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Open AccessArticle

MODIS-Satellite-Based Analysis of Long-Term Temporal-Spatial Dynamics and Drivers of Algal Blooms in a Plateau Lake Dianchi, China

by Yuanyuan Jing 1,2, Yuchao Zhang 1,3,*, Minqi Hu 1,2, Qiao Chu 1,2 and Ronghua Ma 1,3
1
Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
Jiangsu Collaborative Innovation Center of Regional Modern Agriculture & Environmental Protection, Huaiyin Normal University, Huai’an 223300, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(21), 2582; https://doi.org/10.3390/rs11212582
Received: 18 September 2019 / Revised: 26 October 2019 / Accepted: 28 October 2019 / Published: 4 November 2019
(This article belongs to the Special Issue Operational Ecosystem Monitoring Applications from Remote Sensing)
Algal blooms in eutrophic lakes have been a global issue to environmental ecology. Although great progress on prevention and control of algae have been made in many lakes, systematic research on long-term temporal-spatial dynamics and drivers of algal blooms in a plateau Lake Dianchi is so far insufficient. Therefore, the algae pixel-growing algorithm (APA) was used to accurately identify algal bloom areas at the sub-pixel level on the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 2000 to 2018. The results showed that algal blooms were observed all year round, with a reduced frequency in winter–spring and an increased frequency in summer–autumn, which lasted a long time for about 310–350 days. The outbreak areas were concentrated in 20–80 km2 and the top three largest areas were observed in 2002, 2008, and 2017, reaching 168.80 km2, 126.51 km2, and 156.34 km2, respectively. After deriving the temporal-spatial distribution of algal blooms, principal component analysis (PCA) and redundancy analysis (RDA) were applied to explore the effects of meteorological, water quality and human activities. Of the variables analyzed, mean temperature (Tmean) and wind speed (WS) were the main drivers of daily algal bloom areas and spatial distribution. The precipitation (P), pH, and water temperature (WT) had a strong positive correlation, while WS and sunshine hours (SH) had a negative correlation with monthly maximum algal bloom areas and frequency. Total nitrogen (TN) and dissolved oxygen (DO) were the main influencing factors of annual frequency, initiation, and duration of algal blooms. Also, the discharge of wastewater and the southwest and southeast monsoons may contribute to the distribution of algal blooms mainly in the north of the lake. However, different regions of the lake show substantial variations, so further zoning and quantitative joint studies of influencing factors are required to more accurately understand the true mechanisms of algae in Lake Dianchi. View Full-Text
Keywords: algal blooms; influencing drivers; lake dianchi; MODIS; APA algal blooms; influencing drivers; lake dianchi; MODIS; APA
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MDPI and ACS Style

Jing, Y.; Zhang, Y.; Hu, M.; Chu, Q.; Ma, R. MODIS-Satellite-Based Analysis of Long-Term Temporal-Spatial Dynamics and Drivers of Algal Blooms in a Plateau Lake Dianchi, China. Remote Sens. 2019, 11, 2582.

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