Earth Observation Data Mining: A Use Case for Forest Monitoring

Abstract

The increased number of free and open satellite images has led to new applications of these data. Among them is the systematic classification of land cover/use types based on patterns of settlements or agriculture recorded by satellite imagers, in particular, the identification and quantification of temporal changes. In this paper, we will present guidelines and practical examples of how to obtain reliable image patch classification results based on data mining techniques for detecting possible changes that can appear within a data set. Here, we will focus on a scenario, namely forest monitoring using Earth observation Synthetic Aperture Radar data acquired by Sentinel-1, and multispectral data acquired by Sentinel-2.