A Review of Remote Sensing for Water Quality Retrieval: Progress and Challenges

Water pollution has become one of the most serious issues threatening water environments, as a resource and human health. The urgent effective measures rely on dynamic accurate quality monitoring large scale. Due to their temporal spatial advantages, remote sensing technologies have been widely used retrieve data. With development hyper-spectral sensors, unmanned aerial vehicles (UAV) artificial intelligence, there significant advancement in remotely sensed retrieval owing various data availabilities methodologies. This article presents application for retrieval, mainly discusses research progress terms sources modes. In particular, we summarize some algorithms several specific variables, including total suspended matter (TSM), chlorophyll-a (Chl–a), colored dissolved organic (CDOM), chemical oxygen demand (COD), nitrogen (TN) phosphorus (TP). We also discuss challenges atmospheric correction, resolution, model applicability domains spatial, complexity. Finally, propose possible solutions these challenges. review can provide detailed references future retrieval.