Spatial Distribution Information Extraction of Soil Total Phosphorus in Huan River Basin Based on Regression Kriging Method and Sentinel 2B Remote Sensing Data
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摘要: 土壤总磷空间分布是准确掌握流域农业面源污染状况的关键，而遥感技术因其便利性在土壤面源污染调查中的潜力亟待探索。本文以澴河流域土壤总磷分布为例，分析了土壤总磷的光谱特性，发现总磷含量与土壤光谱反射率呈负相关，其中红外光谱（700~1800nm）表现更加明显；并以土壤总磷光谱计算数据作为环境辅助因子，取样点数据作为主要因素，运用回归克里格地统计方法成功提取了澴河流域土壤总磷空间分布信息，将结果与实测数据对比，其ME值为0.08，MAE值为0.48，RMSE值为0.69，预测精度较协同克里格和反距离权重法有明显提高。本方法既保留了地统计分析方法的精度，又具备处理高密度样本的能力，为土壤属性的空间插值提供了一种可行的获取方法。Abstract: Understanding the spatial distribution of soil total phosphorus in the Huan River basin is the key toaccurately grasp the agricultural non-point source pollution in the basin, while remote sensing is expected towork in the pollution as its efficiency.In this paper, the spectral characteristics of soil total phosphorus wereanalyzed to find out that the total phosphorus content was negatively correlated with soil reflectance spectrum, in which the infrared spectrum (700-1800nm) was more obvious.Taking the spectral calculation data of soil total phosphorus as the environmental auxiliary factor and the data of sampling points as the main elements, the regression Kriging statistical method was used to successfully extract the spatial distribution information of soil total phosphorus in the river basin. Compared the results with the measured data, the ME value is 0.08, MAE value is 0.48 and RMSE value is 0.69.The prediction accuracy of this method is significantly higher than that of the co-Kriging and inverse distance weighting method. This method not only matches the accuracy of the statistical analysis, but also be appropriate to deal with high-density samples, which is a feasible method for getting spatial interpolation of soil properties.
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Key words:
- total soil phosphorus /
- spatial distribution /
- regression Kriging /
- Huan River Basin
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