Improving the performance of 3-D radiative transfer model FLIGHT to simulate optical properties of a tree-grass ecosystem
Melendo-Vega, J.R. ; Martín, M.P. ; Pacheco-Labrador, J. ; González-Cascón, R. ; Moreno, G. ; Pérez, F. (Universidad de Zaragoza) ; Migliavacca, M. ; García, M. ; North, P. ; Riaño, D.
Resumen: The 3-D Radiative Transfer Model (RTM) FLIGHT can represent scattering in open forest or savannas featuring underlying bare soils. However, FLIGHT might not be suitable for multilayered tree-grass ecosystems (TGE), where a grass understory can dominate the reflectance factor (RF) dynamics due to strong seasonal variability and low tree fractional cover. To address this issue, we coupled FLIGHT with the 1-D RTM PROSAIL. The model is evaluated against spectral observations of proximal and remote sensing sensors: the ASD Fieldspec® 3 spectroradiometer, the Airborne Spectrographic Imager (CASI) and the MultiSpectral Instrument (MSI) onboard Sentinel- 2. We tested the capability of both PROSAIL and PROSAIL+FLIGHT to reproduce the variability of different phenological stages determined by 16-year time series analysis of Moderate Resolution Imaging Spectroradiometer-Normalized Difference Vegetation Index (MODIS-NDVI). Then, we combined concomitant observations of biophysical variables and RF to test the capability of the models to reproduce observed RF. PROSAIL achieved a Relative Root Mean Square Error (RRMSE) between 6% to 32% at proximal sensing scale. PROSAIL+FLIGHT RRMSE ranged between 7% to 31% at remote sensing scales. RRMSE increased in periods when large fractions of standing dead material mixed with emergent green grasses -especially in autumn-; suggesting that the model cannot represent the spectral features of this material. PROSAIL+FLIGHT improves RF simulation especially in summer and at mid-high view angles.
Idioma: Inglés
DOI: 10.3390/rs10122061
Año: 2018
Publicado en: Remote Sensing 10, 12 (2018), 2061 [33 pp]
ISSN: 2072-4292
Factor impacto JCR: 4.118 (2018)
Categ. JCR: REMOTE SENSING rank: 7 / 30 = 0.233 (2018) - Q1 - T1
Factor impacto SCIMAGO: 1.43 - Earth and Planetary Sciences (miscellaneous) (Q1)
Financiación: info:eu-repo/grantAgreement/ES/MEC/FPU15-03558
Financiación: info:eu-repo/grantAgreement/ES/MINECO/CGL2012-34383
Financiación: info:eu-repo/grantAgreement/ES/MINECO/CGL2015-G9095-R
Tipo y forma: Article (Published version)
Área (Departamento): Área Análisis Geográfico Regi. (Dpto. Geograf. Ordenac.Territ.)
You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
Exportado de SIDERAL (2020-01-17-21:56:34)
Idioma: Inglés
DOI: 10.3390/rs10122061
Año: 2018
Publicado en: Remote Sensing 10, 12 (2018), 2061 [33 pp]
ISSN: 2072-4292
Factor impacto JCR: 4.118 (2018)
Categ. JCR: REMOTE SENSING rank: 7 / 30 = 0.233 (2018) - Q1 - T1
Factor impacto SCIMAGO: 1.43 - Earth and Planetary Sciences (miscellaneous) (Q1)
Financiación: info:eu-repo/grantAgreement/ES/MEC/FPU15-03558
Financiación: info:eu-repo/grantAgreement/ES/MINECO/CGL2012-34383
Financiación: info:eu-repo/grantAgreement/ES/MINECO/CGL2015-G9095-R
Tipo y forma: Article (Published version)
Área (Departamento): Área Análisis Geográfico Regi. (Dpto. Geograf. Ordenac.Territ.)
You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Exportado de SIDERAL (2020-01-17-21:56:34)
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Record created 2019-01-30, last modified 2020-01-17