Land Cover Classification and Monitoring: the STEM Open Source Solution

Abstract Agricultural and forest monitoring is a valued instrument needed by public authorities (PA) for determining land uses, planning natural resources management and collecting taxes. Remote Sensing (RS) can provide accurate information over large areas and it has been already widely used for these tasks. Orthophotos and LiDAR data are regularly acquired to monitor land cover changes in many countries. However, the data processing is usually done through photointerpretation and PA are lacking an automated software for this task. The STEM project aimed at the development of an open source software to process RS data for agricultural and forests monitoring. The developed plug-in can be used by inexperienced users to monitor large land covers. In the paper the main software functionalities are described, with particular emphasis on the most innovative modules and algorithms. Some results obtained by these modules are shown as well to demonstrate the efficiency and reliability of the plug-in.

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