Research of relationship between light reflectance and surface moisture content in tailings samples using hyperspectral images
DOI:
https://doi.org/10.4067/S0718-28132022000100077Keywords:
hypespectral imaging, moisture content, tailings storage facilities, NDVIAbstract
Proper tailings storage facilities (TSF) management can be done by monitoring various variables, such as moisture, which influences at physical and chemical stability phenomena. Nowadays, there are no continuous moisture controls due to the dangers associated with taking samples in tailings, generally in low-density states, making access difficult. Due to the recent hyperspectral imaging technologies and the successful use in monitoring interest variables (moisture, fines content, mineralogy) in areas such as hydrology and agriculture, therefore, this research uses hyperspectral images to estimate surface moisture in TSF using copper and iron tailings samples, which are subjected to active illumination from a 980 nm laser and monitored in a desiccation process in the moisture range from saturation to dry state, including density and fine content effects. Results show a parabolic relationship between moisture and light reflection, which, added to the use of the normalized difference vegetation index (NDVI), allow estimating the surface samples moisture content, generating an auspicious method for the continuous monitoring of humidity in TSF.
References
Araya, V., Suazo, G., Villavicencio, G. y Silva, M. (2019). Monitoreo de la humedad en depósitos de relave a partir de mediciones de reflexión de luz. Obras y Proyectos 25 , 35–41. https://doi.org/10.4067/S0718-28132019000100035
Ávila Álvarez, G. (2005). Estudio de la retracción y el agrietamiento de arcillas. Aplicación a la arcilla de Bogotá . Tesis doctoral, Universitat Politécnica de Cataluña, España.
Babaeian, E., Sadeghi, M., Gohardoust, M.R., Arthur, E., Jones, S. B. and Tuller, M. (2017). Application of shortwave infrared imaging for estimation of soil hydraulic properties. CSSA and SSSA International Annual Meeting , Tampa FL, USA. https://doi.org/10.13140/RG.2.2.30269.36322
Babaeian, E., Sadeghi, M., Jones, S.B. AND Tuller, M. (2019). Relating Evapotranspiration Rate, Soil and Plant temperature, and swir reflectance for root water uptake estimation. SSSA International Soils Meeting , San Diego CA, USA. https://doi.org/10.13140/RG.2.2.18340.73604
Brauers, J. and Aach, T. (2006). A color filter array based multispectral camera. 12th Workshop Farbbildverarbeitung , Ilmenau, Germany.
Changul, C., Sutthirat, C., Padmanahban, G. and Tongcumpou, C. (2010). Chemical characteristics and acid drainage assessment of mine tailings from Akara Gold Mine in Thailand. Environmental Earth Sciences 60 (8), 1583–1595. https://doi.org/10.1007/s12665-009-0293-0
Che, D., Liang, A., Li, X. and Ma, B. (2018). Remote sensing assessment of safety risk of iron tailings pond based on runoff coefficient. Sensors 18 (12), 4373. https://doi.org/10.3390/s18124373
Clark, R.N. (1999). Spectroscopy of rocks and minerals, and principles of spectrocopy. In Remote Sensing for the Earth Sciences: Manual of Remote Sensing , N. Rencz (ed.), John Wiley & Sons, New York, USA, vol. 3, 3–52.
Dalal, R.C. and Henry, R.J. (1986). Simultaneous determination of moisture, organic Carbon, and total Nitrogen by near infrared reflectance spectrophotometry. Soil Science Society of America Journal 50 (1), 120–123. https://doi.org/10.2136/sssaj1986.03615995005000010023x
Entezari, I., Rivard, B., Lipsett, M. and Wilson, W. (2013). Application of hyperspectral remote sensing in estimation of oilsands tailings water content. 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing , WHISPERS, Gainesville FL, USA, IEEE, 1-4. https://doi.org/10.1109/WHISPERS.2013.8080689
Gondek, J.S., Meyer, G.W. and Newman, J.G. (1994). Wavelength dependent reflectance functions. 21st Annual Conference on Computer Graphics and Interactive Techniques SIGGRAPH , Orlando FL, USA, ACM, 213–220.
Hassan-Esfahani, L., Torres-Rua, A., Jensen, A. and McKee, M. (2015). Assessment of surface soil moisture using high-resolution multi-spectral imagery and artificial neural networks. Remote Sensing 7 (3), 2627–2646. https://doi.org/10.3390/rs70302627
Sadeghi, M., Jones, S.B. and Philpot, W.D. (2015a). A linear physically-based model for remote sensing of soil moisture using short wave infrared bands. Remote Sensing of Environment 164 , 66–76. https://doi.org/10.1016/j.rse.2015.04.007
Sadeghi, M., Jones, S.B. and Tuller, M. (2015b). Toward a calibration-free model for optical remote sensing of soil moisture. Conference AGU Fall Meeting , San Francisco CA, USA. https://doi.org/10.13140/RG.2.1.1963.4004
Sadeghi, M., Sheng, W., Babaeian, E., Tuller, M. and Jones, S.B. (2017). High‐resolution shortwave infrared imaging of water infiltration into dry soil. Vadose Zone Journal 16 (13), 1–10. https://doi.org/10.2136/vzj2017.09.0167
Simms, P., Dunmola, A., Fisseha, B. and Bryan, R. (2010). Generic modelling of desiccation for cyclic deposition of thickened tailings to maximise density and to minimise oxidation. Thirteenth International Seminar on Paste and Thickened Tailings , R. Jewell and A.B. Fourie (eds.), Australian Centre for Geomechanics, Perth, Australia, 293–301. https://doi.org/10.36487/ACG_rep/1063_25_Simms
Thomasson, J.A., Sui, R., Cox, M.S. and Al–Rajehy, A. (2001). Soil reflectance sensing for determining soil properties in precision agriculture. Transactions of the ASAE 44 (6), 1445– 1453. https://doi.org/10.13031/2013.7002
Tschuschke, W., Gogolik, S., Wrózynska, M., Kroll, M. and Stefanek, P. (2020). The application of the seismic cone penetration test (SCPTU) in tailings water conditions monitoring. Water 12 (3), 737. https://doi.org/10.3390/w12030737
Tsukamoto, Y., Kawabe, S., Matsumoto, J. and Hagiwara, S. (2014). Cyclic resistance of two unsaturated silty sands against soil liquefaction. Soils and Foundations 54 (6), 1094–1103. https://doi.org/10.1016/j.sandf.2014.11.005
Valenzuela, L. (2016). Design, construction, operation and the effect of fines content and permeability on the seismic performance of tailings sand dams in Chile. Obras y Proyectos 19 , 6–22. https://doi.org/10.4067/S0718-28132016000100001
Villavicencio, A.G., Breul, P., Bacconnet, C., Boissier, D. and Espinace, A.R. (2011). Estimation of the variability of tailings dams properties in order to perform probabilistic assessment. Geotechnical and Geological Engineering 29 (6), 1073–1084. https://doi.org/10.1007/s10706-011-9438-5
Weidong, L., Baret, F., Xingfa, G., Bing, Z., Qingxi, T. and Lanfen, Z. (2003). Evaluation of methods for soil surface moisture estimation from reflectance data. International Journal of Remote Sensing 24 (10), 2069–2083. https://doi.org/10.1080/01431160210163155
Wright, S.P., Walden, P.J., Sangha, C.M. and Langdon, N.J. (1996). Observations on soil permeability, moulding moisture content and dry density relationships. Quarterly Journal of Engineering Geology 29 (3), 249–255. https://doi.org/10.1144/GSL.QJEGH.1996.029.P3.08
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Monserrat Sánchez, Gonzalo Suazo, Víctor Araya, Gabriel Villavicencio
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
