Cargando…
Predicting Cyanobacterial Blooms Using Hyperspectral Images in a Regulated River
Process-based modeling for predicting harmful cyanobacteria is affected by a variety of factors, including the initial conditions, boundary conditions (tributary inflows and atmosphere), and mechanisms related to cyanobacteria growth and death. While the initial conditions do not significantly affec...
Autores principales: | Ahn, Jung Min, Kim, Byungik, Jong, Jaehun, Nam, Gibeom, Park, Lan Joo, Park, Sanghyun, Kang, Taegu, Lee, Jae-Kwan, Kim, Jungwook |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7828484/ https://www.ncbi.nlm.nih.gov/pubmed/33451010 http://dx.doi.org/10.3390/s21020530 |
Ejemplares similares
-
Long-Term Examination of Water Chemistry Changes Following Treatment of Cyanobacterial Bloom with Coagulants and Minerals
por: Lee, Bokjin, et al.
Publicado: (2022) -
Microbial communities in aerosol generated from cyanobacterial bloom-affected freshwater bodies: an exploratory study in Nakdong River, South Korea
por: Kim, Jinnam, et al.
Publicado: (2023) -
Cyanobacterial Blooms and Microcystins in Southern Vietnam
por: Trung, Bui, et al.
Publicado: (2018) -
Shotgun Metagenomic Sequencing to Assess Cyanobacterial Community Composition following Coagulation of Cyanobacterial Blooms
por: Le, Kim Thien Nguyen, et al.
Publicado: (2022) -
A novel indicator for defining plain urban river network cyanobacterial blooms: resource use efficiency
por: Su, Yifan, et al.
Publicado: (2022)