Information, not money or ammunition, is now the holy grail of business organisations and governments across the world. Computer programming and computer graphics, apart from enabling us to visualise data, have made sophisticated data analysis possible, which allows one to understand the nuances in large data sets. Geographical data, being bulky and complex, is a good example of how valuable the sifting of large volumes of information can be. Statistical information pertaining to different aspects of a well-defined geographical region, allowed to vary with various geographical parameters such as latitude, longitude, altitude, population, jurisdictions and other variables, is termed ‘geospatial data’.
Cartographers try to visualise a wide spectrum of this geospatial information in a variety of maps, which is basically to employ visualisation technique. The innovation of digital maps has enabled more comprehensive analysis, manipulation and prediction of statistics based on the data collected. Different mechanisms used to seek, sort and visualise geospatial data are grouped as Geographic Information Systems (GIS). There is a whole gamut of software programmes that can incorporate GIS functionality.
What are GIS tools?
Although GIS tools might appear to be the work of geeks, most computer users have come across these tools in one form or another. These range from simple desktop globes to the entertainingly useful Google Earth.
GIS tools are primarily data interpretation and visualisation software programmes, allowing users to view, manipulate, process and obtain results of the geospatial data.
Geospatial data acquisition today has multiple sources: remote sensing satellites, and data from various national and international censuses. Research-driven data acquisition yields an exhaustive amount of information in various formats, which can be converted into computer databases such as PostgreSQL, SQLite and Oracle for the GIS tools to operate on.
Backed by data tables in databases, GIS tools run programmes that sort entries in the databases as required by users, and use graphic engines to display the geospatial information in 2D and 3D graphics. Intuitive to use, most of these tools allow extensive customisation and feature enhancement in terms of the types of data to be mapped, parameter tweaking and formats of visualisation. Some of the tools allow exporting the plot into XML (Extensible Markup Language) format for further processing by Web-based engines.
Free and Open Source
GIS tools are widely used for research purposes and, like many research initiatives, are backed by the community. There is a whole set of Free and Open Source GIS tools to choose from, over the proprietary ones.
Quantum GIS and GRASS (Geographic Resources Analysis Support System) are the most widely used Free and Open Source GIS tools. These tools have complementing feature sets and are compatible with each other. Both the tools allow users to add plugins written in all major scripting languages such as C, C++ and Python. Proprietary tools such as Map 3D from Autodesk of AutoCad fame are also used in some cases.
GIS tools handle a rich variety of datasets and have options for reading and analysing new data and allow users to render their results in various graphic formats such as raster images, vector graphics or even flash-based animation.
Bharat Anangur, a research student, and his team from the Indian Institute of Science, Bangalore, use GIS tools to study the change of topography in Bangalore due to depleting water bodies and tree cover, and its impact on the weather pattern. “Through two years, we have assimilated data in terms of the increase in constructed area in Bangalore, depleting water reserves and statistics on the number of trees. As expected, regions that have retained or increased green cover and water bodies are cooler; using GIS tools for data representation purposes is highly useful,” he says.