The phytomass of herbaceous and woody plants is the main source of feed for pastoral livestock in the Sahelian savanna. The assessment of the available feedstock plays a key role in national livestock policies and generally requires many field measurements of both herbaceous and woody plants. In this study, we tested the possibility of using a red-green-blue (RGB) unmanned aerial vehicle (UAV) to evaluate the phytomass of both woody and herbaceous species. We thus mapped 38 one hectare plots with a Dji Spark UAV in Northern Senegal. The herbaceous phytomass was measured on the ground. For the woody communities, we evaluated the leaf phytomass using dendrometric parameters combined with allometric equations. We performed partial-least square regressions between UAV-based three-dimension and color indices and phytomass. Results showed a Q² (cross validation results for each response variable) of 0.57 for woody phytomass, 0.68 for herbaceous dry mass, and 0.76 for their fresh mass. This study confirmed the relevance of using low-cost RGB UAV to assess savanna phytomass.
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Unmanned aerial vehicles (UAVs) are widely used to assess the vegetation of an ecosystem. This report presents three data sets from UAVs used on a savannah-type ecosystem in Senegal. Two data sets contain an orthomosaic and a surface and terrain digital model (UAV outputs), along with associated field measurements on the tree and herbaceous layers, while the third data set contains an orthomosaic and digital surface model, along with field measurements on the herbaceous layers. One data set was compiled over the entire rainy season on the same plot (plot dataset). One was compiled across a landscape at the 7000 ha Dahra Djoloff research center (CRZdahra Centre de recherche zootechnique de Dahra). The third data set was compiled across Senegal from the North to the Southeast of the country with wide variability in climate and soil conditions. All the data sets are in Open Access in the Zenodo repository. These data sets could be used in many different studies: calibration between field measurements and UAV outputs on a large scale, or used as an intermediate step between field and satellite images.
1.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 3D model from a set of images. 2: Computed
from 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 and were used to extract
vegetation indices and heights. 3: 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. 4: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 ecosystem.
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