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author:

Liao, Yansong (Liao, Yansong.) [1] | Huang, Fenghua (Huang, Fenghua.) [2]

Indexed by:

EI Scopus

Abstract:

Black and malodorous water bodies represent a severe water pollution phenomenon that urgently needs addressing due to the discomfort and health risks they pose. Since the release of the'Action Plan for Prevention and Control of Water Pollution' in 2015 and the subsequent'Action Plan for the Treatment of Black and Malodorous Water Bodies in Urban Areas during the 14th Five-Year Plan Period' in 2022 by the Chinese government, monitoring efforts have become increasingly crucial. Remote sensing technology offers advantages such as high dynamics, low cost, and a macroscopic perspective in ecological environment monitoring, making it advantageous over traditional physical and chemical methods in monitoring black and malodorous water bodies. This paper summarizes remote sensing methods for identifying black and malodorous water bodies, including extraction of information through spectral, spatial, index, and temporal features, and analyzes the monitoring feasibility of these methods while pointing out potential issues. Finally, future research directions for identifying black and malodorous water bodies are discussed. © 2024 Copyright held by the owner/author(s).

Keyword:

Cleaner production Environmental monitoring Water pollution Water pollution control

Community:

  • [ 1 ] [Liao, Yansong]The Academy of Digital China, Fuzhou University, China
  • [ 2 ] [Liao, Yansong]Fujian University Engineering Research Center of Spatial Data Mining and Application, Yango University, China
  • [ 3 ] [Liao, Yansong]Fujian Key Laboratory of Spatial Information Perception and Intelligent Processing, Yango University, China
  • [ 4 ] [Huang, Fenghua]Fujian University Engineering Research Center of Spatial Data Mining and Application, Yango University, China
  • [ 5 ] [Huang, Fenghua]Fujian Key Laboratory of Spatial Information Perception and Intelligent Processing, Yango University, China
  • [ 6 ] [Huang, Fenghua]College of Artificial Intelligence, Yango University, China

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Year: 2024

Page: 5-10

Language: English

Cited Count:

WoS CC Cited Count:

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ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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