农业资源与环境学报2024，Vol.41Issue(4)：744-756,13.DOI:10.13254/j.jare.2023.0347
基于机器学习的数字土壤制图研究进展
Advances in digital soil mapping based on machine learning
摘要
Abstract
Digital soil mapping can facilitate acquiring soil information efficiently and precisely.In recent years,owing to the rapid development of computer disciplines and widespread recognition of soil-landscape models,digital soil modeling using machine learning has become a mainstream idea to provide new models for soil spatial distribution interpretation.These models differ from traditional mapping techniques such as geostatistics,expert knowledge,and individual representation.This study reviews the recent findings in the field of digital soil mapping nationally and internationally,and provides a complete and systematic description of digital soil mapping from three perspectives:basic theory,mapping method and outlook of soil mapping using machine learning technology,and digital soil mapping methods including the selection of feature information,selection of mapping models,and accuracy verification of soil maps.Finally,future research directions of digital soil mapping are discussed to provide reference for comprehensive,real-time,and accurate acquisition of spatial distribution of soil information.关键词
数字土壤制图/机器学习/环境协同变量/预测模型/精度验证Key words
digital soil mapping/machine learning/environmental covariate/predictive model/accuracy validation分类
农业科技引用本文复制引用
梅帅,童童,应纯洋,汪甜甜,章梅,汤萌萌,蔡天培,马友华,王强..基于机器学习的数字土壤制图研究进展[J].农业资源与环境学报,2024,41(4):744-756,13.基金项目
安徽省科技重大专项(202003a06020002) Major Science and Technology Project of Anhui Province(202003a06020002) （202003a06020002）
