DocumentCode :
576725
Title :
A method of upscaling ground measurements of Leaf Area Index based on Taylor Series expansion Model
Author :
Yan Liu ; Jindi Wang ; Hongmin Zhou ; Huazhu Xue
Author_Institution :
State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
6483
Lastpage :
6486
Abstract :
The ground measurements of Leaf Area Index (LAI) are usually used to validate the LAI estimated using remote sensing observations. The main problem encountered in the validation is the scale mismatch between the sampling area of ground measurements and coarse-resolution image pixel, especially when those sampling area are not ideal homogenous. This study introduced a new approach of upscaling ground measurements to the coarse-resolution scale for the validation of LAI estimations. This upscaling method was based on the Taylor Series expansion Model (TSM). The high-resolution images were used to provide auxiliary information at the sub-pixel scale of coarse-resolution image pixel. The possible error associated with this method is derived from the neglection of the third- and higher-order TSM terms and the uncertainty of the empirical model. The upscaled ground measurements with upscaling error smaller than half of eigenaccuracy could be used for validation of LAI estimations with coarse resolution.
Keywords :
geophysical image processing; series (mathematics); vegetation; LAI; Taylor series expansion model; auxiliary information; coarse resolution image pixel; coarse resolution scale; empirical model uncertainty; ground measurement sampling area; ground measurement upscaling method; leaf area index; remote sensing observation validation; scale mismatch; Area measurement; Equations; Mathematical model; Measurement uncertainty; Remote sensing; Uncertainty; Vegetation mapping; LAI; Taylor Series expansion Model; upscaling; validation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6352737
Filename :
6352737
Link To Document :
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