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Remote sensing applied to estimate lake clarity in China

Remote sensing could be an effective tool to monitor Secchi disk depth (SD) of inland waters by monitoring the water leaving radiance. Remote sensing derived water clarity has been reported in many regions with specific models established for different satellite overpasses concurrent with in situ measured SD, but national water clarity remained unknown in China.

A recent study led by Prof. Song from the Northeast Institute of Geography and Agroecology of the Chinese Academy of Sciences, quantified the water clarity for lakes >8 ha in China using Landsat OLI imagery data for the first time.

The researchers conducted SD in situ measurements of 500 lakes across China from April 2013 to September 2018. The results showed that the national water clarity was averaged to 176 cm in 2016 with large spatial variability due to the marked variation between turbid waters in the east plain area and clean water across the Tibet Plateau. Specifically, lakes in the northeastern (75 cm) and eastern (84 cm) China had low clarity due to shallow water depth combined with high suspended matter and algal abundance. Lakes in the Yungui Plateau (91 cm), Inner Mongolia and Xinjiang autonomous regions (114 cm) exhibited intermediate clarity, while lakes in the Tibet Plateau (294 cm) displayed the highest clarity.



Journal Remote Sensing combines the key points and needs of the international remote sensing industry in different periods and publishes the latest international scientific research achievements. It hopes to become an influential academic journal in the development of international remote sensing science and technology and personnel training.

The journal covers the basic theory, technology and application of remote sensing in resource and environmental fields such as agriculture, forestry, hydrology, mining, oceanography, surveying and mapping, disaster monitoring, geographic information system research, space positioning system (GPS) and others. We sincerely welcome everyone to submit papers to contribute!

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