The IDRISI Selva Service Update to v17.02 includes a fix to Land Change Modeler. In some cases during the change prediction phase using multiple stages and dynamic driver variables, the quantity of change may be incorrect. This issue has been resolved.<\/p>\n
Land Change Modeler<\/strong> Other enhancements to LCM include a revision of Maxent for species distribution modeling to include all Maxent parameters, improvements to the Harmonize facility, and various minor issues with LCM.<\/p>\n Earth Trends Modeler<\/strong> MLP<\/strong> SPLUS<\/strong> RECLASS<\/strong> Project<\/strong> Display<\/strong> RASTERVECTOR<\/strong> NETCDF<\/strong> ENVI Import<\/strong> Minor Revisions to Other Modules<\/strong> As always, the IDRISI documentation has been updated for the Help, Manual and the Tutorials.<\/p>\n","protected":false},"excerpt":{"rendered":" Summary The IDRISI Selva Service Update to v17.02 includes a fix to Land Change Modeler. In some cases during the change prediction phase using multiple stages and dynamic driver variables, the quantity of change may be incorrect. This issue has been resolved. Version 17.01 Update Details Land Change Modeler Perhaps the most substantial revision of […]<\/p>\n","protected":false},"author":7,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[1],"tags":[],"class_list":["post-1855","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"\n
\nPerhaps the most substantial revision of this release is to Land Change Modeler (LCM) and to the creation of the transition potential model using the multi-layer perceptron (MLP) neural network option. We have resolved the major issue of exposing the explanatory power of the independent variables and opening the black-box associated with this routine. The user now has feedback on both the general model and the independent variables. General model information now includes a skill measure to accompany the overall accuracy level of the model. The skill measure is based on the analysis of the validation data. The most significant addition is a sensitivity analysis of the independent variables used in the model. This analysis evaluates the quality of the independent variables and those that could be excluded from the model.<\/p>\n
\nThe Denoise preprocess tool in Earth Trends Modeler (ETM) has been revised to address instances of incorrect time series file creation. CEOT was revised to correct the ordering of the dependent and independent variables. Other minor issues were fixed with Aggregate, MSSA, Linear Modeling and with the saved Project file.<\/p>\n
\nThe same general model and independent variable reporting revisions to LCM have been implemented into the MLP classifier module, along with many other minor revisions.<\/p>\n
\nThe import and export to SPLUS format has been revised and streamlined.<\/p>\n
\nRECLASS has been revised to better support large positive and negative values along with many other improvements.<\/p>\n
\nThere is now support for RGB24 file format.<\/p>\n
\nMany revisions have been made to Composer and Layer Properties, and various display issues.<\/p>\n
\nMany minor errors have been resolved for all object types including calculations of the minimum and maximum values when converting to raster and the loss of significant digits in the Metadata.<\/p>\n
\nAn issue has been resolved with certain files needing to be transposed after import.<\/p>\n
\nBetter support for large files.<\/p>\n
\nCOMPOSITE, Database Workshop, ECWIDRISI, FLOW, GEOTIFF, HDFEOS, HISTO, ISOCLUST, KMLIDRISI, MCE, RADIANCE, REGRESS, SAMPLE, SHAPEIDR, SPOT, TOPRANK, XYZIDRISI.<\/p>\n