DocumentCode :
144237
Title :
Exploring various spectral regions for estimating chlorophyll from ASD leaf reflectance using prospect radiative transfer model
Author :
Cho, Moses Azong ; Ramoelo, Abel ; Skidmore, Andrew
Author_Institution :
Earth Obs., Natural Resources & Environ., Council for Sci. & Ind. Res. (CSIR), Pretoria, South Africa
fYear :
2014
fDate :
13-18 July 2014
Firstpage :
4754
Lastpage :
4757
Abstract :
The performance of PROSPECT-5 radiative transfer model for predicting leaf chlorophyll from reflectance measurements made with the Analytical Spectral Device (ASD) spectrometer was investigated using numerical inversion techniques. The reflectance data of various spectral regions in the visible to shortwave infrared (SWIR) were assessed i.e. the full range (400-2500 nm), VNIR (400-1060 nm), visible (400-700 nm), red (600-700 nm), red-red edge (600-760 nm) and red-edge (670-760 nm). Among the spectral regions, the red-edge region yielded the lowest root mean square error of prediction (RMSEP =10.3 μg/cm2) for a variety of plants including crops and wild plants (n = 463). It is therefore recommended that inversion of radiative transfer models to retrieve leaf chlorophyll content be limited to the red-edge region.
Keywords :
radiative transfer; vegetation; ASD leaf reflectance chlorophyll estimation; ASD spectrometer; Analytical Spectral Device spectrometer; PROSPECT-5 radiative transfer model performance; RMSEP; SWIR; VNIR region; crop; leaf chlorophyll content retrieval; leaf chlorophyll predictinon; lowest root mean square prediction error; numerical inversion technique; plant variety; radiative transfer model inversion; red-red edge region; reflectance measurement; shortwave infrared; spectral region exploration; spectral region reflectance data; visible infrared; visible region; wild plant; Artificial neural networks; Optical reflection; Optical sensors; Reflectivity; Remote sensing; Variable speed drives; Vegetation; Analytical Spectral Device (ASD); PROSPECT-5; Radiative transfer model; leaf chlorophyll;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
Type :
conf
DOI :
10.1109/IGARSS.2014.6947556
Filename :
6947556
Link To Document :
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