000076973 001__ 76973
000076973 005__ 20200117221625.0
000076973 0247_ $$2doi$$a10.3390/rs10122061
000076973 0248_ $$2sideral$$a109864
000076973 037__ $$aART-2018-109864
000076973 041__ $$aeng
000076973 100__ $$aMelendo-Vega, J.R.
000076973 245__ $$aImproving the performance of 3-D radiative transfer model FLIGHT to simulate optical properties of a tree-grass ecosystem
000076973 260__ $$c2018
000076973 5060_ $$aAccess copy available to the general public$$fUnrestricted
000076973 5203_ $$aThe 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.
000076973 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/CGL2015-G9095-R$$9info:eu-repo/grantAgreement/ES/MINECO/CGL2012-34383$$9info:eu-repo/grantAgreement/ES/MEC/FPU15-03558
000076973 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000076973 590__ $$a4.118$$b2018
000076973 591__ $$aREMOTE SENSING$$b7 / 30 = 0.233$$c2018$$dQ1$$eT1
000076973 592__ $$a1.43$$b2018
000076973 593__ $$aEarth and Planetary Sciences (miscellaneous)$$c2018$$dQ1
000076973 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000076973 700__ $$aMartín, M.P.
000076973 700__ $$aPacheco-Labrador, J.
000076973 700__ $$aGonzález-Cascón, R.
000076973 700__ $$aMoreno, G.
000076973 700__ $$0(orcid)0000-0003-4831-4060$$aPérez, F.$$uUniversidad de Zaragoza
000076973 700__ $$aMigliavacca, M.
000076973 700__ $$aGarcía, M.
000076973 700__ $$aNorth, P.
000076973 700__ $$aRiaño, D.
000076973 7102_ $$13006$$2010$$aUniversidad de Zaragoza$$bDpto. Geograf. Ordenac.Territ.$$cÁrea Análisis Geográfico Regi.
000076973 773__ $$g10, 12 (2018), 2061 [33 pp]$$pRemote sens. (Basel)$$tRemote Sensing$$x2072-4292
000076973 8564_ $$s1387931$$uhttps://zaguan.unizar.es/record/76973/files/texto_completo.pdf$$yVersión publicada
000076973 8564_ $$s105433$$uhttps://zaguan.unizar.es/record/76973/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000076973 909CO $$ooai:zaguan.unizar.es:76973$$particulos$$pdriver
000076973 951__ $$a2020-01-17-21:56:34
000076973 980__ $$aARTICLE