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Article: Fractional vegetation cover estimation in heterogeneous areas by combining a radiative transfer model and a dynamic vegetation model

TitleFractional vegetation cover estimation in heterogeneous areas by combining a radiative transfer model and a dynamic vegetation model
Authors
KeywordsDynamic Bayesian network
dynamic vegetation model
fractional vegetation cover
global land surface satellite
radiative transfer model
Issue Date2020
Citation
International Journal of Digital Earth, 2020, v. 13, n. 4, p. 487-503 How to Cite?
AbstractA fractional vegetation cover (FVC) estimation method incorporating a vegetation growth model and a radiative transfer model was previously developed, which was suitable for FVC estimation in homogeneous areas because the finer-resolution pixels corresponding to one coarse-resolution FVC pixel were all assumed to have the same vegetation growth model. However, this assumption does not hold over heterogeneous areas, meaning that the method cannot be applied to large regions. Therefore, this study proposes a finer spatial resolution FVC estimation method applicable to heterogeneous areas using Landsat 8 Operational Land Imager reflectance data and Global LAnd Surface Satellite (GLASS) FVC product. The FVC product was first decomposed according to the normalized difference vegetation index from the Landsat 8 OLI data. Then, independent dynamic vegetation models were built for each finer-resolution pixel. Finally, the dynamic vegetation model and a radiative transfer model were combined to estimate FVC at the Landsat 8 scale. Validation results indicated that the proposed method (R2 = 0.7757, RMSE = 0.0881) performed better than either the previous method (R2 = 0.7038, RMSE = 0.1125) or a commonly used method involving look-up table inversions of the PROSAIL model (R2 = 0.7457, RMSE = 0.1249).
Persistent Identifierhttp://hdl.handle.net/10722/321809
ISSN
2023 Impact Factor: 3.7
2023 SCImago Journal Rankings: 0.950
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorTu, Yixuan-
dc.contributor.authorJia, Kun-
dc.contributor.authorLiang, Shunlin-
dc.contributor.authorWei, Xiangqin-
dc.contributor.authorYao, Yunjun-
dc.contributor.authorZhang, Xiaotong-
dc.date.accessioned2022-11-03T02:21:35Z-
dc.date.available2022-11-03T02:21:35Z-
dc.date.issued2020-
dc.identifier.citationInternational Journal of Digital Earth, 2020, v. 13, n. 4, p. 487-503-
dc.identifier.issn1753-8947-
dc.identifier.urihttp://hdl.handle.net/10722/321809-
dc.description.abstractA fractional vegetation cover (FVC) estimation method incorporating a vegetation growth model and a radiative transfer model was previously developed, which was suitable for FVC estimation in homogeneous areas because the finer-resolution pixels corresponding to one coarse-resolution FVC pixel were all assumed to have the same vegetation growth model. However, this assumption does not hold over heterogeneous areas, meaning that the method cannot be applied to large regions. Therefore, this study proposes a finer spatial resolution FVC estimation method applicable to heterogeneous areas using Landsat 8 Operational Land Imager reflectance data and Global LAnd Surface Satellite (GLASS) FVC product. The FVC product was first decomposed according to the normalized difference vegetation index from the Landsat 8 OLI data. Then, independent dynamic vegetation models were built for each finer-resolution pixel. Finally, the dynamic vegetation model and a radiative transfer model were combined to estimate FVC at the Landsat 8 scale. Validation results indicated that the proposed method (R2 = 0.7757, RMSE = 0.0881) performed better than either the previous method (R2 = 0.7038, RMSE = 0.1125) or a commonly used method involving look-up table inversions of the PROSAIL model (R2 = 0.7457, RMSE = 0.1249).-
dc.languageeng-
dc.relation.ispartofInternational Journal of Digital Earth-
dc.subjectDynamic Bayesian network-
dc.subjectdynamic vegetation model-
dc.subjectfractional vegetation cover-
dc.subjectglobal land surface satellite-
dc.subjectradiative transfer model-
dc.titleFractional vegetation cover estimation in heterogeneous areas by combining a radiative transfer model and a dynamic vegetation model-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/17538947.2018.1531438-
dc.identifier.scopuseid_2-s2.0-85054740768-
dc.identifier.volume13-
dc.identifier.issue4-
dc.identifier.spage487-
dc.identifier.epage503-
dc.identifier.eissn1753-8955-
dc.identifier.isiWOS:000519341300004-

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