Estimation of cyanobacteria pigments in the main rivers of South Korea using spatial attention convolutional neural network with hyperspectral imagery

Estimation of cyanobacteria pigments in the main rivers of South Korea using spatial attention convolutional neural network with hyperspectral imagery

Although remote sensing techniques have been used to monitor toxic cyanobacteria with hyperspectral data in inland water, it is difficult to optimize conventional bio-optical algorithms for individual water bodies because of the complex optical properties of various water components. Therefore, this...

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Bibliographic Details
Main Authors: Seok Min Hong, Kyung Hwa Cho, Sanghyun Park, Taegu Kang, Moon Sung Kim, Gibeom Nam, JongCheol Pyo
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:GIScience & Remote Sensing
Subjects:
algal pigment
deep learning model
sensitivity analysis
geum river
nakdong river
yeongsan river
Online Access:http://dx.doi.org/10.1080/15481603.2022.2037887

Internet

http://dx.doi.org/10.1080/15481603.2022.2037887

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