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dc.contributor.authorBishop, Michael P.
dc.contributor.authorYoung, Brennan W.
dc.contributor.authorColby, Jeffrey D.
dc.contributor.authorFurfaro, Roberto
dc.contributor.authorSchiassi, Enrico
dc.contributor.authorChi, Zhaohui
dc.date.accessioned2020-02-25T17:07:51Z
dc.date.available2020-02-25T17:07:51Z
dc.date.issued2019-11-20
dc.identifier.citationBishop, M.P.; Young, B.W.; Colby, J.D.; Furfaro, R.; Schiassi, E.; Chi, Z. Theoretical Evaluation of Anisotropic Reflectance Correction Approaches for Addressing Multi-Scale Topographic Effects on the Radiation-Transfer Cascade in Mountain Environments. Remote Sens. 2019, 11, 2728.en_US
dc.identifier.issn2072-4292
dc.identifier.doi10.3390/rs11232728
dc.identifier.urihttp://hdl.handle.net/10150/637509
dc.description.abstractResearch involving anisotropic-reflectance correction (ARC) of multispectral imagery to account for topographic effects has been ongoing for approximately 40 years. A large body of research has focused on evaluating empirical ARC methods, resulting in inconsistent results. Consequently, our research objective was to evaluate commonly used ARC methods using first-order radiation-transfer modeling to simulate ASTER multispectral imagery over Nanga Parbat, Himalaya. Specifically, we accounted for orbital dynamics, atmospheric absorption and scattering, direct- and diffuse-skylight irradiance, land cover structure, and surface biophysical variations to evaluate their effectiveness in reducing multi-scale topographic effects. Our results clearly reveal that the empirical methods we evaluated could not reasonably account for multi-scale topographic effects at Nanga Parbat. The magnitude of reflectance and the correlation structure of biophysical properties were not preserved in the topographically-corrected multispectral imagery. The CCOR and SCS+C methods were able to remove topographic effects, given the Lambertian assumption, although atmospheric correction was required, and we did not account for other primary and secondary topographic effects that are thought to significantly influence spectral variation in imagery acquired over mountains. Evaluation of structural-similarity index images revealed spatially variable results that are wavelength dependent. Collectively, our simulation and evaluation procedures strongly suggest that empirical ARC methods have significant limitations for addressing anisotropic reflectance caused by multi-scale topographic effects. Results indicate that atmospheric correction is essential, and most methods failed to adequately produce the appropriate magnitude and spatial variation of surface reflectance in corrected imagery. Results were also wavelength dependent, as topographic effects influence radiation-transfer components differently in different regions of the electromagnetic spectrum. Our results explain inconsistencies described in the literature, and indicate that numerical modeling efforts are required to better account for multi-scale topographic effects in various radiation-transfer components.en_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.rightsCopyright © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectmorphometric propertiesen_US
dc.subjectmountain environmentsen_US
dc.subjectmultispectral imageryen_US
dc.subjectNanga Parbat Himalayaen_US
dc.subjectradiation-transfer cascadeen_US
dc.subjectradiation-transfer parametersen_US
dc.subjectradiometric calibrationen_US
dc.subjecttopographic correctionen_US
dc.titleTheoretical Evaluation of Anisotropic Reflectance Correction Approaches for Addressing Multi-Scale Topographic Effects on the Radiation-Transfer Cascade in Mountain Environmentsen_US
dc.typeArticleen_US
dc.contributor.departmentUniv Arizona, Dept Syst & Ind Engnen_US
dc.identifier.journalREMOTE SENSINGen_US
dc.description.noteOpen access journalen_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal published versionen_US
dc.identifier.piirs11232728
dc.source.journaltitleRemote Sensing
dc.source.volume11
dc.source.issue23
dc.source.beginpage2728
refterms.dateFOA2020-02-25T17:07:51Z


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Copyright © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as Copyright © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).