Automatic Detection of Algal Blooms Using Sentinel-2 MSI and Landsat OLI Images

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing Vol. 14; pp. 8497 - 8511
• Main Authors: Xu, Dandan, Pu, Yihan, Zhu, Mengyuan, Luan, Zhaoqing, Shi, Kun
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algae; Algal bloom; Algal blooms; Aquatic ecosystems; Artificial satellites; cyanobacteria; Detection; Eutrophication; Imagery; Inland waters; Lakes; Landsat; Landsat operational land imager (OLI); Landsat satellites; Microorganisms; Monitoring; Remote sensing; Resolution; Satellite imagery; sentinel-2 multispectral instrument (MSI); Spaceborne remote sensing; spatial autocorrelation; Spatial discrimination; Spatial distribution; Spatial resolution; Temporal resolution; Taihu Lake

Algal bloom is a serious global issue for inland waters, posing poses a serious threat to aquatic ecosystems. The timely and accurate detection of algal blooms is critical for their control, management and forecasting. Optical satellite imagery with short revisit times has been widely used to monito...