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Simulation of Sentinel-1A observations and constraint of water cloud model at the regional scale using a discrete scattering model

hal.structure.identifierNanjing University [NJU]
dc.contributor.authorBAI, Xiaojing
hal.structure.identifierChinese Academy of Sciences [Beijing] [CAS]
dc.contributor.authorZHENG, Donghai
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLIU, Xiangzhuo
hal.structure.identifierSouthwest University [Chongqing]
dc.contributor.authorFAN, Lei
hal.structure.identifierChinese Academy of Sciences [Beijing] [CAS]
dc.contributor.authorZENG, Jiangyuan
hal.structure.identifierChinese Academy of Sciences [Beijing] [CAS]
dc.contributor.authorLI, Xin
dc.date.accessioned2024-04-08T11:43:49Z
dc.date.available2024-04-08T11:43:49Z
dc.date.issued2022-12
dc.identifier.issn0034-4257
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/195124
dc.description.abstractEnEffective calibration of microwave scattering model and accurate simulation of backscattering coefficient (sigma o) at the regional scale are essential for improving soil moisture retrieval based on active microwave remote sensing. This study investigates the potential of simulating the Sentinel-1A observations and constraining the coefficients of the water cloud model (WCM) at the regional scale based on a theoretical microwave scattering model named Tor Vergata model. The Tor Vergata discrete scattering model is firstly calibrated at both site-and regional-scale to find a single set of model parameters for capturing the Sentinel-1A observations at the regional scale. Sub-sequently, the coupled WCM and Oh model is calibrated at the regional scale based on three strategies, i.e., using either the calibrated Tor Vergata simulations or the Sentinel-1A observations, or with the assumption that the sigma o only comes from the vegetation contribution during the peak growth period. The investigation is conducted in a Tibetan meadow ecosystem configured with a long-term regional-scale soil moisture monitoring network. The results show the optimized parameter values obtained for the Tor Vergata model are consistent with each other based on both calibration methods, leading to comparable performances in simulating well the Sentinel-1A observations and scattering components. These results demonstrate the transferability of model parameters under similar land condition and the feasibility of simulating the regional-scale sigma o based on a single set of model parameters using the Tor Vergata model. The sigma o simulated by the coupled WCM and Oh model based on the three calibration strategies are comparable to each other and well agree with the calibrated Tor Vergata simulations as well as Sentinel-1A observations. However, the traditional calibration method using the Sentinel-1A observations tends to produce unreasonable WCM coefficients and thus unrealistic simulation of vegetation transmissivity. Above deficiencies are largely addressed by other two calibration strategies, whereby the first one preserves the physical mechanism of the Tor Vergata model and reduces the computation cost, and the assumption made by the other strategy may provide a new sight to solve the unknown WCM coefficients. These positive results warrant further investigation for developing new parameterization of WCM to improve soil moisture retrieval at the regional scale based on active microwave remote sensing.
dc.language.isoen
dc.publisherElsevier
dc.subject.enSentinel-1A
dc.subject.enBackscattering coefficient
dc.subject.enTheoretical microwave scattering model
dc.subject.enWater cloud model
dc.subject.enRegional scale
dc.subject.enActive microwave remote sensing
dc.title.enSimulation of Sentinel-1A observations and constraint of water cloud model at the regional scale using a discrete scattering model
dc.typeArticle de revue
dc.identifier.doi10.1016/j.rse.2022.113308
dc.subject.halSciences de l'environnement
bordeaux.journalRemote Sensing of Environment
bordeaux.page113308
bordeaux.volume283
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-04115032
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-04115032v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote%20Sensing%20of%20Environment&rft.date=2022-12&rft.volume=283&rft.spage=113308&rft.epage=113308&rft.eissn=0034-4257&rft.issn=0034-4257&rft.au=BAI,%20Xiaojing&ZHENG,%20Donghai&LIU,%20Xiangzhuo&FAN,%20Lei&ZENG,%20Jiangyuan&rft.genre=article


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