基于耕地图斑数据的土壤有机质估测方法研究——以大兴区南部耕地为例

发布时间：2018-07-06 14:30

本文选题：耕地图斑 + 序贯高斯条件模拟　；参考：《中国农业大学学报》2017年11期

【摘要】：基于测土配方采样点调查数据和土地利用现状数据,构建常规耕地质量评价中的土壤有机质含量的面状数据;基于此,采用面克里格法和序贯高斯条件模拟法估测北京大兴区南部耕地土壤有机质含量,并采用验证图斑的点数据和面数据形式进行精度评价,进而探寻基于面数据的土壤有机质含量最优估测方法。结果表明,面克里格法和序贯高斯条件模拟法对研究区耕地土壤有机质空间分布的估测效果具有一致性,但序贯高斯条件模拟法的平滑作用较弱,且单次随机模拟的局部特征变化更突出;点验证和面验证的相关系数与一致性系数表明,面克里格法和序贯高斯条件模拟法可以用来估测耕地土壤有机质含量;在多次随机模拟和变异函数拟合准确性的综合作用下,序贯高斯条件模拟估测精度更高。
[Abstract]:Based on the survey data of soil formula sampling points and land use status data, the surface data of soil organic matter content in the quality evaluation of conventional cultivated land are constructed. The surface kriging method and sequential Gao Si condition simulation method were used to estimate the soil organic matter content in the southern part of Daxing district of Beijing. Furthermore, the optimal estimation method of soil organic matter content based on surface data was explored. The results showed that the effect of surface kriging method and sequential Gao Si condition simulation method on estimating the spatial distribution of soil organic matter in cultivated land in the study area was consistent, but the smoothing effect of sequential Gao Si condition simulation method was weak. The correlation coefficient and consistency coefficient of point verification and surface validation show that the surface kriging method and sequential Gao Si condition simulation can be used to estimate the soil organic matter content of cultivated land. Under the combined action of multiple random simulation and variogram fitting accuracy, sequential Gao Si condition simulation is more accurate.
【作者单位】：北京农业信息技术研究中心;湖南万源评估咨询有限公司;福建农林大学资源与环境学院;
【基金】：国家科技支撑计划课题(2013BAJ05B01)
【分类号】：S153.621

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