Sensing & measuring

This field deals with quantitative, physical and statistical based retrieval of land surface parameters relevant for multiple monitoring applications and earth system modelling.

Activities are ongoing to advance foundations for quantitative land remote sensing and to improve in-situ data collection and analysis for development, calibration and validation of the next generation remote sensing data and products.

Particular attention is paid to the use of innovative in-situ and laboratory based measurements (WUR goniometer system, terrestrial LIDAR, sensor webs), unmanned airborne vehicles (UAVs), radiative transfer models, vegetation indices, data assimilation methods, linking soil-vegetation-atmosphere transfer models, soil spectroscopy and calibration and validation procedures. Our sensing scientific research is underpinned by our long-term expertise in using advanced earth observation techniques (i.e. imaging spectroscopy and LIDAR) in combination with ecological and dynamic vegetation models for applications. Some examples are biodiversity assessment at habitat and ecosystem level, assessing vegetation characteristics and carbon stocks and combining sensing techniques with crop growth models for precision farming.

PhD projects:

  • Anne Hoek van Dijke: The link between vegetation functional traits and evapotranspiration
  • Gustavo Togeiro De Alckmin: Compare and contrast approaches of measurement of perennial ryegrass for biophysical and biochemical attributes
  • Ximena Tagle Casapia: Integration of high resolution imagery from UAVs for Mapping of Provisioning Ecosystem Services in the tropics
  • Na Wang: Measuring sun-induced fluorescence using UAV-based remote sensing
  • Benjamin Brede: Multi-sensor approach for next generation forest biophysical satellite products
  • Marston Domingues Franceschini: Developing UAV based hyperspectral approaches for disease detection in arable cropping systems 

Post-doc projects:

  • Milutin Milenkovic: Monitoring Tropical Forest Recovery and Resilience using Big Data Approaches for Optical and RADAR Sentinel Satellite Data
  • Joao Pereira Valente: Spectors
  • Peter Roosjen: Automated Airborne Pest Management

Recently finished PhDs:

Key publications: