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An alternative AMSR2 vegetation optical depth for monitoring vegetation at large scales

hal.structure.identifierBeijing Normal University [BNU]
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorWANG, Mengjia
hal.structure.identifierSouthwest University [Chongqing]
dc.contributor.authorFAN, Lei
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
hal.structure.identifierLaboratoire d'études en Géophysique et océanographie spatiales [LEGOS]
dc.contributor.authorFRAPPART, Frédéric
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
hal.structure.identifierICOS-ATC [ICOS-ATC]
dc.contributor.authorCIAIS, Philippe
hal.structure.identifierBeijing Normal University [BNU]
dc.contributor.authorSUN, Rui
hal.structure.identifierNanjing University of Information Science and Technology [NUIST]
dc.contributor.authorLIU, Yi
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLI, Xiaojun
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLIU, Xiangzhuo
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorMOISY, Christophe
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorJ.-P., Wigneron
dc.date.accessioned2024-04-08T11:43:32Z
dc.date.available2024-04-08T11:43:32Z
dc.date.issued2021-09
dc.identifier.issn0034-4257
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/195111
dc.description.abstractEnVegetation optical depth (VOD) retrieved from microwave observations has been found to be useful to monitor the dynamics of the vegetation features at global scale. Particularly, many applications could be developed in several fields of research (ecology, water and carbon cycle, etc.) from VOD products retrieved from the SMOS and SMAP observations at L-band, and from the combined AMSR-E (2002−2011)/AMSR2 (2012-present) observations at C- and X-bands. One of the main difficulties in retrieving VOD is that the microwave observations are sensitive to both the soil (mainly soil moisture) and vegetation (mostly VOD) features. The AMSR-E/2 sensors provide only mono-angular observations at two polarizations. These dual-channel observations may be strongly correlated so that retrieving SM and VOD simultaneously can be an ill-posed problem. Here, to overcome this problem, we proposed and evaluated a new retrieval approach from AMSR2 observations at X-band to produce a new X-VOD product. The X-VOD retrievals were based on the inversion of the X-MEB model, an extension of the L-MEB model (L-band microwave emission of the biosphere) to the X-band. The main originality in comparison to previous algorithms is that (i) only VOD was retrieved while SM was estimated from a reanalysis data set (ERA5-Land); (ii) model inversion was based on an innovative approach to initialize the cost function; and (iii) new values for the soil and vegetation X-MEB model parameters were calibrated. To evaluate the methodology, we performed the VOD retrievals over the whole African continent over 2014–2016, including a dry (2015) and a wet (2014) year. In a first step, we calibrated a set of three parameters: effective scattering albedo (ω), soil roughness (HR) and VOD first guess (VODini). Several datasets of vegetation indices as Above-Ground Biomass (AGB), Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI) were chosen as reference data to optimize these model parameters. Globally-constant values (ω = 0.06 and HR = 0.6) were found to achieve high spatial and temporal correlations between retrieved X-VOD and the reference vegetation parameters. Comparison with other X-VOD products suggested IB X-VOD had competitive advantages in terms of both spatial and temporal performances. In particular, spatial correlation with three biomass datasets was found to be higher than for previous X-VOD products (R2 ~ 0.76–0.83) and temporal correlation with LAI or NDVI showed obvious improvements, especially in dense vegetation.
dc.language.isoen
dc.publisherElsevier
dc.rights.urihttp://creativecommons.org/licenses/by-nc/
dc.subject.enVegetation optical depth
dc.subject.enAfrica
dc.subject.enBiomass
dc.subject.enAMSR2
dc.subject.enIB X-VOD
dc.subject.enLPRM
dc.subject.enLPDR
dc.title.enAn alternative AMSR2 vegetation optical depth for monitoring vegetation at large scales
dc.typeArticle de revue
dc.identifier.doi10.1016/j.rse.2021.112556
dc.subject.halPlanète et Univers [physics]/Océan, Atmosphère
dc.subject.halPlanète et Univers [physics]/Interfaces continentales, environnement
bordeaux.journalRemote Sensing of Environment
bordeaux.page112556
bordeaux.volume263
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-03265319
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-03265319v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote%20Sensing%20of%20Environment&rft.date=2021-09&rft.volume=263&rft.spage=112556&rft.epage=112556&rft.eissn=0034-4257&rft.issn=0034-4257&rft.au=WANG,%20Mengjia&FAN,%20Lei&FRAPPART,%20Fr%C3%A9d%C3%A9ric&CIAIS,%20Philippe&SUN,%20Rui&rft.genre=article


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