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机构地区:[1]中国科学院南京土壤研究所,南京210008 [2]安徽工业大学建筑工程学院,马鞍山243002
出 处:《农业工程学报》2009年第7期148-152,共5页Transactions of the Chinese Society of Agricultural Engineering
基 金:中国科学院知识创新工程重要方向项目课题(kzcx2-yw-406-3/4);国家科技支撑计划课题(2006BAD05B02);国家高技术研究发展计划重点课题(2006AA100207);国家科技支撑计划课题(2006BAD05B04)
摘 要:针对目前黄淮海平原存在的土壤盐渍化问题,以河南省封丘县为研究区,利用遥感影像与磁感应电导率仪(EM38)在田间定位、定点测量,对研究区土壤盐分的空间变异性进行研究。利用Kriging、指数回归和回归-Kriging3种不同的方法对土壤盐分空间变异性进行分析。结果表明:土壤电导率在一定的区域范围内具有空间结构特征,符合指数模型分布,具有极强的空间自相关性。通过3种不同的方法对土壤盐分的空间变异性进行分析,结果表明Kriging法、指数回归法及回归-Kriging法在描述土壤盐分空间分布的总体趋势上相似,但指数回归法与回归-Kriging法对于盐分的分布表达更具体,更细致。综合运用多种数据源的方法,即遥感影像数据与EM38测量数据相结合,经典统计学与地统计学方法相结合的方法,能够提高土壤盐分空间预测的精度,结果表明研究区土壤盐分由北向南、自西向东有逐渐升高的趋势,具有明显的趋势效应。Taking into account the problem of soil salinization existing in Huanghuaihai plain at present,spatial variability of soil salinity was surveyed using remote sensing and the EM38(electromagnetic induction instruments)in Fengqiu county of Henan Province.Spatial variability of soil salinity was analyzed by three methods of Kriging,exponential regression and regression-Kriging.The results indicated that soil electrical conductivity had spatial structure characteristics in a certain region,which was in line with the exponential model distribution and had strong spatial autocorrelation.The trends of spatial variability of soil salinity were similar to each other by three methods,but the spatial distributions of soil salinity by index regression and regression-Kriging were more specific and thorough than that by Kriging interpolation.The integrated methods by adopting comprehensively multi data sources,namely integration of remote sensing image data and EM38 measuring data,and integration of exponential regression and regression-Kriging,could improve the spatial prediction precision of soil salinity and were more accurate than that only by Kriging interpolation,which showed that in the study area the distribution of soil salinization appeared a tendency of increasing from north to south and from west to east,and exhibited obvious trend effect.
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