IDRISI Taiga GIS and Image Processing Software

IDRISI Taiga is an integrated GIS and Image Processing software solution providing nearly 300 modules for the analysis and display of digital spatial information. IDRISI offers the most extensive set of GIS and Image Processing tools in the industry in a single, affordable package. With IDRISI, all analytical features come standard—there is no need to buy costly add-ons to extend your research capabilities.

IDRISI Taiga provides:

  • a complete GIS analysis package for basic and advanced spatial analysis, including tools for surface and statistical analysis, decision support, and change and time series analysis;
  • a complete Image Processing system with the most extensive hard and soft classifers in the industry, including machine learning classifiers such as neural networks and classification tree analysis, as well as image segmentation for classification;
  • integrated modeling environments including the Earth Trends Modeler for image time series of environmental trends and Land Change Modeler for land change analysis and prediction, a critical component for REDD projects;
  • complete utilities for import and export along with a comprehensive set of documentation and tutorials.

Learn more about IDRISI Taiga

IDRISI Taiga Brochure (PDF)
IDRISI Taiga Technical Specifications (PDF)
What's New in IDRISI Taiga (PDF)


With IDRISI Taiga, you can:

 

Analyze trends and anomalies of image time series with the innovative Earth Trends Modeler facility.
 

 

 
Image Time Series Analysis with Earth Trends Modeler in IDRISI Taiga

The Earth Trends Modeler is a vertical application included with IDRISI Taiga and specially designed for the analysis of image time series. It includes a coordinated suite of data mining tools for the extraction of trends and the underlying determinants of variability.

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Process remotely-sensed imagery with a full suite of image processing techniques including innovative soft classifiers, neural network and decision tree analyses, and a segment-based classifier.


 
Segmentation Analysis and Classification with IDRISI Taiga

The module SEGCLASS classifies the imagery using a majority rule algorithm to assign each segment to the majority class frorm the reference image. SEGCLASS can improve the accuracy of a pixel-based classification and produce a smoother map-like classification result while preserving the boundaries between the segments.
 

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Utilize cutting-edge decision support and uncertainty management tools to allocate resources and create suitability maps.


 
Decision Support Flood Modeling with IDRISI Taiga

This screenshot illustrates some of the data products developed for a study on the effects of sea level rise on a coastal rice-producing area in Vietnam. Part of the study included prediction of future sea level and inundated areas. This portion of the study explicitly incorporated uncertainty in the elevation data as well as the projected sea level rise. The probability of inundation image (upper left) was then thresholded based upon an acceptable level of risk. The multi-criteria analysis was a prediction model of where people might relocate after inundation, thus a predicted landcover image was produced.
 

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Explore, predict and model impacts on land cover change with the innovative Land Change Modeler application.


 
Biodiversity Analysis with IDRISI Taiga and Land Change Modeler

The Land Change Modeler's Biodiversity Analysis panel provides the capability of mapping five different measures of biodiversity: alpha, gamma and beta diversity (Whittaker’s), Sorensen’s Dissimilarity Index and an index of relative range restriction.

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Import/export with a wide variety of data sources, including all major vector and imagery formats.


 
Extensive Import and Export Utilities in IDRISI Taiga

IDRISI supports the import of HDF-EOS 4 format which is useful for importing ASTER and MODIS data.

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And even more…


 
Watershed Analysis and Modeling with IDRISI Taiga

IDRISI also allows you to delineate watersheds and viewsheds (areas visible from one or more designated sites on a surface), determine surface runoff and flow patterns, evaluate sedimentation and model soil erosion.

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