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Can we achieve through Earth Observation and Machine Learning a global and systematic observation of world’s forests and accurately measure deforestation?

Francescopaolo Sica


Francescopaolo Sica received the Laurea (M.S.) degree (summa cum laude) in telecommunication engineering and the Ph.D. degree in information engineering from the University of Naples Federico II, Naples, Italy, in 2012 and 2016. He is currently a Researcher at the Microwaves and Radar Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany.

From November 2014 until February 2016, he has been a Visiting Student at the DLR Remote Sensing Technology Institute. Previously, since 2012, he held a scholarship of the Italian National Research Council (IREA-CNR).

His research interests include processing of synthetic aperture radar (SAR) images for single and multi-baseline interferometry with specific application to surface deformation monitoring and digital elevation model (DEM) generation. Further interests concern the development of algorithms for the land cover classification from SAR and optical data.

Research objectives

  • Development of novel and efficient algorithms for forest mapping with Sentinel-1 data stacks
  • Exploration of the potential of repeat-pass interferometry with Sentinel-1 for classification purposes
  • Quantification of on-going deforestation and generation of large-scale maps of changes and deforestation rate
  • Optimisation of the approach for the detection of changes in terms of resolution in space (high-resolution maps) and time (quick response to deforestation activities).

Read more in the research project sheet.

Scientific papers


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