采样密度对土壤全氮随机森林模拟精度的响应

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中图分类号：S158 文献标志码：A 文章编号：1672-1098（2025）02-0042-09

引文格式：，等.采样密度对土壤全氮随机森林模拟精度的响应[J].安徽理工大学学报（自然科学版），2025，45（2） ：42-50.

Impact of Sampling Density on the Spatial Prediction Accuracy of Soil Total Nitrogen by Using Random Forest LI Xiaopeng1 ，ZHANG Shiwen' ，LIU Xiaoxue²，YAN Fang² KONG Chenchen1 ，JIAO Yangqing' ，ZHAO Baoyu

（1.SchoolofEarthandEnvironmnt，AnhuiUniversityofSienceandTechnology，HuainanAnhui220o1，China;2.FengtaiAgriculturalProductsQualityandSafetyIspectioStation，BeijingOoo，China;3.DepartmentofFarmlandInformationMaagee， Beijing Cultivated Land Construction and Protection Center，Beijing 1OOo2O，China） Abstract：Objective A reasonable sampling densityfor regional soil total nitrogen（STN） investigation enables accurate assessment of STN content dynamics whileoptimizing resource eficiency. Understandingsampling density on spatial simulation accuracy is therefore crucial.Methods Byutilizing soil sampledata from Fangshan District，Beijing，optimal sampling numbers were calculated and diferent density gradients were established.Topographicand vegetation variables were incorporatedas auxiliary factors in random forest modeling to predictSTNspatial distribution and evaluate sampling density impacts on simulation accuracy.Results Sampling density determination solely by Cochran's formula （neglecting spatial heterogeneity）resulted in low STN predictionaccuracy.Semivariogram analysis revealed moderate spatial autocorrelation of STN. Spatial distribution exhibited a west-high-eastlow patern，aligning with elevation trends. Increased sampling density significantly enhanced random forest accuracy until reaching 37O samples，beyond which accuracy stabilized. Maximum R2（0.82） and minimum RMSE （204号 （0.15g/kg） ） occurred at 497 samples.Conclusion The optimal sampling density for STN prediction in Fangshan District ranges between 222 and 37Osamples，balancing accuracy and cost-effctiveness.This finding providesguidance for regional soil surveys.

Key Words ： soil total nitrogen ;sampling density ;spatial interpolation;random forest ;interpolation accuracy

土壤全氮（Soil total nitrogen，STN）是决定土壤质量的主要因素，也是衡量土壤肥力的重要指标，由于人为活动[1]、成土因素[2]和地形因子[3]等环境因子的影响，STN通常表现出显著的变异，准确估计STN的空间分布可为农业管理提供理论支持和指导[4]。（剩余7927字）