Tools

Geospatial Data Abstraction Library/OGR Simple Feature Library (GDAL/OGR)

GDAL is a translator library for raster and vector data formats under and X/MIT style Open Source license by the Open Source Geospatial Foundation. GDAL utilizes abstract data models for raster and vector data, which allow GDAL to translate between such a variety of formats. The GDAL library also provides a variety of command-line utilities for raster and vector manipulation. A few of the utilities are:

• gdalinfo - Provides a variety of information about a supported raster dataset
• gdal_translate - Translates raster data between different formats
• gdalwarp - Reprojection and manipulates rasters datasets
• gdaldem - Methods for analyzing and visualizing Digital Elevation Models (e.g. slope, hillshade, aspect,color-relief)
• gdal_polygonize - Converts a raster dataset into a polygonal vector dataset
• gdal2tiles - Creates a directory with Tile Mapping Service(TMS) tiles, KMLs and simple web viewers
• ogrinfo - Provides a variety of information about a supported vector dataset
• ogr2ogr - Translates a vector dataset between different formats
• ogrlineref - Create or query a linear referenced file from input data

The R Project for Statistical Computing

R is a programming language descended from the S statistical language. R has a strong presence in the statistical/data science fields due to ease of use and speedy prototyping. Since R treats all values as vectors, it has a natural strengths with manipulating tabular data. With thanks to Roger Bivand, R has grown strong spatial capabilities. The book Applied Spatial Data in R provides a good background on the different libraries, data formats and functions available in R, but R is continually growing so it is good to check the Comprehensive R Archive Network (CRAN) for additional libraries.

Some useful spatial libraries in R include:

• sp - Classes and methods for spatial data
• rgdal - Bindings for the Geospatial Data Abstraction Library
• raster - Geographic data analysis and modeling
• spdep - Spatial Dependence: Weighting schemes, statistics, and models
• maptools - Tools for Reading and handling spatial objects
• rgeos - Interface to Geometry Engine - Open Source (GEOS)

There are several other libraries(GEOS,Grass GIS), languages(Bash,Python, C++) useful for manipulating spatial datasets, which are outside our current scope. We can cover these at a later time.

GRASS GIS

The Geographic Resources Analysis Support System(GRASS GIS) is a Geographic Information System used for data management, image processing, graphics production, spatial modeling and visualization of many types of data.

GRASS GIS was originally developed by the U.S. Army Construction Engineering Research Laboratories, a branch of the US Army Corp of Engineers. It was originally developed as a tool for land management and environmental planning by the military. GRASS GIS is currently used in academic and commercial settings around the world, as well as many governmental agencies.