Software, data and modelling news: imageRF - A user-oriented implementation for remote sensing image analysis with Random Forests

Authors:
Björn Waske;Sebastian van der Linden;Carsten Oldenburg;Benjamin Jakimow;Andreas Rabe;Patrick Hostert
Affiliations:
Institute of Geodesy and Geoinformation, Faculty of Agriculture, University of Bonn, Nussallee 15, 53115 Bonn, Germany;Geomatics Lab, Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany;Institute of Geodesy and Geoinformation, Faculty of Agriculture, University of Bonn, Nussallee 15, 53115 Bonn, Germany;Geomatics Lab, Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany;Geomatics Lab, Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany;Geomatics Lab, Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
Venue:
Environmental Modelling & Software
Year:
2012

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Abstract

An IDL implementation for the classification and regression analysis of remote sensing images with Random Forests is introduced. The tool, called imageRF, is platform and license independent and uses generic image file formats. It works well with default parameterization, yet all relevant parameters can be defined in intuitive GUIs. This makes it a user-friendly image processing tool, which is implemented as an add-on in the free EnMAP-Box and may be used in the commercial IDL/ENVI software.