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Year 2020
 
Vol 61, Issue 2, [04 - 2020]

Determination of water quality parameters in the Tan Rai exploiting area (Lam Dong province) using Sentinel-2 MSI and Landsat 8 data

DOI:10.46326/JMES.2020.61(2).14

  • Affiliations:

    1 Faculty of Geomatics and Land Administration, Hanoi University of Mining and Geology, Vietnam 2 Military Technical Academy, Vietnam

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  • Received: 5th-Feb-2020
  • Revised: 6th-Mar-2020
  • Accepted: 29th-Apr-2020
  • Online: 28th-Apr-2020
Pages: 126 - 134
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Cited by: 3

Abstract:

Despite high profits, the mining process often leads to negative effects on the quality of groundwater around the mining site. Due to the close relationship between the concentration of water quality parameters and spectral reflectance values of surface water, optical remote sensing image has been used effectively in the world in assessing and monitoring surface water quality. This paper presents the results of determining some surface water quality parameters in the Tan Rai bauxite mining area (Lam Dong province) such as turbidity, water-transparency (Secchi depth), and surface temperature from Sentinel-2A and Landsat 8 images taken on January 29, 2019. The results obtained in this study show that the mining process has a great influence on the surface water quality in Tan Rai (Lam Dong), reflected in all three water quality parameters such as turbidity, Secchi depth, and water temperature.

How to Cite
Nguyen, N.Viet and Trinh, H.Le 2020. Determination of water quality parameters in the Tan Rai exploiting area (Lam Dong province) using Sentinel-2 MSI and Landsat 8 data (in Vietnamese). Journal of Mining and Earth Sciences. 61, 2 (Apr, 2020), 126-134. DOI:https://doi.org/10.46326/JMES.2020.61(2).14.
References

Ahn Y. H., Shanmugam P., Lee J. H., Kang Y. Q. (2006). Application of satellite infrared data for mapping of thermal plume contamination in coastal ecosystem of Korea. Marine Environmental Research 61. 186 - 201.

Baughman C. A., Jones B. M., Bartz K. K., Young D. B., Zimmerman C. E. (2015). Reconstructing Turbidity in a Glacially Influenced Lake Using the Landsat TM and ETM+ Surface Reflectance Climate Data Record Archive, Lake Clark, Alaska. Remote Sensing 7. 13692 - 13710.

Chavez P. S. (1988). An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sensing of Environment 24. 459 - 479.

Dekker A. G., Zamurovic-Nenad Z., Hoogenboom H. J., Petters W. M. (1996). Remote sensing, ecological water quality modelling and in situ measurements: a case study in shallow lakes. Hydrological Sciences Journal 41(4). 531 - 547.

Delegido J., Urrego P., Vicente E., Sòria-Perpinyà X., Soria J. M., Pereira-Sandoval M., Ruiz-Verdú A., Peña R., Moreno J. (2019). Turbidity and Secchi disc depth with Sentinel-2 in different trophic status reservoirs at the Comunidad Valenciana. Revista de Teledetección 54. 15 - 24.

Doxaran D., Froidefond J. M., Lavender S., Castaing P., (2002). Spectral signature of highly turbid waters application with SPOT data to quantify suspended particulate matter concentrations. Remote Sensing of Enviroment 81. 149 - 161.

Gholizaded M., Melesse A., Reddi L. (2016). A comprehensive review on water quality parameters estimation using remote sensing techniques. Sensors 16. 1298. 43.

https://glovis.usgs.gov

https://scihub.copernicus.eu/dhus/

Kang K.M., Kim S.H., Kim, D.J., Cho Y.K., Lee S.H. (2014). Comparison of coastal sea surface temperature derived from ship-, air-, and space-borne thermal infrared systems. In Proceedings of the 2014 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Quebec City, QC, Canada. 4419 - 4422.

Loise H., Vantrepotte V., Jamet C., Dinh N. D. (2013). Challenges and new advances in ocean color remote sensing of coastal waters. In book: Earth and Planetary Sciences 38.

Mobley C. D. (1994). Light and water: radiative tranfer in natural waters, Academic Press: San Diego, CA.

Nguyen H. Q., Sasaki J., Higa H., Nguyen H. H. (2017). Spatiotemporal variation of turbidity based on Landsat 8 OLI in Cam Ranh Bay and Thuy Trieu lagoon, Vietnam, Water, 9, 570, 25 pp.

Ritchie J.C., Cooper C.M. (1988). Comparision of measured suspended semdiment concentration with suspended sediment concentrations estimated from Landsat MSS data, International Journal of Remote Sensing, 9(3), 379 - 387.

Syariz M., Jaelani L., Subehi L., Pamungkas A., Koenhardono E., Sulisetyono A., (2015). Retrieval of sea surface temperature over poteran island water of indonesia with Landsat 8 tirs image: A preliminary algorithm, ISPRS International Archives of the Photogrammetry,  Remote Sensing and Spatial Information Sciences 1. 87 - 90.

Trinh L. H., Tarasov M. K. (2016). Evaluation of suspended sediment concentrations in surface water of the Tri An water reservoir using remote sensing, Moscow University Bulletin. Series 5. Geography 2. 38 - 44.

Trinh L.H., Zablotskii V., Le T.G., Dinh T.T.H., Le T.T., Trinh T.T., Nguyen T.T.N. (2018). Estimation of suspended sediment concentration using VNREDSat - 1A multispectral data, a case study in Red River, Hanoi, Vietnam. Geography, Environment. Sustainability 11(3). 49 - 60.

Trịnh Lê Hùng (2018). Kết hợp ảnh vệ tinh Landsat 8 và Sentinel 2 trong nâng cao độ phân giải không gian nhiệt độ bề mặt, Tạp chí Khoa học ĐHQG Hà Nội, chuyên san Các Khoa học Trái Đất và Môi trường 34(4). 54 - 63.

Vesecky J., Onstott R., Wang N., Lettvin E., Slawski J., Shuchman R. (1994). Water surface temperature estimates using active and passive microwave remote sensing: Preliminary results from an outdoor wind-wave tank, In Geoscience and Remote Sensing Symposium, 1994. IGARSS’94. Surface and Atmospheric Remote Sensing: Technologies, Data Analysis and Interpretation, International; IEEE: New York, NY, USA. 1021 - 1023.

Zhou W., Wang S., Zhou Y., Troy A. (2006). Mapping the concentrations of total suspended matter in Lake Taihu, China using Landsat 5 TM data, International Journal of Remote Sensing 27(6). 1177 - 1191.

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