Monitor water quality through retrieving water quality parameters from hyperspectral images using graph convolution network with superposition of multi-point effect: A case study in Maozhou River-Reference-Cited by-同舟云学术

Monitor water quality through retrieving water quality parameters from hyperspectral images using graph convolution network with superposition of multi-point effect: A case study in Maozhou River

Published:2023-09 Issue: Volume:342 Page:118283
ISSN:0301-4797
Container-title:Journal of Environmental Management
language:en
Short-container-title:Journal of Environmental Management

Author:

Zhang Yishan,Kong Xin,Deng Licui,Liu Yawei

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Waste Management and Disposal,General Medicine,Environmental Engineering

Reference104 articles.

1. Comparative study of different B-spline approaches for functional data;Aguilera;Math. Comput. Model.,2013

2. Chlorophyll-a retrieval from sentinel-2 images using convolutional neural network regression;Aptoula;Geosci. Rem. Sens. Lett. IEEE,2021

3. Monitoring water quality of valle de bravo reservoir, Mexico, using entire lifespan of meris data and machine learning approaches;Arias-Rodriguez;Rem. Sens.,2020

4. Processing of makhana and value chain financing in Bihar;Atal;International Journal of Current Microbiology and Applied Sciences,2020

5. Hybrid treatment system for real textile wastewater remediation based on coagulation/flocculation, adsorption and filtration processes: performance and economic evaluation;Badawi;J. Water Process Eng.,2021

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1. Hyperspectral Image Super-Resolution via Adaptive Factor Group Sparsity Regularization-Based Subspace Representation;Remote Sensing;2023-10-07

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