Bloom Forecasting
Bloom Forecasting is a predictive modeling framework that distinguishes itself by estimating the likelihood, timing, magnitude, and spatial extent of harmful algal blooms through the integration of environmental, biological, and remote sensing data.
266
Publications
14.7K
Citations
1.1K
Authors
467
Institutions
Publications per year
2017–2026
144
Parents
266
Interannual Variability of Cyanobacterial Blooms in Lake Erie
Richard P. Stumpf, Timothy T. Wynne, David B. Baker et al. · PLoS ONE · 2012 · 424 citations · Full text
Neural network modelling of coastal algal blooms
Joseph H.W. Lee, Yan Yan Shery Huang, Mike Dickman et al. · Ecological Modelling · 2002 · 280 citations
1–5 of 266
1.1K
NOAA National Centers for Coastal Ocean Science, United States
11 publications · 1.2K citations
11
h-index
NOAA National Centers for Coastal Ocean Science, United States
7 publications · 1.1K citations
7
h-index
6
h-index
6
h-index
6
h-index
1–5 of 1.1K
467

Chinese Academy of Sciences
Beijing, China
14 h-index
50 publications
1.9K citations
Nanjing Institute of Geography and Limnology
Nanjing, China
11 h-index
33 publications
2.4K citations
NOAA Great Lakes Environmental Research Laboratory
Ann Arbor, United States
10 h-index
23 publications
2.4K citations
University of Michigan
Ann Arbor, United States
9 h-index
19 publications
1.1K citations
National Oceanic and Atmospheric Administration
Washington, United States
9 h-index
20 publications
3.3K citations

University of Hong Kong
Pok Fu Lam, Hong Kong
8 h-index
23 publications
2.5K citations
Tsinghua University
Beijing, China
7 h-index
28 publications
963 citations
National Institute of Environmental Research
Incheon, South Korea
6 h-index
28 publications
1.3K citations
1–8 of 467
22 publications · 1.7K citations
20
h-index
12 publications · 1K citations
12
h-index
12 publications · 639 citations
12
h-index
10 publications · 805 citations
9
h-index
8 publications · 312 citations
8
h-index
1–5