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Article: A Novel NIR-Red Spectral Domain Evapotranspiration Model from the Chinese GF-1 Satellite: Application to the Huailai Agricultural Region of China

TitleA Novel NIR-Red Spectral Domain Evapotranspiration Model from the Chinese GF-1 Satellite: Application to the Huailai Agricultural Region of China
Authors
KeywordsChinese GF-1
Evapotranspiration
NIR-red spectral space
perpendicular soil moisture index (PSI)
perpendicular vegetation index (PVI)
Issue Date2021
Citation
IEEE Transactions on Geoscience and Remote Sensing, 2021, v. 59, n. 5, p. 4105-4119 How to Cite?
AbstractThe Chinese GF-1 satellite, the first satellite of the China High-resolution Earth Observation System launched in 2013, can be used to help estimate evapotranspiration (LE), which is important for myriad hydroclimatic and ecosystem science and applications. We propose a novel approach to use the GF-1 visible and near-infrared (VNIR) measurements at 16 m and 4-day resolutions to estimate LE. The NIR (near-infrared)-red spectral-domain (NRSD) model is coupled to a perpendicular soil moisture index (PSI) and a perpendicular vegetation index (PVI). We applied the model to the Huailai agricultural region of China with 55 scenes of GF-1 imagery during 2013-2017 and validated using ground measurements with footprint models for two eddy-covariance (EC) flux tower sites and one large aperture scintillometer (LAS) site. The results illustrate that the terrestrial daily LE can be estimated with squared correlation coefficients (R{2}) of 0.77-0.84 (p < 0.01) and root-mean-square error (RMSE) values of 17.9-21.5 W/m2 among all three sites. The site-calibrated statistics are improved by 0.14-0.25 for R{2} and decreased by 4.2-8.3 W/m2 for RMSE as compared to the commonly used universal PT-JPL model. A satisfactory performance is achieved across all experimental conditions, encouraging the application of the NRSD model to estimate LE for other broad regions.
Persistent Identifierhttp://hdl.handle.net/10722/321928
ISSN
2023 Impact Factor: 7.5
2023 SCImago Journal Rankings: 2.403
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYao, Yunjun-
dc.contributor.authorLiang, Shunlin-
dc.contributor.authorFisher, Joshua B.-
dc.contributor.authorZhang, Yuhu-
dc.contributor.authorCheng, Jie-
dc.contributor.authorChen, Jiquan-
dc.contributor.authorJia, Kun-
dc.contributor.authorZhang, Xiaotong-
dc.contributor.authorBei, Xiangyi-
dc.contributor.authorShang, Ke-
dc.contributor.authorGuo, Xiaozheng-
dc.contributor.authorYang, Junming-
dc.date.accessioned2022-11-03T02:22:25Z-
dc.date.available2022-11-03T02:22:25Z-
dc.date.issued2021-
dc.identifier.citationIEEE Transactions on Geoscience and Remote Sensing, 2021, v. 59, n. 5, p. 4105-4119-
dc.identifier.issn0196-2892-
dc.identifier.urihttp://hdl.handle.net/10722/321928-
dc.description.abstractThe Chinese GF-1 satellite, the first satellite of the China High-resolution Earth Observation System launched in 2013, can be used to help estimate evapotranspiration (LE), which is important for myriad hydroclimatic and ecosystem science and applications. We propose a novel approach to use the GF-1 visible and near-infrared (VNIR) measurements at 16 m and 4-day resolutions to estimate LE. The NIR (near-infrared)-red spectral-domain (NRSD) model is coupled to a perpendicular soil moisture index (PSI) and a perpendicular vegetation index (PVI). We applied the model to the Huailai agricultural region of China with 55 scenes of GF-1 imagery during 2013-2017 and validated using ground measurements with footprint models for two eddy-covariance (EC) flux tower sites and one large aperture scintillometer (LAS) site. The results illustrate that the terrestrial daily LE can be estimated with squared correlation coefficients (R{2}) of 0.77-0.84 (p < 0.01) and root-mean-square error (RMSE) values of 17.9-21.5 W/m2 among all three sites. The site-calibrated statistics are improved by 0.14-0.25 for R{2} and decreased by 4.2-8.3 W/m2 for RMSE as compared to the commonly used universal PT-JPL model. A satisfactory performance is achieved across all experimental conditions, encouraging the application of the NRSD model to estimate LE for other broad regions.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Geoscience and Remote Sensing-
dc.subjectChinese GF-1-
dc.subjectEvapotranspiration-
dc.subjectNIR-red spectral space-
dc.subjectperpendicular soil moisture index (PSI)-
dc.subjectperpendicular vegetation index (PVI)-
dc.titleA Novel NIR-Red Spectral Domain Evapotranspiration Model from the Chinese GF-1 Satellite: Application to the Huailai Agricultural Region of China-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TGRS.2020.3020125-
dc.identifier.scopuseid_2-s2.0-85102284945-
dc.identifier.volume59-
dc.identifier.issue5-
dc.identifier.spage4105-
dc.identifier.epage4119-
dc.identifier.eissn1558-0644-
dc.identifier.isiWOS:000642096400035-

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