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Overview

IDRISI Andes is an integrated GIS and Image Processing software solution providing over 250 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.

Tools for land planning, decision support, and risk analysis are included side-by-side with tools for spatial statistics, surface analysis, and spatial modeling. With IDRISI, all analytical features come standard—there is no need to buy costly add-ons to extend your research capabilities.

The Andes Edition, released in April 2006, is the 15th major release of the IDRISI software since 1987. IDRISI is used by researchers and professionals across industries in over 175 countries.

 

With IDRISI Andes, you can:

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

 
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The Land Change Modeler for Ecological Sustainability is organized around a set of tasks for land cover change assessment, change prediction, assessment of its impacts on habitat and biodiversity, and the exploration of planning interventions.   lcm_project
 
Process remotely-sensed imagery with a full suite of image processing techniques including innovative soft classifiers and neural network and decision tree analyses.
 
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IDRISI has incomparable classification tools. Machine learning classifiers consist of three neural network classifiers--multi-layer perceptron, self organizing map, and fuzzy art map.   neural_networks

 

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

 

 
Compare pairs of images or analyze trends and anomalies from long time series imagery.
 
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IDRISI provides the most extensive set of change and time series analysis tools in the industry. This screenshot illustrates Markov Chain Analysis, a technique for predictive change modeling. Predictions of future change are based on changes that have occurred in the past.   markov

 

 
Import/export with a wide variety of data sources, including all major vector and imagery formats.
 
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IDRISI supports the import of HDF-EOS 4 format which is useful for importing ASTER and MODIS data.   hdf

 

 
And even more…
 
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IDRISI provides full map composition capabilities, including multiple raster and vector layers, layer blending, interactive RGB compositing, multiple legends, title, text labels, grid, north arrow, scale bar, text and image insets. This image depicts the White Mountain region in New Hampshire, USA, including data for elevation, roads, and boundaries using various layer blending options.
 
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Visit the Modules Page for a full list of capabilities included in IDRISI.
 

 

 

reddog@geoafrica.co.za

 Ph: +27-(0)11-467-3371

Mobile: 082 89 2 9771

 26 Crestwood Drive, Lonehill