Landsat-Satellite-Based Analysis of Long-Term Temporal Spatial Dynamics of Cyanobacterial Blooms: A Case Study in Taihu Lake

Jingtai Li, Yao Liu, Siying Xie, Min Li, Li Chen, Cuiling Wu, Dandan Yan and Zhaoqing Luan ()
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Jingtai Li: College of Biology and the Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
Yao Liu: College of Biology and the Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
Siying Xie: College of Biology and the Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
Min Li: College of Biology and the Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
Li Chen: College of Biology and the Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
Cuiling Wu: College of Biology and the Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
Dandan Yan: College of Horticulture and Plant Protection, Henan University of Science and Technology, Luoyang 471023, China
Zhaoqing Luan: College of Biology and the Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China

Land, 2022, vol. 11, issue 12, 1-19

Abstract: Cyanobacterial blooms in large and shallow freshwater lakes have become one of the most severe ecological problems threatening the environment and public health. Although great progress has been made in Taihu Lake in cyanobacterial bloom monitoring, most previous studies have used MODIS images with a resolution greater than 250 m, available after 2000, while the fine-scale studies on its long-term spatio-temporal dynamics to date are insufficient. This study monitored the spatiotemporal distribution of cyanobacterial blooms in Taihu Lake between 1984 and 2021 using Landsat images of 30 m resolution on the cloud computation platform Google Earth Engine and calculated the cyanobacterial blooms’ area percentage and the cyanobacterial bloom frequency index. Then, we investigated the influence of water quality and meteorological factors on area and frequency using Spearman correlation and principal component analysis. The results show that cyanobacterial blooms spread from the northern to the central, western, and eastern parts of Taihu Lake from 1984 to 2021. With the exception of East Lake, the area and frequency of cyanobacterial blooms increased significantly. Hypereutrophic water conditions, high temperatures, abundant sunshine hours, and low wind velocities all favor cyanobacteria blooms in Taihu Lake, and the key influencing factors of dynamics in cyanobacterial blooms are the comprehensive trophic level index, annual sunshine hours, and annual maximum wind speed. This study can serve as a reference for lake eutrophication monitoring and water resource management and protection.

Keywords: cyanobacterial blooms; Taihu Lake; spatiotemporal dynamics; influencing factors; Google Earth Engine; Landsat; remote sensing (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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