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MULTI-TEMPORAL MONITORING OF URBAN RIVER WATER QUALITY USING UAV-BORNE MULTI-SPECTRAL REMOTE SENSING

Authors: Liu, C.; Zhou, X.; Zhou, Y.; Akbar, A.;

MULTI-TEMPORAL MONITORING OF URBAN RIVER WATER QUALITY USING UAV-BORNE MULTI-SPECTRAL REMOTE SENSING

Abstract

Abstract. Water quality is an important index of the ecological environment, which changes rapidly and needs to be monitored chronically. In urban ecological environment, water quality problem is not only more serious, but also more complex in time and space. Remote sensing water quality monitoring can cover a large area in a short time. Therefore, remote sensing can be adopted to make up for the shortcomings of traditional water quality monitoring methods in space coverage and temporal resolution. In order to monitor the narrow rivers in urban area, low altitude remote sensing is needed. This paper proposes a multi-spectral water quality monitoring method based on UAV platform, which can quickly monitor an entire urban water area and conduct multi-temporal observation for key indices of water quality within one day. It is helpful to find and locate the polluted areas which affect the water environment quickly. Also, it can show the changes of water quality on the time axis. The result can provide a decision-making basis for water environment treatment.

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Subjects by Vocabulary

Library of Congress Subject Headings: lcsh:Applied optics. Photonics lcsh:T lcsh:TA1501-1820 lcsh:Technology lcsh:TA1-2040 lcsh:Engineering (General). Civil engineering (General)

Microsoft Academic Graph classification: geography geography.geographical_feature_category media_common.quotation_subject Multi spectral Urban area River water Remote sensing (archaeology) Temporal resolution Water environment Environmental science Quality (business) Water quality media_common Remote sensing

19 references, page 1 of 2

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Liu, Y., Zheng, Y., Liang, Y., Liu, S., & Rosenblum, D. S. 2016.

Urban water quality prediction based on multi-task multi-view learning. In IJCAI'16 Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (pp.

O., & Mueller, J. L. 1997. Remote sensing reflectance and inherent optical properties of oceanic waters derived from abovewater measurements. In Proceedings of SPIE, the International Society for Optical Engineering (Vol. 2963, pp. 160-166).

Minarík, R., Langhammer, J., & Hanus, J. 2019. Radiometric and Atmospheric Corrections of Multispectral μMCA Camera for UAV Spectroscopy. Remote Sensing, 11(20), 2428.

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    impulse
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    Average
  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    3
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
gold
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