassification Default: 2 tcl=float Low threshold for terrain to object reclassification Default: 1

16. 3D visualization

17. Examples for use • Geography • Landscape ecology • Urban planning • Biology • Geophysics • Hydrology • Groundwater Flow Modeling • Vector network analysis • Geostatistics • Raster 3D Volume