DocumentCode :
3310117
Title :
Retrieve soil moisture from mixed-pixels based on scale transformation using hyperspectral data
Author :
Wu, Daihui ; Yan, Binyan ; Cui, Yaokui ; Fan, Wenjie ; Xu, Xiru
Author_Institution :
Inst. of RS & GIS, Peking Univ., Beijing, China
fYear :
2010
fDate :
25-30 July 2010
Firstpage :
3875
Lastpage :
3878
Abstract :
Soil moisture is a key parameter for drought monitoring. Crops distribute so fragmentally in China that mixed pixels account for a large proportion in moderate and coarse resolution remote sensing images. The soil moisture retrieved from vegetation-soil mixed pixels is a very important problem for drought monitoring and ecological study. Focusing on vegetation-soil mixed pixels, a new method for retrieving soil moisture from hyperspectral data is provided based on scale transformation method. Yingke Oasis, Zhangye, Gansu province was selected as validation area. A Hyperion/EO-1 data acquired on Jul.15, 2008 was pre-processed and linearly interpolated to 180m and 1080m resolution images. Then a multi-scale image series was obtained. Using the above method, the soil moisture of pixels whose space resolution is 1080m were calculated. The retrieved results were verified by synchronized ground observation data. The results show that the proposed method is reliable.
Keywords :
geophysical image processing; hydrological techniques; hydrology; moisture measurement; rain; remote sensing; soil; spectral analysis; vegetation; AD 2008 07 15; Gansu province; Hyperion/EO-1 data; Yingke Oasis; Zhangye; coarse resolution remote sensing images; drought monitoring; ecological study; hyperspectral data; multiscale image series; scale transformation; soil moisture retrieval; space resolution; synchronized ground observation data; vegetation-soil mixed pixels; Mathematical model; Pixel; Reflectivity; Remote sensing; Soil moisture; Vegetation mapping; hyperspectral remote sensing; mixed pixels; scale transformation; soil moisture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location :
Honolulu, HI
ISSN :
2153-6996
Print_ISBN :
978-1-4244-9565-8
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2010.5650098
Filename :
5650098
Link To Document :
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