Spatial Prediction of Soil Organic Matter Content Using Cokriging with Remotely Sensed Data

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	Spatial Prediction of Soil Organic Matter Content Using Cokriging with Remotely Sensed Data
	Wu, Chunfa ; Wu, Jiaping ; Luo, Yongming ; Zhang, Limin ; DeGloria, Stephen D.
发表期刊	SOIL SCIENCE SOCIETY OF AMERICA JOURNAL
ISSN	0361-5995
	2009
卷号	73 期号:4 页码:1202-1208
关键词	Multivariate Geostatistical Analysis Landsat Thematic Mapper Spectral Band Selection Surface Carbon Moisture Sequestration Salinity Evaluate Terrain
产权排序	Zhejiang Univ, Dep Nat Resources & Environ; Chinese Acad Sci, Inst Soil Sci, Key Lab Soil Environm & Pollut Remediat; Haining Agr Extens Serv; Cornell Univ, Dep Crop & Soil Sci
通讯作者	Wu, CF, Chinese Acad Sci, Yantai Inst Coastal Zone Res Sustainable Dev, Yantai 264003, Peoples R China
作者部门	滨海湿地实验室
英文摘要	Accurately measuring soil organic matter content (SOM) in paddy fields is important because SOM is one of the key soil properties controlling nutrient budgets in agricultural production systems. Estimation of this soil property at an acceptable level of accuracy is important; especially in the case when SOM exhibits strong spatial dependence and its measurement is a time- and labor-consuming procedure. This study was conducted to evaluate and compare spatial estimation by kriging and cokriging with remotely sensed data to predict SOM using limited available data for a 367-km(2) study area in Haining City, Zhejiang Province, China. Measured SOM ranged from 5.7 to 40.4 g kg(-1), with a mean of 19.5 g kg(-1). Correlation analysis between the SOM content of 131 soil samples and the corresponding digital number (DN) of six bands (Band 1-5 and Band 7) of Landsat Enhanced Thematic Mapper (ETM) imagery showed that correlation between SOM and DN of Band 1 was the highest (r= -0.587). We used the DN of Band I as auxiliary data for the SOM prediction, and used descriptive statistics and the kriging standard deviation (STD) to compare the reliabilities of the predictions. We also used cross-validation to validate the SOM prediction. Results indicate that cokriging with remotely sensed data was superior to kriging in the case of limited available data and the moderately strong linear relationship between remotely sensed data and SOM content. Remotely sensed data such as Landsat ETM imagery have the potential as useful auxiliary variables for improving the precision and reliability of SOM prediction.
资助机构	Natural Science Foundation of China [40341010]; Department of Science and Technology, Zhejiang Province, China [2006C22026]; China Scholarship Council and the Zhejiang University
收录类别	sci
语种	英语
文献类型	期刊论文
条目标识符	http://ir.yic.ac.cn/handle/133337/3413
专题	中国科学院海岸带环境过程与生态修复重点实验室_滨海湿地实验室
推荐引用方式 GB/T 7714	Wu, Chunfa,Wu, Jiaping,Luo, Yongming,et al. Spatial Prediction of Soil Organic Matter Content Using Cokriging with Remotely Sensed Data[J]. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL,2009,73(4):1202-1208.
APA	Wu, Chunfa,Wu, Jiaping,Luo, Yongming,Zhang, Limin,&DeGloria, Stephen D..(2009).Spatial Prediction of Soil Organic Matter Content Using Cokriging with Remotely Sensed Data.SOIL SCIENCE SOCIETY OF AMERICA JOURNAL,73(4),1202-1208.
MLA	Wu, Chunfa,et al."Spatial Prediction of Soil Organic Matter Content Using Cokriging with Remotely Sensed Data".SOIL SCIENCE SOCIETY OF AMERICA JOURNAL 73.4(2009):1202-1208.

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