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为了解决土壤采样中精度与经济性的平衡问题,利用计算机模拟采样研究了规则网格土壤采样时合理的采样点密度。首先构造了一个数学扩散模型,设置2~4个种子在一个100×100网格(1×1单位)的不同地方,根据扩散模型进行扩散和叠加,生成模拟的土壤属性分布地图,其结果可很好地模拟某些土壤属性的分布。利用计算机按照不同的网格单元尺寸(如3×3,5×5,7×7等)进行采样,之后利用采样值进行IDW插值处理,将数据点恢复到原始的10000个,并把插值结果与原始值进行比较即可得到采样误差。研究结果表明,当采样网格单元尺寸为属性地图输出栅格单元尺寸的11倍和17倍时,相对采样误差分别为10%和15%。合理的采样密度可以根据允许的采样误差及要求的属性地图输出栅格单元尺寸而定。
In order to solve the problem of the balance between accuracy and economy in soil sampling, the reasonable sampling point density of regular grid soil sampling was studied by computer simulation sampling. First, a mathematical diffusion model is constructed, in which 2 to 4 seeds are set up in different places with 100 × 100 grids (1 × 1 units). Diffusion models are used to diffuse and superimpose them to generate simulated soil attribute distribution maps. Well simulates the distribution of some soil properties. Using a computer according to the different grid cell size (such as 3 × 3, 5 × 5, 7 × 7, etc.) for sampling, then use the sample value IDW interpolation, the data points back to the original 10000, and the interpolation results Compare with the original value to get the sampling error. The results show that the relative sampling errors are 10% and 15% respectively when the sampling grid unit size is 11 times and 17 times the output grid unit size. Reasonable sampling density can be based on the allowable sampling error and the required attribute map output raster cell size.