New approaches in multi-angular proximal sensing of vegetation: Accounting for spatial heterogeneity and diffuse radiation in directional reflectance distribution models

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• 作者：Javier Pacheco-Labrador^a ; ^{javier.pacheco@cchs.csic.es} ; M. Pilar Martí ; n^a ; ^{mpilar.martin@cchs.csic.es} ; David Riañ ; o^a ; ^b ; ^{david.riano@cchs.csic.es} ; ^{driano@ucdavis.edu} ; Thomas Hilker^c ; ¹ ; ^{T.Hilker@soton.ac.uk} ; Arnaud Carrara^d ; ^{arnaud@ceam.es}
• 关键词：BRDF ; HDRDF ; Diffuse radiation ; Un-mixing ; Automated proximal sensing ; AMSPEC-MED ; Unispec DC ; Savanna ; MODIS
• 刊名：Remote Sensing of Environment
• 出版年：2016
• 出版时间：15 December 2016
• 年：2016
• 卷：187
• 期：Complete
• 页码：447-457
• 全文大小：1545 K
• 卷排序：187

文摘

AMSPEC-MED automated multi-angular hyperspectral system set in tree-grass ecosystem Ecosystem 3-D and FOV ray casting models simulate heterogeneous sensor's observations. Diffuse radiation included in Reflectance Distribution Functions (RDF) improves model. The model achieves the unmixing of tree and grass hemispherical-directional RDFs. Comparison to MODIS BRDF product and hand held spectral data cast r2 ∈ [0.74, 0.88].