Abstract
Algal blooms in lakes have become a common global environmental problem. Nowadays, remote sensing is widely used to monitor algal blooms in lakes due to the macroscopic, fast, real-time characteristics. However, it is often difficult to distinguish between algal blooms and aquatic vegetation due to their similar spectral characteristics. In this paper, we used modified vegetation presence frequency index (VPF) based on Moderate-resolution Imaging Spectroradiometer (MODIS) imagery to distinguish algal blooms from aquatic vegetation, and analyzed the spatial and temporal variations of algal blooms and aquatic vegetation from a phenological perspective for five large natural lakes with frequent algal bloom outbreaks in China from 2019 to 2020. We simplified the VPF method to make it with a higher spatial transferability so that it could be applied to other lakes in different climatic zones. Through accuracy validation, we found that the modified VPF method can effectively distinguish between algal blooms and aquatic vegetation, and the results vary from lake to lake. The highest accuracy of 97% was achieved in Hulun Lake, where the frequency of algal outbreaks is low and the extent of aquatic vegetation is stable, while the lowest accuracy of 76% was achieved in Dianchi Lake, which is rainy in summer and the lake is small. Analyses suggests that the time period when algal blooms occur most frequently might not coincide with that when they have the largest area. However, in most cases these two are close in terms of time period. The modified VPF method has a broad scope of application, is easy to implement, and has a high practical value. Furthermore, the method could be established using only a small amount of measured data, which is useful for water quality monitoring on large spatial scales.
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Foundation item: Under the auspices of National Key Research and Development Project of China (No. 2021YFB3901101), National Natural Science Foundation of China (No. 41971322, 42071336, 42001311, 41730104), Jilin Provincial Science and Technology Development Project (No. 20180519021JH), Youth Innovation Promotion Association of Chinese Academy of Sciences (No. 2020234), China Postdoctoral Science Foundation (No. 2020M681057)
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Pu, J., Song, K., Liu, G. et al. Differentiation of Algal Blooms and Aquatic Vegetation in Chinese Lakes Using Modified Vegetation Presence Frequency Index Method. Chin. Geogr. Sci. 32, 792–807 (2022). https://doi.org/10.1007/s11769-022-1301-5
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DOI: https://doi.org/10.1007/s11769-022-1301-5