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Article: A direct algorithm for estimating land surface broadband albedos from MODIS imagery

TitleA direct algorithm for estimating land surface broadband albedos from MODIS imagery
Authors
KeywordsBroadband albedo
Land surface
MODIS
Multi-spectral imagery
Remote sensing
Issue Date2003
Citation
IEEE Transactions on Geoscience and Remote Sensing, 2003, v. 41, n. 1, p. 136-145 How to Cite?
AbstractLand surface albedo is a critical variable needed in land surface modeling. The conventional methods for estimating broadband albedos rely on a series of steps in the processing chain, including atmospheric correction, surface angular modeling, and narrowband-to-broadband albedo conversions. Unfortunately, errors associated with each procedure may be accumulated and significantly impact the accuracy of the final albedo products. In an earlier study, we developed a new direct procedure that links the top-of-atmosphere spectral albedos with land surface broadband albedos without performing atmospheric correction and other processes. In this paper, this method is further improved in several aspects and implemented using actual Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Several case studies indicated that this new method can predict land surface broadband albedos very accurately and eliminate aerosol effects effectively. It is very promising for global applications and is particularly suitable for nonvegetated land surfaces. Note that a Lambertian surface has been assumed in the radiative transfer simulation in this paper as a first-order approximation; this assumption can be easily removed as long as a global bidirectional reflectance distribution function climatology is available.
Persistent Identifierhttp://hdl.handle.net/10722/321269
ISSN
2023 Impact Factor: 7.5
2023 SCImago Journal Rankings: 2.403
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLiang, Shunlin-
dc.date.accessioned2022-11-03T02:17:46Z-
dc.date.available2022-11-03T02:17:46Z-
dc.date.issued2003-
dc.identifier.citationIEEE Transactions on Geoscience and Remote Sensing, 2003, v. 41, n. 1, p. 136-145-
dc.identifier.issn0196-2892-
dc.identifier.urihttp://hdl.handle.net/10722/321269-
dc.description.abstractLand surface albedo is a critical variable needed in land surface modeling. The conventional methods for estimating broadband albedos rely on a series of steps in the processing chain, including atmospheric correction, surface angular modeling, and narrowband-to-broadband albedo conversions. Unfortunately, errors associated with each procedure may be accumulated and significantly impact the accuracy of the final albedo products. In an earlier study, we developed a new direct procedure that links the top-of-atmosphere spectral albedos with land surface broadband albedos without performing atmospheric correction and other processes. In this paper, this method is further improved in several aspects and implemented using actual Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Several case studies indicated that this new method can predict land surface broadband albedos very accurately and eliminate aerosol effects effectively. It is very promising for global applications and is particularly suitable for nonvegetated land surfaces. Note that a Lambertian surface has been assumed in the radiative transfer simulation in this paper as a first-order approximation; this assumption can be easily removed as long as a global bidirectional reflectance distribution function climatology is available.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Geoscience and Remote Sensing-
dc.subjectBroadband albedo-
dc.subjectLand surface-
dc.subjectMODIS-
dc.subjectMulti-spectral imagery-
dc.subjectRemote sensing-
dc.titleA direct algorithm for estimating land surface broadband albedos from MODIS imagery-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TGRS.2002.807751-
dc.identifier.scopuseid_2-s2.0-0037243198-
dc.identifier.volume41-
dc.identifier.issue1-
dc.identifier.spage136-
dc.identifier.epage145-
dc.identifier.isiWOS:000181468200014-

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