SOIL MOISTURE MONITORING OF COTTON FARMLAND WITH REMOTE SENSING IMAGE FROM LANDSAT 5 (TM)
文献类型: 外文期刊
作者: Xu, Xingang 1 ; Wang, Jihua 1 ; Huang, Wenjiang 1 ; Li, Cunjun 1 ; Zhao, Chunjiang 1 ;
作者机构: 1.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
关键词: soil moisture; Landsat 5 (TM); spectral feature space
期刊名称:INTELLIGENT AUTOMATION AND SOFT COMPUTING ( 影响因子:1.647; 五年影响因子:1.469 )
ISSN: 1079-8587
年卷期: 2010 年 16 卷 6 期
页码:
收录情况: SCI
摘要: Soil moisture is the most direct and important indicator for monitoring drought. In the paper, to estimate soil moisture of different depth in cotton farmland in Sinkiang Municipality, China, using the image from Landsat 5 (TM) with measured data in field makes the remote sensing models of monitoring moisture on basis of the distributional characteristics of soil moisture in spectral feature spaces with both Nir (near infrared)-Red and Nir-Swir (short wave infrared). As far as three different depths of 5cm, 10cm and 20cm are concerned, the result shows that whether for Nir-Red or Nir-Swir SFS, the two models gradually display better performance with depth increase, but for the same depth, the Nir-Swir model always has higher accuracy than Nir-Red. Lastly, soil moisture spatial map is successfully made by applying the Nir-Swir model and illustrates for cotton scientific irrigation and precise agriculture.
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