Using coastal waters of Hong Kong as the study area, this study utilized GEE to (i) query and pre-process all Sentinel-2 observations that coincided with in situ measurements (ii) extract the spectra to develop empirical models for water quality parameters using artificial neural networks and (iii) visualize the results using spatial distribution maps, time-series charts and an online application. While remote sensing data such as Sentinel-2 satellite imagery routinely provide high-resolution observations for time-series analysis, the cloud-based Google Earth Engine (GEE) platform supports simple image retrieval and large-scale processing. 2Institute of Future Cities, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, ChinaĬontinuous monitoring of coastal water qualities is critical for water resource management and marine ecosystem sustainability.1Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
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