Clark Labs is releasing the 17th version of its IDRISI geospatial software for monitoring and modelling the Earth’s system. The IDRISI Selva software incorporates major revisions to its Land Change Modeler and Earth Trends Modeler applications. It also includes a variety of new analytical techniques, optimisations to current modules and additional import/export options.

IDRISI’s Land Change Modeler application for the modeling, prediction and impact assessment of land cover change now includes major modeling enhancements and special tools to support REDD (Reducing Emissions from Deforestation and Forest Degradation). These include accounting methodologies required for REDD projects, such as the estimation of baseline emissions from various carbon pools and the calculation of deferred emissions and carbon credits. A pioneering Land Cover Change modeling procedure, following the recently published SimWeight methodology, is now also included, as well as an integrated interface to the Maxent software for species distribution modeling.

IDRISI Selva introduces substantial enhancements to its revolutionary Earth Trends Modeler application for the analysis of patterns and trends in earth observation image time series. Particular emphasis has been given to the provision of new tools for the analysis of coupled systems (such as the oceans and atmosphere). These include Extended PCA/EOF, Multi-channel Singular Spectrum Analysis, Extended EOT, Multichannel EOT and Canonical Correlation Analysis.

IDRISI Selva delivers a variety of new display elements and enhancements for map compositions. Firstly, the new version eliminates the 32,000 row/column limitation on both the display and processing of images. IDRISI Selva additionally includes a new pyramid file structure for the rapid display of large image files, and a new automatic arrangement feature for the display of map compositions. With IDRISI Selva, vector field plots showing magnitude and direction, such as wind speed and direction, are now supported.

IDRISI has the largest support for image classifiers in the industry, and Selva continues its groundbreaking support of machine learning procedures, adding a Radial Basis Function classifier to its existing suite of MLP, SOM and Fuzzy Artmap neural networks.