DocumentCode
2576240
Title
Retrieval of leaf area index, leaf chlorophyll content based on SLC model and CHRIS data
Author
Junlei Tan ; Mingguo Ma ; Yi Song ; Guanghui Huang
Author_Institution
Cold & Arid Regions Environ. & Eng. Res. Inst., Chinese Acad. of Sci., Lanzhou, China
Volume
2
fYear
2010
fDate
28-31 Aug. 2010
Firstpage
551
Lastpage
554
Abstract
Leaf area index (LAI) and leaf chlorophyll content (Cab) are two significant parameters that control physical and physiological processes in vegetation canopies. The hyper spectral data, CHRIS/PROBA, were used in this study. Simultaneous ground experiments for CHRIS were carried out in July 1, 2008 in Zhangye during experiment of the Watershed Airborne Telemetry Experimental Research (WATER). In this paper, Soil-Leaf-Canopy (SLC) canopy reflectance model was used to simulate spectral of canopy and inverted for vegetation variables. For inversion of this coupled model, the very fast simulated re-annealing algorithm was used as an inversion strategy of retrieval of LAI and Cab. The retrieval results were validated with field measurements of LAI and Cab. The root-mean-square error (RMSE) of LAI and Cab were 1.2614 and 14.82 μg/cm2 respectively. The verified result shows that the retrieval algorithm for vegetation parameters based on SLC and simulated annealing algorithm is credible.
Keywords
atmospheric boundary layer; vegetation mapping; AD 2008 07 01; CHRIS data; Cab; China; LAI; PROBA; SLC model; Soil-Leaf-Canopy canopy reflectance model; Watershed Airborne Telemetry Experimental Research; Zhangye; ground experiments; hyperspectral data; leaf area index; leaf chlorophyll content; reannealing algorithm; root-mean-square error; vegetation canopies; vegetation parameters; vegetation variables; Atmospheric modeling; Biological system modeling; Computational modeling; Reflectivity; Remote sensing; Soil; Vegetation mapping; CHRIS; LAI; Leaf Chorophyll Content; SLC Model; Simulated Annealing Algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing (IITA-GRS), 2010 Second IITA International Conference on
Conference_Location
Qingdao
Print_ISBN
978-1-4244-8514-7
Type
conf
DOI
10.1109/IITA-GRS.2010.5602344
Filename
5602344
Link To Document