NDLI: Utility of an Image-Based Canopy Reflectance Modeling Tool for Remote Estimation of LAI and Leaf Chlorophyll Content in Crop Systems

Content Provider	IEEE Xplore Digital Library
Author	Houborg, R. Anderson, M.C.
Copyright Year	2008
Description	Author affiliation: USDA-ARS Hydrol. & Remote Sensing Lab., Beltsville, MD (Houborg, R.; Anderson, M.C.)
Abstract	Remotely sensed data in the reflective optical domain function as a unique cost-effective source for providing spatially and temporally distributed information on key biophysical and biochemical parameters of land surface vegetation. The challenging task of estimating leaf chlorophyll content $(C_{ab})$ and leaf area index (LAI) is here undertaken for crop systems in Maryland using a regularized canopy reflectance (REGFLEC) modeling tool, which couples leaf optics (PROSPECT), canopy reflectance (ACRM), and atmospheric radiative transfer (6SV1) models. Using 10-m resolution SPOT-5 imagery, REGFLEC effectuated robust retrievals of $C_{ab}$ and LAI for a diversity of agricultural fields characterized by a wide range in leaf chlorophyll and LAI levels with relative root-mean-square deviations on the order of 11% and 15%, respectively. REGFLEC is made entirely image-based by incorporating radiometric information from pixels belonging to the same land cover class during a LUT-based model inversion approach.
File Size	1460876
File Format	PDF
ISBN	9781424428076
DOI	10.1109/IGARSS.2008.4778947
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Reflectivity Crops Biomedical optical imaging Optical sensors Atmospheric modeling Land surface Vegetation mapping Electromagnetic coupling Optical coupling Image resolution
Content Type	Text
Resource Type	Article

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