File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Validation of global land surface satellite (GLASS) fractional vegetation cover product from MODIS data in an agricultural region

TitleValidation of global land surface satellite (GLASS) fractional vegetation cover product from MODIS data in an agricultural region
Authors
Issue Date2018
Citation
Remote Sensing Letters, 2018, v. 9, n. 9, p. 847-856 How to Cite?
AbstractFractional vegetation cover (FVC) is an important parameter for describing the land surface vegetation conditions and widely used for land surface process simulations and global change studies. Global FVC products are mainly derived from satellite data and several global FVC products have been generated. Validation of the satellite FVC products is important before they can be applied. The objective of this study is to validate the newly generated Global LAnd Surface Satellite (GLASS) FVC product based on the time series of field FVC measurements in an agriculture region in the Heihe Basin of Northwest China. The high spatial resolution remotely sensed Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Compact Airborne Imaging Spectrometer (CASI) data were used to upscale the ground FVC measurements to validate the GLASS FVC product at 0.5 km spatial resolution. The results indicated that the GLASS FVC was highly accurate with the coefficient of determination (R2) of 0.86 and root-mean-square error (RMSE) of 0.087. Furthermore, the time series FVC profiles were consistent with the crop growing characteristics. It can be a reliable FVC product for agricultural applications.
Persistent Identifierhttp://hdl.handle.net/10722/321810
ISSN
2023 Impact Factor: 1.4
2023 SCImago Journal Rankings: 0.458
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorJia, Kun-
dc.contributor.authorLiang, Shunlin-
dc.contributor.authorWei, Xiangqin-
dc.contributor.authorYao, Yunjun-
dc.contributor.authorYang, Linqing-
dc.contributor.authorZhang, Xiaotong-
dc.contributor.authorLiu, Duanyang-
dc.date.accessioned2022-11-03T02:21:35Z-
dc.date.available2022-11-03T02:21:35Z-
dc.date.issued2018-
dc.identifier.citationRemote Sensing Letters, 2018, v. 9, n. 9, p. 847-856-
dc.identifier.issn2150-704X-
dc.identifier.urihttp://hdl.handle.net/10722/321810-
dc.description.abstractFractional vegetation cover (FVC) is an important parameter for describing the land surface vegetation conditions and widely used for land surface process simulations and global change studies. Global FVC products are mainly derived from satellite data and several global FVC products have been generated. Validation of the satellite FVC products is important before they can be applied. The objective of this study is to validate the newly generated Global LAnd Surface Satellite (GLASS) FVC product based on the time series of field FVC measurements in an agriculture region in the Heihe Basin of Northwest China. The high spatial resolution remotely sensed Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Compact Airborne Imaging Spectrometer (CASI) data were used to upscale the ground FVC measurements to validate the GLASS FVC product at 0.5 km spatial resolution. The results indicated that the GLASS FVC was highly accurate with the coefficient of determination (R2) of 0.86 and root-mean-square error (RMSE) of 0.087. Furthermore, the time series FVC profiles were consistent with the crop growing characteristics. It can be a reliable FVC product for agricultural applications.-
dc.languageeng-
dc.relation.ispartofRemote Sensing Letters-
dc.titleValidation of global land surface satellite (GLASS) fractional vegetation cover product from MODIS data in an agricultural region-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/2150704X.2018.1484958-
dc.identifier.scopuseid_2-s2.0-85054753787-
dc.identifier.volume9-
dc.identifier.issue9-
dc.identifier.spage847-
dc.identifier.epage856-
dc.identifier.eissn2150-7058-
dc.identifier.isiWOS:000438144500001-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats