Probabilistic machine learning-based phytoplankton abundance using hyperspectral remote sensing

Probabilistic machine learning-based phytoplankton abundance using hyperspectral remote sensing

Remote sensing is a crucial tool for understanding the spatial dynamics of algal blooms by quantifying and detecting algal proliferation in water bodies. Hyperspectral remote monitoring enables precise pigment concentration measurements of Cyanobacteria, facilitating the accurate quantification of a...

Full description

Saved in:
Bibliographic Details
Main Authors: Do Hyuck Kwon, Jung Min Ahn, Jong Cheol Pyo, Jiye Lee, Ather Abbas, Sanghyun Park, Kyunghyun Kim, Hyuk Lee, Kyung Hwa Cho
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:GIScience & Remote Sensing
Subjects:
Hyperspectral remote sensing
algal bloom
deep learning
probabilistic modeling
Online Access:https://www.tandfonline.com/doi/10.1080/15481603.2025.2484864
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.tandfonline.com/doi/10.1080/15481603.2025.2484864

Similar Items