湖泊科学2026，Vol.38Issue(3)：980-993,中插2-中插3,16.DOI:10.18307/2026.0316
基于便携式高光谱近感快速监测内陆水体叶绿素a浓度
Rapid monitoring of chlorophyll-a concentration in inland water bodies using a portable proximal sensing technology
摘要
Abstract
Phytoplankton chlorophyll-a(Chl.a)concentration is a key indicator for assessing water eutrophication status.Conven-tional monitoring approaches face significant limitations:laboratory analyses are time-consuming and labor-intensive,while in situ sensors are susceptible to biofouling,low accuracy,and high maintenance costs.Traditional satellite remote sensing is also unsuita-ble for high-precision,real-time monitoring due to challenges such as atmospheric correction errors,technical complexity,and low temporal resolution.The emergence of hyperspectral proximal sensing technology offers a promising alternative for improving Chl.a monitoring efficiency.In this study,we utilized a novel portable hyperspectral proximal sensing device to collect 533 synchronized in situ Chl.a measurements across eight lakes,reservoirs,and rivers between 2021 and 2024.We developed and compared high-accuracy Chl.a inversion models using both linear regression and machine learning methods.Among the evaluated algorithms—lin-ear regression,random forest,extreme gradient boosting(XGBoost),and support vector machine—the XGBoost-based model ex-hibited the best performance(R2=0.87,RMSE=6.02 μg/L,MAE=3.98 μg/L).This approach enables simultaneous spectral acquisition and Chl.a estimation,streamlining field monitoring workflows,lowering technical barriers,and significantly improving operational efficiency.关键词
便携式高光谱/近感监测/叶绿素a/内陆水体/机器学习Key words
Portable hyperspectral/proximal sensing/chlorophyll-a/inland waters/machine learning引用本文复制引用
骆夏杨,李娜,张运林,郭宇龙,马宗伟..基于便携式高光谱近感快速监测内陆水体叶绿素a浓度[J].湖泊科学,2026,38(3):980-993,中插2-中插3,16.基金项目
江苏省生态环境科研项目(2023003)、江苏省重点研发计划(产业前瞻与关键核心技术)项目(BE2022152)、国家重点研发计划项目(2022YFC3204100)、江苏省卓越博士后计划项目(2024ZB312)和国家自然科学基金项目(42401479)联合资助. （2023003）
