Water Quality Variations in the Lower Yangtze River Based on GA-RF Model From GF-1, Landsat-8, and Sentinel-2 Images

IF 4.7 2区地球科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Pub Date : 2025-01-06 DOI:10.1109/JSTARS.2025.3526207

Wentao Hu;Shuanggen Jin;Yuanyuan Zhang

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引用次数: 0

Abstract

Total phosphorus (TP) and total nitrogen (TN) are critical water quality indicators in the Yangtze River and remote sensing techniques can inverse these parameters. However, current models suffer from shortcomings such as lower accuracy due to the fewer spectral bands available from a single satellite. In this article, GF-1, Landsat-8, and Sentinel-2 data are jointly used to develop a genetic algorithm-random forest (GA-RF) water quality inversion model weighted by the entropy method. These models are validated and applied to derive long-term time series of TP and TN in the lower Yangtze River from 2018 to 2023. The results indicate that the three-satellite GA-RF joint model shows the best estimation performance from the in-situ measurements: TP with MAE 0.0108 and RMSE 0.0132, and TN with MAE 0.32 and RMSE 0.40. From 2018 to 2023, the water quality shows an improved trend with TP decreasing by 8.91% and TN decreasing by 11.34% . The annual average TP shows a decreasing trend with 0.0017 mg/L per year, while TN shows a decreasing trend with 0.0557 mg/L per year. In terms of seasonal distribution, the highest values of TP and TN are mostly distributed in summer, and the lowest values are mostly distributed in winter. Spatially, both TP and TN increase from west to east. Furthermore, the effects of hydrometeorological factors on water quality are discussed as well as water environmental factors such as pH and NH3-N.

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来源期刊

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 地学-成像科学与照相技术

CiteScore

9.30

自引率

10.90%

发文量

563

审稿时长

4.7 months

期刊介绍： The IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing addresses the growing field of applications in Earth observations and remote sensing, and also provides a venue for the rapidly expanding special issues that are being sponsored by the IEEE Geosciences and Remote Sensing Society. The journal draws upon the experience of the highly successful “IEEE Transactions on Geoscience and Remote Sensing” and provide a complementary medium for the wide range of topics in applied earth observations. The ‘Applications’ areas encompasses the societal benefit areas of the Global Earth Observations Systems of Systems (GEOSS) program. Through deliberations over two years, ministers from 50 countries agreed to identify nine areas where Earth observation could positively impact the quality of life and health of their respective countries. Some of these are areas not traditionally addressed in the IEEE context. These include biodiversity, health and climate. Yet it is the skill sets of IEEE members, in areas such as observations, communications, computers, signal processing, standards and ocean engineering, that form the technical underpinnings of GEOSS. Thus, the Journal attracts a broad range of interests that serves both present members in new ways and expands the IEEE visibility into new areas.