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Monitoring forest degradation using terrestrial lidar and satellite images

Final Report Summary - STRUCCHANGE (Monitoring forest degradation using terrestrial lidar and satellite images)

Monitoring forest change using terrestrial LIDAR and satellite images: Strucchange
Natural resource managers, policy makers and researchers demand knowledge of deforestation and forest degradation over increasingly large spatial and temporal extents for addressing many pressing issues such as climate change mitigation and adaptation, carbon dynamics, biodiversity, and food security. The scientific community is witnessing a significant increase in the availability of different global satellite derived biophysical data sets (e.g. biomass and surface photosynthesis). However, the use of such data is not supported by accurate in-situ biophysical measurements (e.g. canopy structure) for the monitoring of forest and land dynamics. Consequently, there is an urgent need for methods to measure in-situ canopy structure accurately and better integrate with improved and innovative remote sensing approaches.

The research performed within the MC IRG has addressed this need by solving three core challenges. Main outcomes are published in peer-reviewed publications. Firstly, methods are developed to retrieve forest canopy structure attributes and biomass using a novel type of ground-based upward-looking laser scanner (Calders et al. 2013). Secondly, a physical modeling approach is used which provides a more rigorous framework than prior methods, which largely used regression relationships, to study relationship between the retrieved canopy attributes and satellite data (Calders et al. 2012 and 2013). Finally, these accurate satellite-derived biophysical data sets enable assessment deforestation and forest degradation (De Jong et al. 2012, 2013, De Sy et al. 2012, Reiche et al. 2013, Verbesselt et al. 2012,). However, existing methods to detect changes in satellite data are not able account for seasonal climatic variations. A new approach is therefore proposed to account for seasonality while detecting changes in forest ecosystems (Verbesselt et al. 2011, 2012) (Fig. 1). The research efforts are part of a coordinated research activity among groups in Europe, Australia, and USA.

A summary of main research outcome during the Marie Curie IRG (publications, figures) can be found here on (1) the project website (change monitoring), (2) terrestrial LIDAR website and (3) Open source code and functions are published and made available via : A full and complete overview of all relevant publications and their impact factors can be found via research candidate’s publication profile.

In conclusion, the Strucchange project facilitated by the Marie Curie (MC ) IRG grant is a success story for three main reasons. Firstly, Jan Verbesselt is currently continuing his academic career, on a tenure track towards a full professor position at the Remote Sensing group of Wageningen University. Secondly, high quality peer-review papers were published (see publication overview) thanks to intense collaboration with the Wageningen research team and other groups internationally (Belgium, Australia, Austria, US). Thirdly, based on peer-reviewed papers, open-source software was published via the Strucchange project website called BFAST ( This open-source code platform led to a high impact and resulted in new scientific projects and collaboration with companies (i.e. Google) who are currently implementing the Strucchange algorithms for “Global near real-time deforestation Monitoring” using the Google Earth Engine Deforestation project. An extra research grant for operational implementation of change monitoring code was awarded to the BFAST coding project. Fig. 2 and 3 illustrate the socio-economic impact of the Strucchange – BFAST code project globally via reported statistics of visitors of the project website.

The appendix (attached pdf with publishable summary) contains all figures, publications, and website links.