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openModeller
openModeller
openModeller is a generic framework for carrying out fundamental niche modelling experiments - typically used to predict species distribution given a set of environmental raster layers.1
Description The openModeller project aims to provide a flexible, user friendly, cross-platform environment where the entire process of conducting a fundamental niche modelling experiment can be carried out. The software includes facilities for reading species occurrence and environmental data, selection of environmental layers on which the model should be based, creating a fundamental niche model and projecting the model into an environmental scenario. A number of fundamental niche modelling algorithms are provided as plug-ins, including GARP, Climate Space Model, Bioclimatic Envelopes, and others. Additional algorithms are planned for the future.2
openModeller Desktop Map Viewer3
openModellerDesktop is a cross platform, user friendly interface to the openModeller library. With openModellerDesktop you create an experiment consisting of one or more models. When you run the experiment, a model is computed to predict the distribution of each taxon you have selected. The model is then used to generate ('project') a probability distribution map. An embedded mapping component in openModellerDesktop allows you to visualise the probability distribution map, and shows the original occurrence points overlaid on to of the map.4
Models are generated by an algorithm that receives as input a set of occurrence points (latitude/longitude) and a set of environmental layer files. It's being written in C++ ANSI with platform independence in mind. It accepts different algorithms (now BIOCLIM and simple Cartesian distance algorithms, GARP, Climate Space Model, and in the near future GAM, GLM, Neural Nets, etc). It uses GDAL to read several map file formats and proj4 to convert between different georeferencing systems and projections.
A client-server architecture will be used as a first approach, enabling the existence of different client interfaces (desktop, command line and web-based). In the future some tasks could be performed in a distributed way5
The project is currently being developed by the Centro de Referência em Informação Ambiental (CRIA ), Escola Politécnica da USP (Poli ), and Instituto Nacional de Pesquisas Espaciais (INPE ) as an open-source initiative. It is funded by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), the Incofish project, and by individuals that have generously contributed their time. Previous collaborators include the BDWorld project, the University of Kansas Natural History Museum & Biodiversity Research Center (KU), and other individual participants. 6
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