UAV-based multi-angular measurements for improved crop parameter retrieval

Peter P.J. Roosjen

Research output: Thesisinternal PhD, WU


Optical remote sensing enables the estimation of crop parameters based on reflected light through empirical-statistical methods or inversion of radiative transfer models. Natural surfaces, however, reflect light anisotropically, which means that the intensity of reflected light depends on the viewing and illumination geometry. Therefore, reflectance anisotropy can be considered as an unwanted effect since it may lead to inaccuracies in parameter estimations. However, it can also be considered as information source due to its unique response to the optical and structural properties of the observed surface. In the past, reflectance anisotropy was studied by multi-angular reflectance measurements from space-borne or ground-based sensors. In this research, the opportunities of Unmanned Aerial Vehicles (UAVs) to collect multi-angular measurements were explored. The main results of this research show that multi-angular measurements can be done with UAVs and that the reflectance anisotropy signal can be used to improve the retrieval of crop parameters.

Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Wageningen University
  • Herold, Martin, Promotor
  • Clevers, Jan, Co-promotor
  • Bartholomeus, Harm, Co-promotor
Award date17 Nov 2017
Place of PublicationWageningen
Print ISBNs9789463436717
Publication statusPublished - 17 Nov 2017


  • reflectance
  • anisotropy
  • crops
  • soil water content
  • drones
  • remote sensing


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