4.7 Article

Comparison of UAS and Sentinel-2 Multispectral Imagery for Water Quality Monitoring: A Case Study for Acid Mine Drainage Affected Areas (SW Spain)

Journal

REMOTE SENSING
Volume 14, Issue 16, Pages -

Publisher

MDPI
DOI: 10.3390/rs14164053

Keywords

abandoned mine; acidic water; surface water monitoring; drone; Copernicus programme

Funding

  1. Erasmus Mundus Joint Master Degree (EMJMD) in Water and Coastal Management (WACOMA)
  2. Erasmus+ Programme of the European Union
  3. Plan Andaluz de Investigacion RNM 166 Environmental radioactivity research group
  4. FEDER UHU2020-21 Project
  5. MINECO [EQC2018-00446-P, UNCA-2013-1969]
  6. Spanish Ministry of Science and Innovation [IJC2018-035056-I]
  7. European Regional Development Fund MCIN/AEI [RTI 2018-098784-J-I00]
  8. Spanish State Research Agency
  9. Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades from Andalusian Government through the Andalusian FEDER operational program 2014-2020 [A1123060E0_PYC20 RE 032 UHU]
  10. Innovation Ecosystems of the International Excellence Centers

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This study examines the potential of using Sentinel-2 (S2) data to complement UAS data for monitoring water quality in mining environments affected by acid mine drainage (AMD). The results show that the S2 atmospheric correction (AC) processors, C2RCC and C2X, perform well for acidic greenish-blue and non-acidic greenish-brown water bodies, but not for acidic dark reddish-brown waters. There are significant differences in reflectance between the UAS sensor and both S2 AC processors, which should be considered when combining data from both instruments.
Uncrewed Aerial Systems (UAS) and satellites are used for monitoring and assessing the quality of surface waters. Combining both sensors in a joint tool may scale local water quality retrieval models to regional and global scales by translating UAS-based models to satellite imagery. The main objective of this study is to examine whether Sentinel-2 (S2) data can complement UAS data, specifically from the MicaSense RedEdge MX-Dual sensor, for inland water quality monitoring in mining environments affected by acid mine drainage (AMD). For this purpose, a comparison between UAS reflectance maps and atmospherically corrected S2 imagery was performed. S2 data were processed with Case 2 Regional Coast Colour (C2RCC) and Case 2 Regional Coast Colour for Complex waters (C2X) atmospheric correction (AC) processors. The correlation between the UAS data and the atmospherically corrected S2 data was evaluated on a band-by-band and a pixel-by-pixel basis, and the compatibility of the spectral data was analyzed through statistical methods. The results showed C2RCC and C2X performed better for acidic greenish-blue and non-acidic greenish-brown water bodies concerning the UAS data than for acidic dark reddish-brown waters. However, significant differences in reflectance between the UAS sensor and both S2 AC processors have been detected. The poor agreement between sensors should be considered when combining data from both instruments since these could have further consequences in developing multi-scale models.

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