NDLI: Correction of Reflectance Anisotropy Effects of Vegetation on Airborne Spectroscopy Data and Derived Products

Content Provider	IEEE Xplore Digital Library
Author	Weyermann, J. Damm, A. Kneubuhler, M. Schaepman, M.E.
Copyright Year	1980
Abstract	Directional effects in airborne imaging spectrometer (IS) data are mainly caused by anisotropic reflectance behavior of surfaces, commonly described by bi-directional reflectance distribution functions (BRDF). The radiometric and spectral accuracy of IS data is known to be highly influenced by such effects, which prevents consistent comparison of products. Several models were developed to approximate surface reflectance anisotropy for multi-angular observations. Few studies were carried out using such models for airborne flight lines where only a single observation is available for each ground location. In the present work, we quantified and corrected reflectance anisotropy on a single airborne HyMap flight line using a Ross-Li model. We stratified the surface in two vegetation structural types (different in vertical structuring) using spectral angle mapping, to generate a structure dependent set of angular observations. We then derived a suite of products [indices (structure insensitive pigment index, normalized difference vegetation index, simple ratio index, and anthocyanin reflectance index) and inversion-based (SAIL/PROSPECT-leaf area index, Cw, Cdm, Cab)] from corrected and uncorrected images. Non-parametric analysis of variance (Kruskal-Wallis test) showed throughout significant improvements in products from corrected images. Data correction resulting in airborne nadir BRDF adjusted reflectance (aNBAR) showed uncertainty reductions from 60 to 100% (p-value = 0.05) as compared to uncorrected and nadir observations. Using sparse IS data acquisitions, the use of fully parametrized BRDF models is limited. Our normalization scheme is straightforward and can be applied with illumination and observation geometry being the only a priori information. We recommend aNBAR generation to precede any higher level airborne IS product generation based on reflectance data.
Sponsorship	IEEE Geoscience and Remote Sensing Society IEEE URSI
Starting Page	616
Ending Page	627
Page Count	12
File Size	1324791
File Format	PDF
ISSN	01962892
Volume Number	52
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Anisotropic magnetoresistance Scattering Atmospheric modeling Vegetation mapping Kernel Uncertainty Indexes Ross–Li Airborne imaging spectroscopy bi-directional reflectance distribution functions (BRDF) directional effects HyMap pre-processing PROSPECT/SAIL reflectance anisotropy
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Electrical and Electronic Engineering

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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