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Simone Vaccari


MSc Geo-information Science, Wageningen University, Netherlands, 2013; BSc Telecommunication Engineering, University of Trento, Italy, 2010.

Simone is experienced in designing and developing products from remotely sensed satellite imagery that include radar, optical and LiDAR data by using mainly open-source computer programming and geo-spatial software. Simone’s background largely focused on using satellite imagery to estimate forest structural parameters and monitor vegetation changes over time.

Between 2015 and 2016, under the BRACED programme, Simone supported the LTS team in the application of the in-house developed tool RaVeN (Rangeland Vegetation NDVI), which is based on freely available optical and radar satellite imagery, and provides vegetation maps in remote rangeland ecosystems. RaVeN is now being used by the BRACED programme to monitor the impact of the project interventions on pasture quality in rangeland areas in Afar Region, Ethiopia.

Between 2013 and 2015, Simone worked at the University of Edinburgh, in close collaboration with LTS, on the development of FoRAsT, the Forest Radar Assessment Tool that uses high resolution L-band radar imagery to monitoring and quantify forest degradation and forest aboveground carbon changes in dry woodland ecosystems. FoRAsT was tested in Malawi and Sierra Leone within two distinct international development projects.

Simone’s key skills include:

  • Designing, developing and implementing methodologies that exploit Earth Observation data to address project-specific needs;
  • Processing, analysing and interpreting RS imagery;
  • Multi-sensors (e.g. radar, optical, LiDAR) and multi-temporal data fusion;
  • Examples of applications are forest biomass (and carbon) mapping, land cover classification, tree modelling, statistical analysis, and 2D & 3D plotting for data visualisation.


Forast Radar Tool

Vaccari, S.; Ryan, C.; Gou, Y.; Lincoln, P.; Abbot, P., 2014. A tool for monitoring woody biomass (change) in woodland ecosystems, 15th International Radar Symposium (IRS), 16-18 June 2014, 1, pp.1,5,
Vaccari, S., van Leeuwen, M., Calders, K., Coops, N. C., and Herold, M., 2013. Bias in lidar-based canopy gap fraction estimates, Remote Sensing Letters 4(4), pp. 391-399



Service areas:
climate change