Terrain Slope Effect on Forest Height and Wood Volume Estimation from GEDI Data
The Global Ecosystem Dynamics Investigation LiDAR (GEDI) is a new full waveform (FW) based LiDAR system that presents a new opportunity for the observation of forest structures globally. The backscattered GEDI signals, as all FW systems, are distorted by topographic conditions within their footprint...
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MDPI AG
2021-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/11/2136 |
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| author | Ibrahim Fayad Nicolas Baghdadi Clayton Alcarde Alvares Jose Luiz Stape Jean Stéphane Bailly Henrique Ferraço Scolforo Italo Ramos Cegatta Mehrez Zribi Guerric Le Maire |
| author_facet | Ibrahim Fayad Nicolas Baghdadi Clayton Alcarde Alvares Jose Luiz Stape Jean Stéphane Bailly Henrique Ferraço Scolforo Italo Ramos Cegatta Mehrez Zribi Guerric Le Maire |
| author_sort | Ibrahim Fayad |
| collection | DOAJ |
| description | The Global Ecosystem Dynamics Investigation LiDAR (GEDI) is a new full waveform (FW) based LiDAR system that presents a new opportunity for the observation of forest structures globally. The backscattered GEDI signals, as all FW systems, are distorted by topographic conditions within their footprint, leading to uncertainties on the measured forest variables. In this study, we explore how well several approaches based on waveform metrics and ancillary digital elevation model (DEM) data perform on the estimation of stand dominant heights (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>H</mi><mrow><mi>d</mi><mi>o</mi><mi>m</mi></mrow></msub></mrow></semantics></math></inline-formula>) and wood volume (V) across different sites of Eucalyptus plantations with varying terrain slopes. In total, five models were assessed on their ability to estimate <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>H</mi><mrow><mi>d</mi><mi>o</mi><mi>m</mi></mrow></msub></mrow></semantics></math></inline-formula> and four models for V. Results showed that the models using the GEDI metrics, such as the height at different energy quantiles with terrain data from the shuttle radar topography mission’s (SRTM) digital elevation model (DEM) were still dependent on the topographic slope. For <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>H</mi><mrow><mi>d</mi><mi>o</mi><mi>m</mi></mrow></msub></mrow></semantics></math></inline-formula>, an RMSE increase of 14% was observed for data acquired over slopes higher than 20% in comparison to slopes between 10 and 20%. For V, a 74% increase in RMSE was reported between GEDI data acquired over slopes between 0–10% and those acquired over slopes higher than 10%. Next, a model relying on the height at different energy quantiles of the entire waveform (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><msub><mi>T</mi><mi>n</mi></msub></mrow></semantics></math></inline-formula>) and the height at different energy quartiles of the bare ground waveform (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><msub><mi>G</mi><mi>n</mi></msub></mrow></semantics></math></inline-formula>) was assessed. Two sets of the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><msub><mi>G</mi><mi>n</mi></msub></mrow></semantics></math></inline-formula> metrics were generated, the first one was obtained using a simulated waveform representing the echo from a bare ground, while the second one relied on the actual ground return from the waveform by means of Gaussian fitting. Results showed that both the simulated and fitted models provide the most accurate estimates of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>H</mi><mrow><mi>d</mi><mi>o</mi><mi>m</mi></mrow></msub></mrow></semantics></math></inline-formula> and V for all slope ranges. The simulation-based model showed an RMSE that ranged between 1.39 and 1.66 m (between 26.76 and 39.26 m<sup>3</sup>·ha<sup>−1</sup> for V) while the fitting-based method showed an RMSE that ranged between 1.26 and 1.34 m (between 26.78 and 36.29 m<sup>3</sup>·ha<sup>−1</sup> for V). Moreover, the dependency of the GEDI metrics on slopes was greatly reduced using the two sets of metrics. As a conclusion, the effect of slopes on the 25-m GEDI footprints is rather low as the estimation on canopy heights from uncorrected waveforms degraded by a maximum of 1 m for slopes between 20 and 45%. Concerning the wood volume estimation, the effect of slopes was more pronounced, and a degradation on the accuracy (increased RMSE) of a maximum of 20 m<sup>3</sup>·ha<sup>−1</sup> was observed for slopes between 20 and 45%. |
| first_indexed | 2024-03-10T10:54:17Z |
| format | Article |
| id | doaj.art-0eebac6bba6e4325b85c8e70773ab8ce |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T10:54:17Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-0eebac6bba6e4325b85c8e70773ab8ce2023-11-21T21:56:39ZengMDPI AGRemote Sensing2072-42922021-05-011311213610.3390/rs13112136Terrain Slope Effect on Forest Height and Wood Volume Estimation from GEDI DataIbrahim Fayad0Nicolas Baghdadi1Clayton Alcarde Alvares2Jose Luiz Stape3Jean Stéphane Bailly4Henrique Ferraço Scolforo5Italo Ramos Cegatta6Mehrez Zribi7Guerric Le Maire8CIRAD, CNRS, INRAE, TETIS, AgroParisTech, University Montpellier, CEDEX 5, 34093 Montpellier, FranceCIRAD, CNRS, INRAE, TETIS, AgroParisTech, University Montpellier, CEDEX 5, 34093 Montpellier, FranceUnesp, Faculdade de Ciências Agronômicas, Botucatu 18610-034, BrazilUnesp, Faculdade de Ciências Agronômicas, Botucatu 18610-034, BrazilInstitut Agroalimentaire, LISAH, University Montpellier, INRAE, IRD, CEDEX 1, 34060 Montpellier, FranceSuzano SA, Estrada Limeira 391, Limeira 13465-970, BrazilSuzano SA, Estrada Limeira 391, Limeira 13465-970, BrazilCESBIO, Université de Toulouse, CNES/CNRS/INRAE/IRD/UPS, 31400 Toulouse, FranceCIRAD, UMR Eco&Sols, 34398 Montpellier, FranceThe Global Ecosystem Dynamics Investigation LiDAR (GEDI) is a new full waveform (FW) based LiDAR system that presents a new opportunity for the observation of forest structures globally. The backscattered GEDI signals, as all FW systems, are distorted by topographic conditions within their footprint, leading to uncertainties on the measured forest variables. In this study, we explore how well several approaches based on waveform metrics and ancillary digital elevation model (DEM) data perform on the estimation of stand dominant heights (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>H</mi><mrow><mi>d</mi><mi>o</mi><mi>m</mi></mrow></msub></mrow></semantics></math></inline-formula>) and wood volume (V) across different sites of Eucalyptus plantations with varying terrain slopes. In total, five models were assessed on their ability to estimate <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>H</mi><mrow><mi>d</mi><mi>o</mi><mi>m</mi></mrow></msub></mrow></semantics></math></inline-formula> and four models for V. Results showed that the models using the GEDI metrics, such as the height at different energy quantiles with terrain data from the shuttle radar topography mission’s (SRTM) digital elevation model (DEM) were still dependent on the topographic slope. For <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>H</mi><mrow><mi>d</mi><mi>o</mi><mi>m</mi></mrow></msub></mrow></semantics></math></inline-formula>, an RMSE increase of 14% was observed for data acquired over slopes higher than 20% in comparison to slopes between 10 and 20%. For V, a 74% increase in RMSE was reported between GEDI data acquired over slopes between 0–10% and those acquired over slopes higher than 10%. Next, a model relying on the height at different energy quantiles of the entire waveform (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><msub><mi>T</mi><mi>n</mi></msub></mrow></semantics></math></inline-formula>) and the height at different energy quartiles of the bare ground waveform (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><msub><mi>G</mi><mi>n</mi></msub></mrow></semantics></math></inline-formula>) was assessed. Two sets of the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><msub><mi>G</mi><mi>n</mi></msub></mrow></semantics></math></inline-formula> metrics were generated, the first one was obtained using a simulated waveform representing the echo from a bare ground, while the second one relied on the actual ground return from the waveform by means of Gaussian fitting. Results showed that both the simulated and fitted models provide the most accurate estimates of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>H</mi><mrow><mi>d</mi><mi>o</mi><mi>m</mi></mrow></msub></mrow></semantics></math></inline-formula> and V for all slope ranges. The simulation-based model showed an RMSE that ranged between 1.39 and 1.66 m (between 26.76 and 39.26 m<sup>3</sup>·ha<sup>−1</sup> for V) while the fitting-based method showed an RMSE that ranged between 1.26 and 1.34 m (between 26.78 and 36.29 m<sup>3</sup>·ha<sup>−1</sup> for V). Moreover, the dependency of the GEDI metrics on slopes was greatly reduced using the two sets of metrics. As a conclusion, the effect of slopes on the 25-m GEDI footprints is rather low as the estimation on canopy heights from uncorrected waveforms degraded by a maximum of 1 m for slopes between 20 and 45%. Concerning the wood volume estimation, the effect of slopes was more pronounced, and a degradation on the accuracy (increased RMSE) of a maximum of 20 m<sup>3</sup>·ha<sup>−1</sup> was observed for slopes between 20 and 45%.https://www.mdpi.com/2072-4292/13/11/2136GEDILiDARterrain slopecanopy heightwood volume |
| spellingShingle | Ibrahim Fayad Nicolas Baghdadi Clayton Alcarde Alvares Jose Luiz Stape Jean Stéphane Bailly Henrique Ferraço Scolforo Italo Ramos Cegatta Mehrez Zribi Guerric Le Maire Terrain Slope Effect on Forest Height and Wood Volume Estimation from GEDI Data Remote Sensing GEDI LiDAR terrain slope canopy height wood volume |
| title | Terrain Slope Effect on Forest Height and Wood Volume Estimation from GEDI Data |
| title_full | Terrain Slope Effect on Forest Height and Wood Volume Estimation from GEDI Data |
| title_fullStr | Terrain Slope Effect on Forest Height and Wood Volume Estimation from GEDI Data |
| title_full_unstemmed | Terrain Slope Effect on Forest Height and Wood Volume Estimation from GEDI Data |
| title_short | Terrain Slope Effect on Forest Height and Wood Volume Estimation from GEDI Data |
| title_sort | terrain slope effect on forest height and wood volume estimation from gedi data |
| topic | GEDI LiDAR terrain slope canopy height wood volume |
| url | https://www.mdpi.com/2072-4292/13/11/2136 |
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