Spatial estimation of surface soil texture using remote sensing data(Soil physics)
スポンサーリンク
概要
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Understanding the spatial distribution and variability of soil texture is essential for land use planning and other activities related to agricultural management and environmental protection. This study was conducted to evaluate Landsat Enhanced Thematic Mapper (ETM) remote sensing data as auxiliary variables for spatial estimation of surface soil texture using a limited number of soil samples taken from a site located in the city of Pingdu, Shandong Province, China. Three methods of evaluating variability in surface soil texture were evaluated: (1) multiple stepwise regression (MSR) based on the relationship between surface soil sand, silt and clay contents and remote sensing data; (2) kriging of surface soil sand, silt and clay contents; (3) cokriging with remote sensing data. Correlation analysis showed that surface soil sand, silt and clay contents were significantly correlated with Landsat ETM digital number (DN) of six bands (Bands 1-5 and Band 7), and the DN of Band 7 explained most of the variability in soil sand, silt and clay contents. The DN of Band 7 was selected as auxiliary data for the estimation of surface soil texture. The cross-validation results indicated that both MSR and kriged estimates had low reliability due to the variations in landscape and the low-density sampling in the study area. Cokriging with remote sensing data significantly improves estimates of surface soil texture compared with MSR and kriging.
著者
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LIAO Kaihua
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences
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ZHU Qing
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences
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XU Shaohui
Department of Environmental Science, Qingdao University
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WU Jichun
Department of Hydrosciences, Nanjing University