Two Master theses detect illegal landuse using satellite imagery


Our two Erasmus students Thomas and Augustine successfully completed their Master theses on illegal land use using satellite imagery. Both of their projects were a collaboration between the University of Münster, NOVA Information Management School, Lisboa, Portugal and the Universitat Jaume I, Castellón, Spain. Thomas’ thesis with the title “Spatiotemporal Deep Learning for detecting illegal deforestation using Sentinel 1 and 2 Imagery and context-aware modelling” demonstrates the importance of satellite imagery and deep learning approaches in detecting illegal deforestation and assessing the legality of forest harvest activities. Augstines’ thesis “Detection of Artisanal Small-Scale Mining (ASM) Using Segmentation-Based Deep Learning and Sentinel 2 Imagery in Madre de Dios, Peru” reveals that deep learning in combination with satellite imagery can help with the detection of Artisanal and Small-Scale Mining.
Congrats, Thomas and Augustine!












































































