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Research Article

A remote sensing index for the detection of multi-type water quality anomalies in complex geographical environments

, , , , , & show all
Article: 2313695 | Received 09 Oct 2023, Accepted 29 Jan 2024, Published online: 05 Feb 2024
 

ABSTRACT

Frequent water quality anomalies severely affect the ecological environment, hindering the protection, restoration, and sustainable use of inland freshwater ecosystems in Sustainable Development Goals (SDG) 15.1. Thus, there is an urgent need to conduct real-time monitoring and early warnings of various water quality anomalies. However, current remote sensing indices of water quality anomalies are aimed at only one specific water anomaly event in water regions, which makes it difficult to achieve high-precision and on-orbit detection of sudden water quality anomalies in complex geographical environments with the limited storage and computing resources of satellites. Therefore, this study proposed a remote sensing index for the detection of multi-type water quality anomalies in complex geographical environments by analyzing the spectral differences between different earth’s surfaces. The validation results indicated that the proposed index achieved satisfactory performance for the synchronous detection of most water quality anomalies and could be used directly in complex geographical environments to detect water anomalies. Overall, this study contributes to the realization of real-time water quality anomaly detection methods in complex geographical environments, which increases the possibility of on-orbit water quality anomaly detection.

This article is part of the following collections:
Innovative approaches and applications on SDGs using SDGSAT-1

Acknowledgement

The authors appreciate the editors and anonymous reviewers for their valuable suggestions.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article was originally published with errors, which have now been corrected in the online version. Please see Correction (http://dx.doi.org/10.1080/17538947.2024.2359753)

Additional information

Funding

This study was supported by the National Natural Science Foundation of China (grant number 42192580 and No.42192581).