A Study on UAV-Based Water Contents of Soil Monitoring for Fugitive Dust Management at Construction Sites

doi:10.15683/kosdi.2026.3.31.105

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2026 Vol.22, Issue 1 Preview Page Next Page

Original Article

A Study on UAV-Based Water Contents of Soil Monitoring for Fugitive Dust Management at Construction Sites 건설현장 비산먼지 관리를 위한 드론 기반 지반 함수비 모니터링 연구: 김기성¹ㆍ김재호²ㆍ박승진³ㆍ이광구⁴*
Ki-Sung Kim¹, Jae-Ho Kim², Sung-jin Park³, Kwang-gu Lee⁴*; ¹CEO, Corporate Research Institute, UCI Tech Co., Ltd., Incheon, Republic of Korea
²Researcher, Corporate Research Institute, UCI Tech Co., Ltd., Incheon, Republic of Korea
³Professor, Department of Urban Engineering, Incheon National University, Incheon, Republic of Korea
⁴Executive Director, Corporate Research Institute, UCI Tech Co., Ltd., Incheon, Republic of Korea

31 March 2026. pp. 105-113

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Abstract

Purpose: Fugitive dust at construction sites is a major air pollution source, but current water spraying relies on experience, causing uneven control. This study aims to propose a spatial monitoring approach based on soil moisture prediction. Method: UAV-based hyperspectral imagery and an ANN model were used to estimate soil water content, trained with field measurements and validated using 5-fold cross-validation. Result: The model showed high accuracy with an average R² of about 0.97, effectively identifying dry zones prone to dust generation. Conclusion: The proposed UAV–AI approach enables data-driven dust management and improves the limitations of conventional point-based methods.

Keywords

Fugitive Dust

Construction Site

Water Content

Hyperspectral Imaging

ANN

연구목적: 비산먼지는 건설현장의 주요 대기오염원으로, 기존 살수 방식은 경험에 의존하여 공간적 저감 불균형이 발생한다. 본 연구는 함수비의 공간적 예측을 기반으로 비산먼지 관리 모니터링 기법을 제안하는 것을 목적으로 한다. 연구방법: UAV 기반 초분광 영상을 통해 건설현장의 공간 정보를 취득하고, 현장 실측 함수비 데이터를 결합하여 ANN 기반 예측모델을 구축하였다. 모델 학습 과정에서는 다양한 분광 특성과 함수비 간의 관계를 반영하였으며, 5-Fold 교차검증을 적용하여 모델의 일반화 성능과 신뢰성을 평가하였다. 연구결과: 모델은 평균 결정계수(R²) 약 0.97의 높은 예측 정확도를 나타내었으며, 실제 함수비와의 높은 상관성을 확인하였다. 또한 함수비의 공간 분포를 시각화함으로써 건조 구간을 효과적으로 식별할 수 있었으며, 이는 비산먼지 발생 가능성이 높은 구역을 정량적으로 판단할 수 있음을 의미한다. 결론: 제안된 UAV–AI 기반 함수비 예측 기법은 기존 점측정 중심의 비산먼지 관리 방식과 달리, 공간 기반의 정밀한 관리가 가능하도록 한다. 이를 통해 살수 작업의 효율성과 정확도를 향상시킬 수 있으며, 향후 건설현장 환경관리의 데이터 기반 의사결정을 지원하는 실용적인 모니터링 도구로 활용될 수 있다.

키워드

비산먼지

건설 현장

함수비

초분광 영상

인공신경망

References

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Environmental Protection Agency (EPA) (2020). Compilation of Air Pollutant Emission Factors (AP-42). Washington. USA.
Kim, H., Tae, S., Yang, J. (2020) “Calculation methods of emission factors and emissions of fugitive particulate matter in South Korean construction sites.” Sustainability, Vol. 12, 9802. 10.3390/su12239802
Kim, J.-H. (2019). A Study on the Reduction of Fugitive Dust from Construction Site. Master’s Dissertation, University of Suwon.
Kim, K.-S., Kim, J.-H., Ahn, H.-C., Park, J.-J., Hong, G.-K., You, S.-K. (2021). “A fundamental study on spectral information according to the water content condition of Jumunjin standard sand.” Proceedings of the 2021 Spring Geosynthetics Conference, Korean Geotechnical Society, Seoul, Republic of Korea, pp. 5-6.
Lee, K., Ahn, H., Park, J., Cho, J., You, S., Hong, G. (2021). “a study on reliability analysis for prediction technology of water content in the ground using hyperspectral information.” Journal of the Korean Geosynthetics Society, Vol. 20, No. 4, pp.141-149. 10.12814/JKGSS.2021.20.4.141
Munkhtsetseg, E., Shinoda, M., Gillies, J.A., Kimura, R., King, J., Nikolich, G. (2016). “Relationships between soil moisture and dust emissions in a bare sandy soil of Mongolia.” Particuology, Vol. 28, pp.131-137. 10.1016/j.partic.2016.03.001
Shao, Y., Lu, H. (2000). “A simple expression for wind erosion threshold friction velocity.” Journal of Geophysical Research: Atmospheres, Vol. 105, No. D17, pp. 22437-22443. 10.1029/2000JD900304
World Health Organization (WHO) (2021). Air Quality Guidelines: Global Update 2021. WHO Regional Office for Europe. Geneva. Netherlands.
Yang, S., Liu, J., Bi, X., Ning, Y., Qiao, S., Yu, Q., Zhang, J. (2020). “Risks related to heavy metal pollution in urban construction dust fall of fast-developing Chinese cities.” Ecotoxicology and Environmental Safety, Vol. 197, 110628. 10.1016/j.ecoenv.2020.110628

Information

Publisher :The Korean Society of Disaster Information
Publisher(Ko) :한국재난정보학회
Journal Title :Journal of the Society of Disaster Information
Journal Title(Ko) :한국재난정보학회논문집
Volume : 22
No :1
Pages :105-113
DOI :https://doi.org/10.15683/kosdi.2026.3.31.105

[1] Bagnold, RA. (1941). The Physics of Blown Sand and Desert Dunes. Methuen & Co., London, U.K.

[2] Crooks, J.L., Cascio, W.E., Percy, M.S., Reyes, J., Neas, L. M., Hilborn, E.D. (2016). “The association between dust storms and daily non-accidental mortality in the United States, 1993-2005.” Environmental Health Perspectives, Vol. 124, No. 11, pp.1735-1743. 10.1289/EHP216 27128449 PMC5089887

[3] Environmental Protection Agency (EPA) (2020). Compilation of Air Pollutant Emission Factors (AP-42). Washington. USA.

[4] Kim, H., Tae, S., Yang, J. (2020) “Calculation methods of emission factors and emissions of fugitive particulate matter in South Korean construction sites.” Sustainability, Vol. 12, 9802. 10.3390/su12239802

[5] Kim, J.-H. (2019). A Study on the Reduction of Fugitive Dust from Construction Site. Master’s Dissertation, University of Suwon.

[6] Kim, K.-S., Kim, J.-H., Ahn, H.-C., Park, J.-J., Hong, G.-K., You, S.-K. (2021). “A fundamental study on spectral information according to the water content condition of Jumunjin standard sand.” Proceedings of the 2021 Spring Geosynthetics Conference, Korean Geotechnical Society, Seoul, Republic of Korea, pp. 5-6.

[7] Lee, K., Ahn, H., Park, J., Cho, J., You, S., Hong, G. (2021). “a study on reliability analysis for prediction technology of water content in the ground using hyperspectral information.” Journal of the Korean Geosynthetics Society, Vol. 20, No. 4, pp.141-149. 10.12814/JKGSS.2021.20.4.141

[8] Munkhtsetseg, E., Shinoda, M., Gillies, J.A., Kimura, R., King, J., Nikolich, G. (2016). “Relationships between soil moisture and dust emissions in a bare sandy soil of Mongolia.” Particuology, Vol. 28, pp.131-137. 10.1016/j.partic.2016.03.001

[9] Shao, Y., Lu, H. (2000). “A simple expression for wind erosion threshold friction velocity.” Journal of Geophysical Research: Atmospheres, Vol. 105, No. D17, pp. 22437-22443. 10.1029/2000JD900304

[10] World Health Organization (WHO) (2021). Air Quality Guidelines: Global Update 2021. WHO Regional Office for Europe. Geneva. Netherlands.

[11] Yang, S., Liu, J., Bi, X., Ning, Y., Qiao, S., Yu, Q., Zhang, J. (2020). “Risks related to heavy metal pollution in urban construction dust fall of fast-developing Chinese cities.” Ecotoxicology and Environmental Safety, Vol. 197, 110628. 10.1016/j.ecoenv.2020.110628

Journal of the Society of Disaster Information ISSN:1976-2208(Print) 2671-5287(Online) 한국재난정보학회논문집

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