An ensemble machine learning model for water quality estimation in coastal area based on remote sensing imagery
The accurate estimation of coastal water quality parameters (WQPs) is crucial for decision-
makers to manage water resources. Although various machine learning (ML) models have …
makers to manage water resources. Although various machine learning (ML) models have …
[HTML][HTML] Harmful Algal Blooms in Eutrophic Marine Environments: Causes, Monitoring, and Treatment
J Lan, P Liu, X Hu, S Zhu - Water, 2024 - mdpi.com
Marine eutrophication, primarily driven by nutrient over input from agricultural runoff,
wastewater discharge, and atmospheric deposition, leads to harmful algal blooms (HABs) …
wastewater discharge, and atmospheric deposition, leads to harmful algal blooms (HABs) …
Estimating coastal chlorophyll-a concentration from time-series OLCI data based on machine learning
Chlorophyll-a (chl-a) is an important parameter of water quality and its concentration can be
directly retrieved from satellite observations. The Ocean and Land Color Instrument (OLCI) …
directly retrieved from satellite observations. The Ocean and Land Color Instrument (OLCI) …
Quantifying Karenia brevis bloom severity and respiratory irritation impact along the shoreline of Southwest Florida
Nearly all annual blooms of the toxic dinoflagellate Karenia brevis (K. brevis) pose a serious
threat to coastal Southwest Florida. These blooms discolor water, kill fish and marine …
threat to coastal Southwest Florida. These blooms discolor water, kill fish and marine …
A remote sensing and machine learning-based approach to forecast the onset of harmful algal bloom
In the last few decades, harmful algal blooms (HABs, also known as “red tides”) have
become one of the most detrimental natural phenomena in Florida's coastal areas. Karenia …
become one of the most detrimental natural phenomena in Florida's coastal areas. Karenia …
Red tide detection method for HY− 1D Coastal Zone imager based on U− Net convolutional neural network
X Zhao, R Liu, Y Ma, Y Xiao, J Ding, J Liu, Q Wang - Remote Sensing, 2021 - mdpi.com
Existing red tide detection methods have mainly been developed for ocean color satellite
data with low spatial resolution and high spectral resolution. Higher spatial resolution …
data with low spatial resolution and high spectral resolution. Higher spatial resolution …
Red tide detection using deep learning and high-spatial resolution optical satellite imagery
Red tide is one of the most devastating phenomena that have impacted coastal
environments and fishery on a local scale in the worldwide seas. Satellite imagery can …
environments and fishery on a local scale in the worldwide seas. Satellite imagery can …
Mapping and forecasting onsets of harmful algal blooms using MODIS data over coastal waters surrounding Charlotte County, Florida
Over the past two decades, persistent occurrences of harmful algal blooms (HAB; Karenia
brevis) have been reported in Charlotte County, southwestern Florida. We developed data …
brevis) have been reported in Charlotte County, southwestern Florida. We developed data …
Distribution of Harmful Algae (Karenia spp.) in October 2021 Off Southeast Hokkaido, Japan
H Kuroda, Y Taniuchi, T Watanabe… - Frontiers in Marine …, 2022 - frontiersin.org
An unprecedented large-scale outbreak of harmful algae, including Karenia selliformis and
Karenia mikimotoi, was reported in mid-September 2021 in the northwest Pacific Ocean off …
Karenia mikimotoi, was reported in mid-September 2021 in the northwest Pacific Ocean off …
Detection of Karenia brevis red tides on the West Florida Shelf using VIIRS observations: Accounting for spatial coherence with artificial intelligence
Harmful algal blooms (HABs) of the toxic dinoflagellate Karenia brevis (K. brevis) occur
annually on the West Florida Shelf (WFS). Detection of these blooms using satellite …
annually on the West Florida Shelf (WFS). Detection of these blooms using satellite …