Projects / openModeller


openModeller is a C++ framework providing tools and an API for ecological niche modeling using a variety of algorithms. It can be used to predict species potential distribution based on a set of georeferenced occurrence points and a set of environmental layers.

Operating Systems

Recent releases

  •  02 Apr 2014 12:48

    Release Notes: This release contains a new "meta" algorithm which can use several algorithms behind the scenes to generate a consensus model. A new commandline tool (om_evaluate) can be used to return raw model values given a set of points and an environmental scenario. A new version of the Web service (OMWS 2.0) is also available, including new operations, one of them allowing whole experiments to be specified in a single request. A new raster driver now allows remote files to the fetched and used. There were also many changes in the framework itself.

    •  03 Oct 2011 18:53

      Release Notes: This release includes the new algorithm Random Forests and new versions of ENFA, Maxent, and Environmental Distance. There were also minor changes in the Web Service, the command line interface, and the framework itself.

      •  15 Feb 2010 18:09

        Release Notes: This release includes two new algorithms: ENFA (Ecological Niche Factor Analysis) and Niche Mosaic. A new version of the Maximum Entropy algorithm based on the Maxent paper (Phillips et al., 2006) has been added. It also contains a few adjustments in other existing algorithms (GARP, AquaMaps, ANN, CSM and Mahalanobis distance).

        •  22 May 2009 17:17

          Release Notes: This release includes adjustments in algorithms (ANN and SVM), commandline tools (om_model and om_niche), and the ROC curve procedure. There were also improvements in the modeling protocol and model statistics (including the possibility to use the lowest presence threshold).

          •  02 Feb 2009 22:20

            Release Notes: This release includes a new algorithm using Artificial Neural Networks, support for generating distribution maps in ARC/Info ASCII grid format, and changes in the ROC Curve class.


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