Algal blooms are commonly grown in the aquatic environment due to the excessive nutrients (nitrogen and phosphorous) present in ponds and reservoirs. Harmful algal blooms can produce toxic compounds that can contaminate the water and cause serious and harmful effects on aquatic life. Along with algal blooms the presence of other organic matter also makes huge gallons of water unfit for consumption. Remote Sensing is one of the efficient and well-established technologies that is used for the detection of phytoplankton present in the water. Monitoring the rapid growth of algal blooms continuously requires high-resolution spatial and temporal satellite data sets that are costly and hard to get. The images acquired through Unmanned Air Vehicle (UAV) produce high spatial resolution information to continuously monitor the algal bloom growth variation cost-effectively. In this proposed work, the algal bloom presented in the Waddeaplly Lake (Warangal, India) was captured by using a multispectral sensor mounted in DJI Phantom 4 Pro V2.0. RGB images were acquired and pre-processed in Pix4D Mapper Pro to develop the orthomosaic image. NGRDI, NGBDI, GNDVI, and ExGI indices are used in this proposed work to extract the algal bloom matter present in the lake and the data is compared with the Sentinel-2A images for validation purposes. UAV plays an important role in continuously monitoring the algae biomass and developing the precautionary warning system accurately.
Algal Bloom Detection Using UAV Imagery: A Case Study on Waddepally Lake, Warangal
Lecture Notes in Civil Engineering
International Conference on Unmanned Aerial System in Geomatics ; 2021 ; Roorkee, India April 02, 2021 - April 04, 2021
2023-03-16
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Data assimilation and deep learning in lake algal global bloom forecasting
BASE | 2022
|Data assimilation and deep learning in lake algal global bloom forecasting
HENRY – Bundesanstalt für Wasserbau (BAW) | 2022
|Skylab Detection of an Algal Bloom in the Gulf of Mexico
AIAA | 1978
|