Estimating herbaceous aboveground biomass in Sahelian rangelands using Structure from Motion data collected on the ground and by UAV. Issue 5 (1st May 2022) - Taugourdeau, Simon; Diedhiou, Antoine; Fassinou, Cofélas; Bossoukpe, Marina; Diatta, Ousmane; N'Goran, Ange; Auderbert, Alain; Ndiaye, Ousmane; Diouf, Abdoul Aziz; Tagesson, Torbern; Fensholt, Rasmus; Faye, Emile
Abstract: Herbaceous aboveground biomass (HAB) is a key indicator of grassland vegetation and indirect estimation tools, such as remote sensing imagery, increase the potential for covering larger areas in a timely and cost‐efficient way. Structure from Motion (SfM) is an image analysis process that can create a variety of 3D spatial models as well as 2D orthomosaics from a set of images. Computed from Unmanned Aerial Vehicle (UAV) and ground camera measurements, the SfM potential to estimate the herbaceous aboveground biomass in Sahelian rangelands was tested in this study. Both UAV and ground camera recordings were used at three different scales: temporal, landscape, and national (across Senegal). All images were processed using PIX4D software (photogrammetry software) and were used to extract vegetation indices and heights. A random forest algorithm was used to estimate the HAB and the average estimation errors were around 150 g m − ² for fresh mass (20% relative error) and 60 g m − ² for dry mass (around 25% error). A comparison between different datasets revealed that the estimates based on camera data were slightly more accurate than those from UAV data. It was also found that combining datasets across scales for the same type of tool (UAV or camera) could be a useful option for monitoring HAB in Sahelian rangelands or in other grassy ecosystems. Abstract : We tested UAV and Ground camera photogrammetry for the evaluation of herbaceous biomass of Sahelian rangeland. We show that both UAV and ground camera can be used for the evaluation of the biomass during a season and across different spatial scales. Our work shows the possibility of the intercalibration between different datasets.