DocumentCode :
2607427
Title :
Study on retrieval methods of soil water content in vegetation covering areas based on multi-source remote sensing data
Author :
Ying, Zhang
Author_Institution :
Coll. of Tourism, Xinjiang Finance & Econ. Univ., Urumqi, China
Volume :
2
fYear :
2010
fDate :
28-31 Aug. 2010
Firstpage :
369
Lastpage :
372
Abstract :
Fusion image of SAR (Radar-sat image) combined with visible spectrum remote sensing image (TM image) is used to extract soil and vegetation water content in arid oasis taking the delta oasis of Weigan and Kuqa rivers in Xinjiang as the study area. Based on the Normalized Difference Moisture Index extracted from homochromous visible spectrum remote sensing data, this thesis utilizes “water-cloud model” to wipe off vegetation influence from total backscattering coefficient of radar data and sets up the relationship between soil backscattering coefficient and soil moisture. The Result shows that in arid and semi-arid area where the main crops are cotton and corn, the combination of C- band HH polarization radar data with visible image performs well in the study of removing vegetation influence while retrieving soil water content in medium vegetated areas.
Keywords :
geophysical image processing; radar polarimetry; remote sensing by radar; rivers; soil; synthetic aperture radar; vegetation mapping; C-band HH polarization radar data; China; Kuqa River; Normalized Difference Moisture Index; SAR; TM image; Weigan River; Xinjiang; arid oasis; corn; cotton; crops; delta oasis; fusion image; homochromous visible spectrum remote sensing data; multisource remote sensing data; radar-sat image; semiarid area; soil backscattering coefficient; soil moisture; soil water content; total backscattering coefficient; vegetation covering areas; vegetation water content; visible spectrum remote sensing image; water-cloud model; Atmospheric measurements; Atmospheric modeling; MODIS; Monitoring; Radar measurements; Sensors; Water resources; backscattering coefficient; remote sensing; soil moisture; vegetation; water-cloud model;
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.2010.5604231
Filename :
5604231
Link To Document :
بازگشت