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土壤质量研究几乎涵盖土壤研究的所有领域,土壤质量制图理论与方法是土壤质量研究的一项重要研究内容。该研究以北京市密云县为研究区,基于土壤质量评价最小数据集和指数和法计算的土壤质量指数,探究了在地学模型支持下区域土壤质量数字制图方法。研究设计了5种区域土壤质量数字制图方法,并比较了不同方法的空间数字制图精度。结果显示,目前广泛使用的基于参评指标空间插值结果的土壤质量数字制图方法精度最低、工序较繁琐,且无法反映研究区景观高度异质的特点;而基于计算后的土壤质量指数(soil quality index,SQI),借助于地统计学方法的土壤质量数字制图方法相对比较科学合理,其中又以基于计算后的SQI和回归克里格法预测效果最好,均方根误差最小,仅为0.01897,相对于基于参评指标空间插值结果的土壤质量数字制图方法,精度相对提高率最大,达到50%以上。综合考虑空间制图精度、工序的繁简程度,在该研究设计的5种方法中基于计算的SQI和回归克里格法最佳,该法避免了地统计插值在景观高度异质区的应用局限性,预测结果与实际最为相符。
Soil quality research covers almost all areas of soil research, soil quality mapping theory and method is an important study of soil quality research. Based on the minimum data set of soil quality assessment and the index of soil quality index calculated by the method of Miyun County in Beijing, the study explored the digital mapping method of regional soil quality with the support of geosciences model. Five kinds of regional soil quality digital mapping methods were researched and designed, and the spatial digital mapping accuracy of different methods was compared. The results show that the currently widely used method of soil quality digital mapping based on the results of spatial interpolation of reference indices has the lowest accuracy and the more complicated procedures and can not reflect the highly heterogeneous landscape characteristics of the study area. Based on the calculated soil quality index , SQI). The digital mapping method based on geostatistics is comparatively scientific and reasonable. Among them, the results based on the calculated SQI and the regression kriging method are the best, with the least square root mean square error of 0.01897, Compared with the digital mapping method of soil quality based on the spatial interpolation of the indexes, the accuracy improvement rate is the highest, reaching more than 50%. Considering the accuracy of space mapping and the simplification of the process, the SQI based on calculation and the regression kriging are the best in the five methods of this study. This method avoids the limitation of the application of geostatistical interpolation in the highly heterogeneous area Sexually, the forecast result is most in line with the actual situation.