DocumentCode :
410877
Title :
Retrieving the crop coefficient spatial distribution for cotton under different growth status with Landsat ETM+ image
Author :
Shuhua, Qi ; Changyao, Wang ; Zheng, Niu ; Chunyan, Yan
Author_Institution :
Inst. of Remote Sensing Applications, Chinese Acad. of Sci., Beijing, China
Volume :
4
fYear :
2003
fDate :
21-25 July 2003
Firstpage :
2212
Abstract :
Crop water requirement was important in the irrigation scheduling. The crop coefficient is a parameter for estimating crop water requirement by multiplying with the reference crop evapotranspiration. Crop coefficient used to be approximated by crop developing days. The method must have some defect because the crop coefficient is a parameter related to crop status, climate condition and surface albedo. All the factors relating to the crop coefficient are spatially diverse and remote sensing has advantages in obtaining the distributing parameters for vegetation and climate factor. Based on the Penman-Monteith equation, the reference crop evapotranspiration and potential evapotranspiration for cotton under different growth status was estimated with measured meteorological data, then the crop coefficient for cotton was retrieved from a Landsat ETM+ image. And the sensitivity of crop coefficient to the influence factors were analysed. The results showed that the crop coefficient retrieved from the ETM+ image was greater than those suggested by FAO and the crop coefficient was influenced and decided by NDVI that represents crop growth status, while surface albedo that has a very larger variance for the sparse vegetation cover has scarcely any effect on crop coefficient and the climate factors has litter influence on crop coefficient too; with the vegetation cover fraction developing, the climate factor has a much more positive effect on the crop coefficient.
Keywords :
cotton; crops; image retrieval; transpiration; vegetation mapping; Landsat enhanced Thematic Mapper image; Penman-Monteith equation; climate factor; cotton; crop coefficient spatial distribution; crop water; irrigation scheduling; normalized difference vegetation index; potential evapotranspiration; reference crop evapotranspiration; remote sensing; sparse vegetation cover; spatial diversification; vegetation factor; Cotton; Crops; Differential equations; Image retrieval; Irrigation; Meteorology; Parameter estimation; Remote sensing; Satellites; Vegetation mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International
Print_ISBN :
0-7803-7929-2
Type :
conf
DOI :
10.1109/IGARSS.2003.1294392
Filename :
1294392
Link To Document :
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