Observations of the Impacts of Hong Kong International Airport on Water Quality from 1986 to 2022 Using Landsat Satellite

Wang, Zhengyi; Mao, Zhihua; Zhang, Longwei; Zhang, Xianliang; Yuan, Dapeng; Li, Youzhi; Wu, Zhongqiang; Huang, Haiqing; Zhu, Qiankun

doi:10.3390/rs15123146

Cited by 2 publications

(2 citation statements)

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“…The Landsat 8 OLI sensor added a coastal aerosol band and a panchromatic band with a spatial resolution of 15 m, and a cirrus cloud band based on the Landsat 5 TM sensor. The panchromatic band is primarily used to improve resolution [23]. The band ranges of Blue, Green, Red, and NIR bands are basically the same for both sensors.…”

Section: Satellite Data and Preprocessingmentioning

confidence: 99%

“…Ma et al [22] developed an algorithm based on an artificial neural network (ANN) to obtain TSS and Chl-a concentration characteristics in the PRE area from MODIS/Aqua data. Employing an algorithm based on a back propagation neural network (BPNN), Wang et al [23] explored the impact of suspended particulate matter, orthophosphate phosphorus, and dissolved inorganic nitrogen on surrounding waters during the construction of the Hong Kong International Airport. In addition to algorithms based on neural network technology, support vector machine regression (SVR) [24][25][26], random forest regression (RFR) [27,28], and XGBoost [29] algorithms have also been applied to establish water quality models.…”

Section: Introductionmentioning

confidence: 99%

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Monitoring Total Suspended Solids and Chlorophyll-a Concentrations in Turbid Waters: A Case Study of the Pearl River Estuary and Coast Using Machine Learning

Liu,

Qiu,

Feng

et al. 2023

Remote Sensing

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Total suspended solids (TSS) and chlorophyll-a (Chl-a) are critical water quality parameters. Focusing on the Pearl River Estuary and its coastal waters, this study compared the performance of XGBoost- and BPNN-based algorithms in estimating TSS and Chl-a levels. The XGBoost-based algorithm demonstrated better performance and was then used to estimate TSS and Chl-a in the Pearl River Estuary and coastal waters from 2000 to 2021. According to our results, TSS and Chl-a were relatively high mainly in the northwest and low in the southeast. Furthermore, values were high in spring and summer and low in fall and winter, with high values emerging near the estuary of the Pearl River. In summer, a band zone with high Chl-a was observed from south of Yamen to south of Hong Kong. In terms of trends, TSS and Chl-a concentrations in the area around the Hong Kong–Zhuhai–Macao Bridge tended to decrease from 2000 to 2021. As the construction of the bridge began, changes in water flow caused by the bridge piers and artificial islands were influenced, the change in the rate of TSS in the west area of the bridge was greater than 0, and the TSS in the upstream area of the west side changed from decreasing to increasing trends. Concerning Chl-a concentrations, the change in the rate in the downstream area of the west side of the bridge was greater than 0. The study may provide a helpful example for similar estuarine and coastal waters in other coastal areas.

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Section: Satellite Data and Preprocessingmentioning

confidence: 99%