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http://dx.doi.org/10.7843/kgs.2019.35.11.51

Soil Water Content Measurement Technology Using Hyperspectral Visible and Near-Infrared Imaging Technique  

Lim, Hwan-Hui (Dept. of Civil and Environmental Engrg., KAIST)
Cheon, Enok (Dept. of Civil and Environmental Engrg., KAIST)
Lee, Deuk-Hwan (Dept. of Civil and Environmental Engrg., KAIST)
Jeon, Jun-Seo (Building Safety Research Center & Seismic Safety Research Center, Korea Institute of Civil Engineering and Building Technology)
Lee, Seung-Rae (Dept. of Civil and Environmental Engrg., KAIST)
Publication Information
Journal of the Korean Geotechnical Society / v.35, no.11, 2019 , pp. 51-62 More about this Journal
Abstract
In this study, a simple method to estimate the soil water content variation in a wide area was proposed using hyperspectral near-infrared images. The reflectance data of a sand, granite soils, and a kaolinite were measured by reflecting the soil samples with different wavelengths in the visible and near-infrared (VNIR) regions using hyperspectral cameras. The measured reflectances and parameters were used to build a water content prediction model using the Partial Least Square Regression (PLSR) analysis. In the water content prediction model, the Area of Reflectance (Near-infrared, NIR) parameter was the most suitable parameter to determine the water content. The parameter was applicable regardless of the soil type, as the coefficient of determination (R2) exceeded 0.9 for each soil sample. Additionally, the mean absolute percentage error (MAPE) was less than 15% when compared with the actual water content of the soil. Therefore, the predictability of water content variation for soils with water content lower than 50% was confirmed. Accordingly through this study, the predictability of water content variation in several soil types using the hyperspectral near-infrared images was confirmed. For further development, a model that incorporates soil classification would be required to improve the accuracy of the model and to predict higher range of water contents.
Keywords
Granite soils; Hyperspectral camera; Kaolinite; Sand; Visible and near-infrared; Water content;
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Times Cited By KSCI : 2  (Citation Analysis)
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