A Radiative Transfer Model for Patchy Landscapes Based on Stochastic Radiative Transfer Theory

Zeng, Y; Li, J; Liu, Q; Huete, AR; Xu, B; Yin, G; Fan, W; Ouyang, Y; Yan, K; Hao, D; Chen, M

A Radiative Transfer Model for Patchy Landscapes Based on Stochastic Radiative Transfer Theory

Zeng, Y Li, J Liu, Q Huete, AR Xu, B Yin, G Fan, W Ouyang, Y Yan, K Hao, D Chen, M

Permalink

Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Geoscience and Remote Sensing, 2020, 58, (4), pp. 2571-2589
Issue Date:: 2020-04-01

Closed Access

	Filename	Description	Size
	08931687.pdf	Published version	20.43 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Zeng, Y
dc.contributor.author	Li, J
dc.contributor.author	Liu, Q
dc.contributor.author	Huete, AR
dc.contributor.author	Xu, B
dc.contributor.author	Yin, G
dc.contributor.author	Fan, W
dc.contributor.author	Ouyang, Y
dc.contributor.author	Yan, K
dc.contributor.author	Hao, D
dc.contributor.author	Chen, M
dc.date.accessioned	2020-10-15T04:52:09Z
dc.date.available	2020-10-15T04:52:09Z
dc.date.issued	2020-04-01
dc.identifier.citation	IEEE Transactions on Geoscience and Remote Sensing, 2020, 58, (4), pp. 2571-2589
dc.identifier.issn	0196-2892
dc.identifier.issn	1558-0644
dc.identifier.uri	http://hdl.handle.net/10453/143257
dc.description.abstract	© 2019 IEEE. The availability of global high-resolution land cover maps provides promising a priori knowledge for characterizing subpixel heterogeneity and improving predictions of directional reflectance of coarse-resolution pixels. Due to mutual shadowing and sheltering effects between the adjacent forest and cropland patches, the spectral nonlinear mixing of patchy ecotones is significant, especially when the sun illuminates the ecotone from the forest side with high solar zenith angle. The spectral linear mixture (SLM) approach leads to overestimation of the bidirectional reflectance factor (BRF) in the red band in the principal plane (PP), with a maximum absolute error (MAE) of 0.0063 and a maximum relative error (MRE) of 52.5%, and to underestimation in the near-infrared band in PP with an MAE of 0.0940 and an MRE of 14.5%. In a scenario with randomly distributed boundary orientations, the overestimation of SLM increases with the degree of fragmentation and the view zenith angle. We propose a Radiative Transfer model for patchy ECotones (RTEC). which improves R2 from 0.61 to 0.94 in the red band of Landsat-8 directional reflectance at the validation site. The RTEC model provides an efficient and analytical approach for directional reflectance predictions over heterogeneous patchy landscapes at coarse resolution and will be used for biophysical parameter retrievals [e.g., the leaf area index (LAI)] in future applications.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation	Department of Innovation, Industry, Science & ResearchCSIRO - C013420
dc.relation.ispartof	IEEE Transactions on Geoscience and Remote Sensing
dc.relation.isbasedon	10.1109/TGRS.2019.2952377
dc.rights	© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	0404 Geophysics, 0906 Electrical and Electronic Engineering, 0909 Geomatic Engineering
dc.subject.classification	Geological & Geomatics Engineering
dc.title	A Radiative Transfer Model for Patchy Landscapes Based on Stochastic Radiative Transfer Theory
dc.type	Journal Article
utslib.citation.volume	58
utslib.for	0404 Geophysics
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	0909 Geomatic Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2020-10-15T04:51:42Z
pubs.issue	4
pubs.publication-status	Published
pubs.volume	58
utslib.citation.issue	4

Abstract:

© 2019 IEEE. The availability of global high-resolution land cover maps provides promising a priori knowledge for characterizing subpixel heterogeneity and improving predictions of directional reflectance of coarse-resolution pixels. Due to mutual shadowing and sheltering effects between the adjacent forest and cropland patches, the spectral nonlinear mixing of patchy ecotones is significant, especially when the sun illuminates the ecotone from the forest side with high solar zenith angle. The spectral linear mixture (SLM) approach leads to overestimation of the bidirectional reflectance factor (BRF) in the red band in the principal plane (PP), with a maximum absolute error (MAE) of 0.0063 and a maximum relative error (MRE) of 52.5%, and to underestimation in the near-infrared band in PP with an MAE of 0.0940 and an MRE of 14.5%. In a scenario with randomly distributed boundary orientations, the overestimation of SLM increases with the degree of fragmentation and the view zenith angle. We propose a Radiative Transfer model for patchy ECotones (RTEC). which improves R2 from 0.61 to 0.94 in the red band of Landsat-8 directional reflectance at the validation site. The RTEC model provides an efficient and analytical approach for directional reflectance predictions over heterogeneous patchy landscapes at coarse resolution and will be used for biophysical parameter retrievals [e.g., the leaf area index (LAI)] in future applications.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/143257