imageRF – A user-oriented implementation for remote sensing image analysis with Random Forests

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.

Publication
Environmental Modelling & Software
Benjamin Jakimow
Benjamin Jakimow
Geodata & Software

2022 - Doctoral Thesis at Humboldt-Universität zu Berlin

Patrick Hostert
Patrick Hostert
Principal Investigator