基于空间模拟退火算法的最优土壤采样尺度选择研究

Study on Optimal Soil Sampling Scale Selection Based on Spatial Simulated Annealing Method

以研究区0.5 km×0.5 km(尺度a)网格的7050个样点为基础,分别得到1 km×1 km网格的1757个样点(尺度b),2 km×2 km网格的444个样点(尺度c),4 km×4 km网格的110个样点(尺度d),以土壤有机质(SOM)为目标属性,运用模拟退火算法对4种采样尺度的土壤样点进行优化选择,确定区域土壤调查的最优采样尺度。研究发现,通过模拟退火算法优化选择后,尺度a、b、c、d的最优样点数量分别为956、751、283和95个,优选的样点在空间上均匀分布。随着采样尺度的减小,采样点数量呈倍数增长,但对土壤属性的预测精度并没有相应比例的增加,且随着样点数量的增加,土壤属性预测精度的增加量逐渐减小。从样点数量与土壤属性预测精度综合来看,2 km×2 km的采样尺度是最优的土壤采样尺度。

Four sampling point layouts at different scales based on different grid sizes:scale a,7050 sampling points in 0.5 km×0.5 km;scale b,1757 sampling points in 1 km×1 km;scale c,444 sampling points in 2 km×2 km;scale d,110 sampling points in 4 km×4 km were set up.Then,the optimized selection of the original soil sampling points at the four sampling scales were conducted using the simulated annealing method,and the optimum sampling numbers of scales a,b,c and d were 956,751,283 and 95,respectively,and were uniformly distributed in the space.Relative to the decrease in the sampling scale,the number of sampling points increased multiplicatively,but the predicted accuracy of soil properties did not increase proportionately.With the increased sampling point number,the predicted accuracy of soil properties gradually decreased.Considering the number of samples and the predicted accuracy of soil properties,a sampling scale of 2 km×2 km is optimal for soil organic matter.