Pushpita's Tool Review
GRASS GIS(Geographic Resource Analysis Support System)
GRASS GIS is free and open source Geographic Information System(GIS) software used for geospatial data management and analysis, image processing, graphics and maps production, spatial modeling, and visualization. GRASS is currently used in academic and commercial settings around the world, as well as by many governmental agencies and environmental consulting companies. It is a founding member of Open Source Geospatial Foundation (OSGeo). The Open Source Geospatial Foundation (OSGeo) is a not-for-profit organization whose mission is to foster global adoption of open geospatial technology by being an inclusive software foundation devoted to an open philosophy and participatory community driven development. It is released under GNU General Public License (GPL) >= V2. Originally developed by the U.S. Army Construction Engineering Research Laboratories (USA-CERL, 1982-1995), a branch of the US Army Corp of Engineers, as a tool for land management and environmental planning by the military, GRASS GIS has evolved into a powerful utility with a wide range of applications in many different areas of applications and scientific research. GRASS is currently used in academic and commercial settings around the world, as well as many governmental agencies including NASA, NOAA, USDA, DLR, CSIRO, the National Park Service, the U.S. Census Bureau, USGS, and many environmental consulting companies.
GRASS GIS contains over 350 modules to render maps and images on monitor and paper; manipulate raster, and vector data including vector networks; process multispectral image data; and create, manage, and store spatial data. GRASS GIS offers both an intuitive graphical user interface as well as command line syntax for ease of operations. GRASS GIS can interface with printers, plotters, digitizers, and databases to develop new data as well as manage existing data.
GRASS GIS capabilities:
Raster analysis: Automatic raster line and area to vector conversion, Buffering of line structures, Cell and profile data query, Color table modifications, Conversion to vector and point data format, Correlation / covariance analysis, Expert system analysis , Map algebra (map calculator), Interpolation for missing values, Neighborhood matrix analysis, Raster overlay with or without weight, Reclassification of cell labels, Resampling (resolution), Rescaling of cell values, Statistical cell analysis, Surface generation from vector lines.
3D-Raster (voxel) analysis: 3D data import and export, 3D masks, 3D map algebra, 3D interpolation (IDW, Regularized Splines with Tension), 3D Visualization (iso-surfaces), Interface to Para-view and POV ray visualization tools.
Vector analysis: Contour generation from raster surfaces (IDW, Splines algorithm), Conversion to raster and point data format, Digitizing (scanned raster image) with mouse, Reclassification of vector labels, Super positioning of vector layers.
Point data analysis: Delaunay triangulation, Surface interpolation from spot heights, Thiessen polygons, Topographic analysis (curvature, slope, aspect), LiDAR
Image processing: Support for aerial and UAV images, satellite data (optical, radar, thermal), Canonical component analysis (CCA), Color composite generation, Edge detection, Frequency filtering (Fourier, convolution matrices), Fourier and inverse Fourier transformation, Histogram stretching, IHS transformation to RGB, Image rectification (affine and polynomial transformations on raster and vector targets), Ortho photo rectification, Principal component analysis (PCA), Radiometric corrections (Fourier), Resampling, Resolution enhancement (with RGB/IHS), RGB to IHS transformation, Texture oriented classification (sequential maximum a posteriori classification), Shape detection, Supervised classification (training areas, maximum likelihood classification), Unsupervised classification (minimum distance clustering, maximum likelihood classification)
DTM-Analysis: can analyze Contour generation, Cost / path analysis, Slope / aspect analysis, Surface generation from spot heights or contours.
Geocoding: Geocoding of raster and vector maps including (LiDAR) point clouds.
Visualization: 3D surfaces with 3D query (NVIZ), Color assignments, Histogram presentation, Map overlay, Point data maps, Raster maps, Vector maps, Zoom / unzoom –function.
Map creation: Image maps, Postscript maps, HTML maps.
SQL-support: Database interfaces (DBF, SQLite, PostgreSQL, mySQL, ODBC).
Geo-statistics: Interface to "R" (a statistical analysis environment), Matlab etc.
Temporal framework: support for time series analysis to manage, process and analyze (big) spatio-temporal environmental data. It supports querying, map calculation, aggregation, statistics and gap filling for raster, vector and raster3D data. A temporal topology builder is available to build spatio-temporal topology connections between map objects for 1D, 3D and 4D extents. Besides that, Erosion modeling, Landscape structure analysis, Solution transport, Watershed analysis also can be done through GRASS GIS. More over, it can be use in analyzing urban spaces, building interior through geo-spatial modeling and visualizing. Different version of GIS has been already used in the complex data analysis in the field of urban and regional development. in the historical research, these tool proved to help in reconstructing the previous historical environment by adding the known values of the historic time. Though this tool has been more extensively used in the environmental research till now, there is a huge opportunity to use it in the field of historical researches related to place, space and time. It can be a useful source of data analyzing in the field of archaeology for data exchange, visualization and 3D modeling. As, GRASS is used for highly technical purposes and mathematical analyses, it can be very helpful to prove the debates over historical spaces that includes urban or any kind of natural settlement. it can help to unveil all those data which probably the traditional methods of humanities can not. Therefore, I believe, GRASS GIS can prove to be a useful tool to digital humanities, which can help the humanities to connect with the scientific part of the history.