河南水利与南水北调2025，Vol.54Issue(4)：81-83,3.
基于PSO-SVR的水体总氮遥感监测算法
Remote Sensing Monitoring Algorithm of Total Nitrogen in Water Based on PSO-SVR
刘向辉 1裘钧2
作者信息
- 1. 青海大学土木水利学院,青海 西宁 810016
- 2. 北京师范大学水科学研究院,北京 100875||青海大学省部共建三江源生态与高原农牧业国家重点实验室,青海 西宁 810016
- 折叠
摘要
Abstract
Traditional total nitrogen monitoring methods are difficult to meet the needs of a large range of high frequency due to their small coverage and low temporal resolution.In recent years,progress has been made in water quality inversion through remote sensing and machine learning,but studies on total nitrogen in high-altitude and complex terrain areas are still insufficient.Taking the Yellow River Basin in Qinghai Province as the research area,based on the national monitoring data and Sentinel-2 images,the total nitrogen remote sensing inversion was realized through SVR model optimized by PSO.The results show that the model has high accuracy and good stability,providing a new method for regional water quality monitoring and high-altitude water quality inversion.It is of great significance for water environment protection.关键词
遥感/水质/PSO-SVR/黄河源区/总氮Key words
remote sensing/water quality/PSO-SVR/source area of Yellow River/total nitrogen分类
天文与地球科学引用本文复制引用
刘向辉,裘钧..基于PSO-SVR的水体总氮遥感监测算法[J].河南水利与南水北调,2025,54(4):81-83,3.
