Spectrum Index for Estimating Ground Water Content Using Hyperspectral Information

Kicheol Lee, Ki Sung Kim, Jeongjun Park () and Gigwon Hong ()
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Kicheol Lee: Corporate Affiliated Research Institute, UCI Tech, 313, Inha-ro, Michuhol-gu, Incheon 22012, Korea
Ki Sung Kim: Corporate Affiliated Research Institute, UCI Tech, 313, Inha-ro, Michuhol-gu, Incheon 22012, Korea
Jeongjun Park: Incheon Disaster Prevention Research Center, Incheon National University, 119 Academy-ro, Yeonsu-gu, Incheon 22012, Korea
Gigwon Hong: Department of Civil Engineering, Halla University, 28 Halladae-gil, Wonju-si 26404, Korea

Sustainability, 2022, vol. 14, issue 21, 1-17

Abstract: Quality control considerably affects road stability and operability and is directly linked to the underlying ground compaction. The degree of compaction is largely determined by water content, which is typically measured at the actual construction site. However, conventional methods for measuring water content do not capture entire construction sites efficiently. Therefore, this study aimed to apply remote sensing of hyperspectral information to efficiently measure the groundwater content of large areas. A water content prediction equation was developed through an indoor experiment. The experimental samples comprised 0–40% (10% increase) of fine contents added to standard sand. As high water content is not required in road construction, 0–15% (1% increase) of water content was added. The test results were normalized, the internal and external environments were controlled for precise results, and a wavelength–reflection curve was derived for each test case. Data variability analyses were performed, and the appropriate wavelength for water content reflection, as well as reflectance, was determined and converted into a spectrum index. Finally, various fitting models were applied to the corresponding spectrum index for water content prediction. Reliable results were obtained with the reflectance corresponding to a wavelength of 720 nm applied as the spectrum index.

Keywords: spectrum index; water content; hyperspectral information (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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