Improving Spaceborne GNSS-R Algal Bloom Detection with Meteorological Data

• Published in: Remote sensing (Basel, Switzerland) Vol. 15; no. 12; p. 3122
• Main Authors: Zhen, Yinqing, Yan, Qingyun
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.06.2023
• Subjects: Accuracy; Algae; algal bloom detection; algal blooms; Algorithms; Aquatic ecosystems; Artificial satellites in navigation; Artificial satellites in remote sensing; China; CYGNSS; Datasets; Environmental monitoring; Global navigation satellite system; GNSS-R; lakes; Machine learning; Meteorological data; Meteorological parameters; Methods; Monitoring methods; Plankton; Radiation; Remote sensing; RUSBoost; Satellite observation; Satellites; Solar radiation; surface water; Technology application; temperature; Water bloom; Wind speed; China; Taihu Lake

Algal bloom has become a serious environmental problem caused by the overgrowth of plankton in many waterbodies, and effective remote sensing methods for monitoring it are urgently needed. Global navigation satellite system-reflectometry (GNSS-R) has been developed rapidly in recent years, which off...