The IDRISI Taiga GIS and Image Processing software for the desktop provides a host of utilities and procedures to optimize, analyze and visualize your raster data and imagery. Extensive conversion tools allow for easy import and export with many of the most popular software and government formats.
IDRISI includes a range of tools for the analysis and manipulation of spatial data. With IDRISI, you can query and explore your raster data, derive new data layers, evaluate and measure spatial relationships, and identify patterns and trends.
IDRISI provides a complete suite of image processing tools, including the widest range of classification techniques in the industry, for both multispectral and hyperspectral remotely sensed imagery. All major imagery formats are accommodated.
IDRISI provides several environments for users to develop their own models. The software also includes specific modeling applications for land change analysis and image time series analysis.
Earth Trends Modeler provides an integrated environment for the analysis of time series data. Here an analysis of trends in sea surface temperature from 1982 to 2006 shows a strong increasing trend of temperature in the Atlantic and its relation to the Atlantic Multidecadal Oscillation (AMO). The triangular wavelet analysis diagram shows the nature and scale of these trends in the Labrador Sea. The animated globe shows variations in ocean height which are closely related with temperature variations.
Land Change Modeler provides a set of tools for the rapid assessment and mapping of change, allowing for one-click evaluations of land cover gains and losses, net change, and persistence, both in map and graphical form.
In Earth Trends Modeler, an analysis of trends in MODIS land surface temperature in degrees Celsius from 2000-2006. The map shows warming zones in North America, Eurasia, and Australia. Large cooling zones are depicted in Southern Europe and throughout Asia.
IDRISI allows on-screen digitizing of training sites and the development and analysis of signatures including signature comparison, measures of separability, and scattergrams.
Classification Tree Analysis is a type of machine learning classifier. Procedures are included for training and pruning a classification tree. This module produces both hard and soft classified maps. There is one soft map for each class associated with the degree of membership for that class at a particular leaf in the tree structure.
The IDRISI Macro Modeler provides a graphic environment for the construction of models. Facilities are included for batch processing of multiple images through the same model and for iterative processing with the output of one iteration becoming an input to the next.