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Estimating herbaceous aboveground biomass in Sahelian rangelands using Structure from Motion data collected on the ground and by UAV.
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.
Afiliação
  • Taugourdeau S; CIRAD UMR SELMET- PPZS Dakar Senegal.
  • Diedhiou A; UMR SELMET CIRAD, INRA Institut Agro Univ Montpellier Montpellier France.
  • Fassinou C; Departement Biologie végétale - PPZS UCAD Dakar Senegal.
  • Bossoukpe M; Departement Biologie végétale - PPZS UCAD Dakar Senegal.
  • Diatta O; ISRA CRZ (Centre de Recherches Zootechniques) Dahra-PPZS Dahra Djoloff Senegal.
  • N'Goran A; Departement Biologie végétale - PPZS UCAD Dakar Senegal.
  • Auderbert A; Departement Biologie végétale - PPZS UCAD Dakar Senegal.
  • Ndiaye O; ISRA CRZ (Centre de Recherches Zootechniques) Dahra-PPZS Dahra Djoloff Senegal.
  • Diouf AA; Departement Biologie végétale - PPZS UCAD Dakar Senegal.
  • Tagesson T; ISRA CRZ (Centre de Recherches Zootechniques) Dahra-PPZS Dahra Djoloff Senegal.
  • Fensholt R; CIRAD, INRAE UMR AGAP Institut Univ Montpellier Montpellier France.
  • Faye E; ISRA CRZ (Centre de Recherches Zootechniques) Dahra-PPZS Dahra Djoloff Senegal.
Ecol Evol ; 12(5): e8867, 2022 May.
Article em En | MEDLINE | ID: mdl-35509616
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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article