Acknowledgement
Supported by : Ministry of Land, Infrastructure and Transport
References
- Adhikari, R.S., Bagchi A. and Moselhi O. (2014), "Automated condition assessment of concrete bridges with digital imaging", Smart Struct. Syst., 13(6), 901-925. https://doi.org/10.12989/sss.2014.13.6.901
- Arita, J., Sasaki, K.I., Endo, T. and Yasuoka, Y. (2001). "Assessment of concrete degradation with hyper-spectral remote sensing", Proceedings of the 22nd Asian Conference on Remote Sensing, Singapore, November.
- BASF (2014), Efflorescence Guidelines - causes, prevention, removal, control; BASF, Ludwigshafen, Germany: www.basf.com
- Baseley, D., Wunderlich, L., Phillips, G., Gross, K., Perram, G., Willison, S., Phillips, R., Magnuson, M., Lee, S.D. and Harper, W.F. (2016), "Hyperspectral analysis for standoff detection of dimethyl methylphosphonate on building materials", Build. Environ., 108, 135-142. https://doi.org/10.1016/j.buildenv.2016.08.028
- Bateson, A. and Curtiss, B. (1996), "A method for manual endmember selection and spectral unmixing", Remote Sens. Environ., 55(3), 229-243. https://doi.org/10.1016/S0034-4257(95)00177-8
- Cemex USA - Technical Bulletin (2008), Efflorescence in Concrete Products, Houston, Texas, USA: available at http://www.cemexusa.com/ProductsServices/files/TechnicalServices/Efflorescence_in_Concrete_Products.pdf.
- Caughlin, T.T., Graves, S.J., Asner, G.P., Breugel, M., Hall, J.S., Martin, R.E. and Bohlman, S.A. (2016), "A hyperspectral image can predict tropical tree growth rates in single-species stands", Ecological Appl., 26(8), 2367-2373.
- Chang, C.I. (2003), Techniques for Spectral Detection and Classification, Kluwer Academic/ Plenum Publishers, New York, USA.
- Dawood, T., Zhu, Z., and Zayed, T. (2017), "Machine vision-based model for spalling detection and quantification in subway networks", Autom. Constr., 81, 149-160. https://doi.org/10.1016/j.autcon.2017.06.008
- Dow, C. and Glasser, F.P. (2003), "Calcium carbonate efflorescence on Portland cement and building materials", Cement Concrete Res., 33(1), 147-154. https://doi.org/10.1016/S0008-8846(02)00937-7
- ElMasry, G., Sun, D.W. and Allen, P. (2012), "Near-infrared hyperspectral imaging for predicting colour, pH and tenderness of fresh beef", J. Food Eng., 110(1), 127-140. https://doi.org/10.1016/j.jfoodeng.2011.11.028
- Grahn. H. and Geladi. P. (2007), Techniques and Applications of Hyperspectral Image Analysis. John Wiley & Sons., NJ, USA.
- Harris Geospatial Solutions (2017), Material Identification Using ENVI. Available at: https://www.harrisgeospatial.com/docs/THORMaterialIdentification.html.
- Jun, S., Xin, Z., Hanping, M., Xiaohong, W., Xiaodong, Z. and Hongyan, G. (2016), "Identification of pesticide residue level in lettuce based on hyperspectra and chlorophyll fluorescence spectra",. Int. J. Agricultural Biol. Eng., 9(6), 231.
- Kokaly, R.F., Clark, R.N., Swayze, G.A., Livo, K.E., Hoefen, T.M., Pearson, N.C., Wise, R.A., Benzel, W.M., Lowers, H.A., Driscoll, R.L. and Klein, A.J. (2017), USGS Spectral Library Version 7: U.S. Geological Survey Data Series 1035, 61 p.
- Kruse, F.A., Lefkoff, A.B., Boardman, J.W., Heidebrecht, K.B., Shapiro, A.T., Barloon, P.J. and Goetz, A.F.H. (1993), "The spectral image processing system (SIPS)-interactive visualization and analysis of imaging spectrometer data", Remote Sens. Environ., 44(2-3), 145-163. https://doi.org/10.1016/0034-4257(93)90013-N
- Lee, J.D., Dewitt, B.A., Lee, S.S., Bhang, K.J. and Sim, J.B. (2012), "Analysis of concrete reflectance characteristics using spectrometer and VNIR hyperspectral camera", Int. Arch. Photogrammetry Remote Sens. Spatial Inform. Sci., 39, B7.
- Liu, Y., Cho, S., Spencer Jr, B.F. and Fan, J. (2014), "Automated assessment of cracks on concrete surfaces using adaptive digital image processing", Smart Struct. Syst., 14(4), 719-741. https://doi.org/10.12989/sss.2014.14.4.719
- Man, S.H., Chang, C.C., Hassan, M. and Bermak, A. (2015), "Design and calibration of a wireless laser-based optical sensor for crack propagation monitoring", Smart Struct. Syst., 15(6), 1543-1567 https://doi.org/10.12989/sss.2015.15.6.1543
- Ministry of Land, Infrastructure, and Transport (MOLIT) (2016), Detailed Guidelines of Safety Inspection and Precise Safety Diagnosis for Bridges (in Korean).
- Proto, M., Bavusi, M., Bernini, R., Bigagli, L., Bost, M., Bourquin, F., Cottineau, L.M., Cuomo, V., Vecchia, P.D., Dolce, M. and Dumoulin, J. (2010), "Transport infrastructure surveillance and monitoring by electromagnetic sensing: the ISTIMES project", Sensors, 10(12), 10620-10639. https://doi.org/10.3390/s101210620
- Santos, B.O., Valenca, J., and Julio, E. (2017), Detection of cracks on concrete surfaces by hyperspectral image processing. In Automated Visual Inspection and Machine Vision II (Vol. 10334, p. 1033407). International Society for Optics and Photonics. Munich, Germany, June.
- Taylor, H.F. (1997), Cement Chemistry. Thomas Telford Ltd. London, UK
- USGS Spectral Library (2017), Version 7, available at: https://speclab.cr.usgs.gov/spectral-lib.html.
- Vaghefi, K., Oats, R.C., Harris, D.K., Ahlborn, T.T.M., Brooks, C. N., Endsley, K.A., Roussi, C., Shuchman, R., Burns, J.W. and Dobson, R. (2011), "Evaluation of commercially available remote sensors for highway bridge condition assessment", J. Bridge Eng., 17(6), 886-895. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000303
- van der Werff, H.M.A. (2006), Knowledge-based Remote Sensing of Complex Objects: Recognition of Spectral and Spatial Patterns Resulting from Natural Hydrocarbon Seepages. Utrecht University, Utrecht, Utrecht, Netherlands
- Zhang, C., Ye, H., Liu, F., He, Y., Kong, W. and Sheng, K. (2016), "Determination and visualization of pH values in anaerobic digestion of water hyacinth and rice straw mixtures using hyperspectral imaging with wavelet transform denoising and variable selection", Sensors, 16(2), 244. https://doi.org/10.3390/s16020244
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