农业资源与环境学报2026，Vol.43Issue(5)：1147-1154,8.DOI:10.13254/j.jare.2025.0483
基于高分遥感和随机森林算法的澄迈县热带土壤肥力综合评价
Comprehensive evaluation of tropical soil fertility in Chengmai County based on high resolution remote sensing and random forest
摘要
Abstract
To explore the random forest on the comprehensive evaluation of soil fertility,a study was conducted in Chengmai County.PCA method and K-means clustering algorithm were adopted to determine the weights of each soil fertility index.After calculating the remote sensing indices related to soil fertility,the Pearson correlation analysis method,LASSO,GBDT method and VIF were used to feature screening.19 independent remote sensing characteristic parameters related to soil fertility were obtained.Finally,a random forest model based on remote sensing characteristic parameters was established.Compared with the EBK method,the model trained by random forest was significantly improved in prediction accuracy,with R2=0.591 7(an increase of 24.1%),RMSE=0.110 5 and MAE=0.085 1.The results showed that there was obvious spatial heterogeneity in soil fertility in Chengmai County,the average soil fertility grade in Ruixi Town and Qiaotou Town was higher.In terms of soil type,paddy soil had the highest average soil fertility grade,followed by fluvial soil and aeolian sandy soil,while stony soil and brick red soil had the lowest average grade.Our results indicate that random forest model incorporating multiple topographic indices based on high resolution remote sensing may effectively improve the efficiency and prediction accuracy,and are conducive to analyzing the distribution of soil fertility at the spatial scale of counties.关键词
土壤肥力/高分遥感/随机森林/耕地/澄迈县Key words
soil fertility/high resolution remote sensing/random forest/cultivated land/Chengmai County引用本文复制引用
李志豪,胡月明,杨颢,王璐,刘连胜..基于高分遥感和随机森林算法的澄迈县热带土壤肥力综合评价[J].农业资源与环境学报,2026,43(5):1147-1154,8.基金项目
国家重点研发计划项目(2023YFD1900105) （2023YFD1900105）
高分辨率对地观测系统国家科技重大专项(民用部分)科研项目(85-Y50G26-9001-22/23,83-Y50G23-9001-22/23) （民用部分）
