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- Publisher Website: 10.1016/j.jag.2016.07.017
- Scopus: eid_2-s2.0-84998886414
- PMID: 29618964
- WOS: WOS:000383003500053
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Article: Scaling estimates of vegetation structure in Amazonian tropical forests using multi-angle MODIS observations
Title | Scaling estimates of vegetation structure in Amazonian tropical forests using multi-angle MODIS observations |
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Authors | |
Keywords | Anisotropy Canopy roughness LiDAR MAIAC MODIS Multi-angle |
Issue Date | 2016 |
Citation | International Journal of Applied Earth Observation and Geoinformation, 2016, v. 52, p. 580-590 How to Cite? |
Abstract | Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r2 = 0.54, RMSE = 0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy (0.52 ≤ r2 ≤ 0.61; p < 0.05), with similar slopes and offsets found throughout the season, and RMSE between 0.26 and 0.30 (units of entropy). The relationships between the MODIS-derived anisotropy and backscattering measurements (σ0) from SeaWinds/QuikSCAT presented an r2 of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon. |
Persistent Identifier | http://hdl.handle.net/10722/309235 |
ISSN | 2023 Impact Factor: 7.6 2023 SCImago Journal Rankings: 2.108 |
PubMed Central ID | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Moura, Yhasmin Mendes de | - |
dc.contributor.author | Hilker, Thomas | - |
dc.contributor.author | Gonçalves, Fabio Guimarães | - |
dc.contributor.author | Galvão, Lênio Soares | - |
dc.contributor.author | dos Santos, João Roberto | - |
dc.contributor.author | Lyapustin, Alexei | - |
dc.contributor.author | Maeda, Eduardo Eiji | - |
dc.contributor.author | de Jesus Silva, Camila Valéria | - |
dc.date.accessioned | 2021-12-15T03:59:48Z | - |
dc.date.available | 2021-12-15T03:59:48Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | International Journal of Applied Earth Observation and Geoinformation, 2016, v. 52, p. 580-590 | - |
dc.identifier.issn | 1569-8432 | - |
dc.identifier.uri | http://hdl.handle.net/10722/309235 | - |
dc.description.abstract | Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r2 = 0.54, RMSE = 0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy (0.52 ≤ r2 ≤ 0.61; p < 0.05), with similar slopes and offsets found throughout the season, and RMSE between 0.26 and 0.30 (units of entropy). The relationships between the MODIS-derived anisotropy and backscattering measurements (σ0) from SeaWinds/QuikSCAT presented an r2 of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon. | - |
dc.language | eng | - |
dc.relation.ispartof | International Journal of Applied Earth Observation and Geoinformation | - |
dc.subject | Anisotropy | - |
dc.subject | Canopy roughness | - |
dc.subject | LiDAR | - |
dc.subject | MAIAC | - |
dc.subject | MODIS | - |
dc.subject | Multi-angle | - |
dc.title | Scaling estimates of vegetation structure in Amazonian tropical forests using multi-angle MODIS observations | - |
dc.type | Article | - |
dc.description.nature | link_to_OA_fulltext | - |
dc.identifier.doi | 10.1016/j.jag.2016.07.017 | - |
dc.identifier.pmid | 29618964 | - |
dc.identifier.pmcid | PMC5880039 | - |
dc.identifier.scopus | eid_2-s2.0-84998886414 | - |
dc.identifier.volume | 52 | - |
dc.identifier.spage | 580 | - |
dc.identifier.epage | 590 | - |
dc.identifier.eissn | 1872-826X | - |
dc.identifier.isi | WOS:000383003500053 | - |