Harmful cyanobacterial blooms: biological traits, mechanisms, risks, and control strategies
L Song, Y Jia, B Qin, R Li… - Annual Review of …, 2023 - annualreviews.org
Harmful cyanobacterial blooms (CyanoHABs) impact lakes, estuaries, and freshwater
reservoirs worldwide. The duration, severity, and spread of CyanoHABs have markedly …
reservoirs worldwide. The duration, severity, and spread of CyanoHABs have markedly …
Machine learning-based design and monitoring of algae blooms: Recent trends and future perspectives–A short review
Abstract Machine learning (ML) models are widely used methods for analyzing data from
sensors and satellites to monitor climate change, predict natural disasters, and protect …
sensors and satellites to monitor climate change, predict natural disasters, and protect …
Map** invasive aquatic plants in sentinel-2 images using convolutional neural networks trained with spectral indices
Multispectral images collected by the European Space Agency's Sentinel-2 satellite offer a
powerful resource for accurately and efficiently map** areas affected by the distribution of …
powerful resource for accurately and efficiently map** areas affected by the distribution of …
[HTML][HTML] Modeling temporal and spatial variations of biogeochemical processes in a large subtropical lake: Assessing alternative solutions to algal blooms in Lake …
Abstract Study region: Algal blooms (ABs), often exacerbated by excess nutrients from
anthropogenic activities, can pose serious risks to public health, fisheries, and ecosystem …
anthropogenic activities, can pose serious risks to public health, fisheries, and ecosystem …
Leveraging explainable machine learning for enhanced management of lake water quality
Freshwater lakes worldwide suffer from eutrophication caused by excessive nutrient loads,
particularly nitrogen (N) and phosphorus (P) from wastewater and runoff, affecting aquatic …
particularly nitrogen (N) and phosphorus (P) from wastewater and runoff, affecting aquatic …
[HTML][HTML] Forecasting freshwater cyanobacterial harmful algal blooms for Sentinel-3 satellite resolved US lakes and reservoirs
This forecasting approach may be useful for water managers and associated public health
managers to predict near-term future high-risk cyanobacterial harmful algal blooms …
managers to predict near-term future high-risk cyanobacterial harmful algal blooms …
[HTML][HTML] Review of recent advances in remote sensing and machine learning methods for lake water quality management
This review examines the integration of remote sensing technologies and machine learning
models for efficient monitoring and management of lake water quality. It critically evaluates …
models for efficient monitoring and management of lake water quality. It critically evaluates …
Deep learning for spatiotemporal forecasting in Earth system science: a review
Deep learning (DL) has demonstrated strong potential in addressing key challenges in
spatiotemporal forecasting across various Earth system science (ESS) domains. This review …
spatiotemporal forecasting across various Earth system science (ESS) domains. This review …
An early warning model for starfish disaster based on multi-sensor fusion
L Li, T Liu, H Huang, H Song, S He, P Li… - Frontiers in Marine …, 2023 - frontiersin.org
Starfish have a wide range of feeding habits, including starfish, sea urchins, sea cucumbers,
corals, abalones, scallops, and many other marine organisms with economic or ecological …
corals, abalones, scallops, and many other marine organisms with economic or ecological …
Comparative evaluation of performances of algae indices, pixel-and object-based machine learning algorithms in map** floating algal blooms using Sentinel-2 …
One of the main threats to freshwater resources is pollution from anthropogenic activities
such as rapid urbanization and excessive agricultural nutrient runoff. Remote sensing …
such as rapid urbanization and excessive agricultural nutrient runoff. Remote sensing …