Studentinformatie

Msc thesis subject: Exploring new estimators for tropical forest above-ground biomass based on UAV laser scanning

In recent years, Terrestrial Laser Scanning (TLS) has revolutionised the opportunities for forest above-ground biomass (AGB) estimation through explicit, geometrical modelling of the tree. Some of the developed approaches are treated as a new standard for AGB reference measurements in the context of satellite mission calibration/validation tasks. However, TLS is labour and time intense. Airborne Laser Scanning (ALS) is capable to cover large areas and collect structural information that can be used to create local AGB maps for space-borne mission calibration. The disadvantage of ALS are high acquisition costs and low point density compared with TLS. Recently, Unmanned Aerial Vehicle Laser Scanning (UAV-LS) technology has made the step from prototypes to marketed solutions with promising first results in forestry. UAV-LS could be a bridge between TLS and ALS, combining desirable advantages of both.

The GRS group has a UAV-LS system available, the Riegl RiCopter with VUX1. This system has been tested in various applications in the Netherlands, including explicit 3D tree modelling. How useful the point clouds are in tropical forests is still unknown. Therefore, a field campaign to the Paracou field site in French Guiana is planned for end of 2019 to collect UAV-LS together with field inventory and TLS data.

Objectives

  • Review literature on AGB estimation with field inventories/allometric scaling equations, ALS and TLS
  • Option: Take part in the tropical field campaign in French Guiana
  • Prepare the different datasets (UAV-lidar, field inventory data, TLS) for analysis
  • Test proven ALS-like AGB estimators with UAV-LS
  • Develop and test new UAV-LS AGB estimators

Literature

  • Brede, B., Lau, A., Bartholomeus, H.M., Kooistra, L., 2017. Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR. Sensors 17, 2371. doi:10.3390/s17102371
  • Calders, K., Newnham, G., Burt, A., Murphy, S., Raumonen, P., Herold, M., Culvenor, D., Avitabile, V., Disney, M., Armston, J., Kaasalainen, M., 2015. Nondestructive estimates of above-ground biomass using terrestrial laser scanning. Methods Ecol. Evol. 6, 198–208. doi:10.1111/2041-210X.12301
  • Drake, J.B., Dubayah, R.O., Clark, D.B., Knox, R.G., Blair, J.B., Hofton, M.A., Chazdon, R.L., Weishampel, J.F., Prince, S., 2002. Estimation of tropical forest structural characteristics using large-footprint lidar. Remote Sens. Environ. 79, 305–319. doi:10.1016/S0034-4257(01)00281-4

Requirements

  • Basic scripting skills (e.g. R, Python, MatLab) (more will be learned during the thesis)
  • Fitness for fieldwork in tropical forests

Theme(s): Sensing & measuring