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首页> 外文期刊>International Journal of Plant & Soil Science >Spatial Variability Analysis of Soil Properties Using Geospatial Technique in Katni District of Madhya Pradesh, India
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Spatial Variability Analysis of Soil Properties Using Geospatial Technique in Katni District of Madhya Pradesh, India

机译:基于地理空间技术的印度中央邦卡特尼地区土壤性质的空间变异性分析

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This study was conducted in Katni district of Madhya Pradesh India to map the spatial variability of major soil properties using geospatial technique. Surface soil samples of 505 locations (0-15 cm) were collected by random sampling strategy using GPS. Soil physico-chemical properties were measured in laboratory. In this paper we execute and compare the accuracy of various ordinary kriging methods. Spatial variability of soil physico-chemical properties was quantified through semi-variogram analysis and the relevant surface maps were prepared through ordinary kriging. Exponential model fits well with experimental semi-variogram of pH, OC, available N, P, K, S and Zn, where as in case of electric conductivity best fitted model was spherical. Coefficient of variation of soil properties showed large variability with greatest variation observed in Zn (140%) while EC, OC, N, P, and K has displayed moderate spatial variation whereas the smallest variation was in pH (14.16% ). In case of EC and P the goodness of prediction (G) had a negative value while N, P, K, pH, Zn and S shows positive value. The pH value in north-east part of the study area was alkaline and in the south-west portion of area was acidic in nature. Correlation coefficient between soil nutrients shows strong positive relationship between Nitrogen and organic carbon (r= 0.955). Cross validation of kriged map shows that spatial prediction of soil nutrients using semi-variogram parameters is better than assuming mean of observed value for any un-sampled location.
机译:这项研究是在印度中央邦的Katni区进行的,目的是使用地理空间技术绘制主要土壤属性的空间变异性。使用GPS通过随机抽样策略收集了505个位置(0-15厘米)的表层土壤样品。在实验室测量土壤理化性质。在本文中,我们执行并比较了各种普通克里金法的准确性。通过半变异函数分析定量分析土壤理化性质的空间变异性,并通过普通克里金法绘制相关的表面图。指数模型与pH,OC,可用的N,P,K,S和Zn的实验半变异图非常吻合,就电导率而言,最佳拟合模型为球形。土壤特性的变异系数显示出较大的变异性,其中锌的变异最大(140%),而EC,OC,N,P和K表现出中等的空间变异,而pH的变异最小(14.16%)。对于EC和P,预测优度(G)为负,而N,P,K,pH,Zn和S为正值。研究区东北部的pH值为碱性,而西南部则为酸性。土壤养分之间的相关系数显示出氮与有机碳之间的强正相关(r = 0.955)。克立格地图的交叉验证显示,使用半变异函数参数对土壤养分的空间预测要好于对任何未采样位置的观测值的均值。

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