Soil depth estimation in mountainous areas by using GIS and satellite images

Sangseom Jeong, Moonhyun Hong, Jinho Song

Research output: Contribution to journalArticlepeer-review


Soil depth, a major parameter influencing the behavior of landslides, was estimated by scanning rocky surfaces in mountainous areas to spatially obtain the thickness of the soil zone. The emphasis was on quantifying the rocky surface identification with the soil depth estimation by using the K-means clustering method and geographic information system (GIS) data on topology, land use, rock proportion, and satellite images. The results of the rocky surface identification in the study area were compared with the field survey, and it was shown that the classification with and without rocky surfaces in the mountainous area was different from the other natural mountains with basal soil areas only. Based on the results obtained, a simple method is presented for identifying the spatial thickness of the soil zone in mountainous areas by comparison with in situ borehole data. Moreover, a landslide-debris flow simulation was performed using the estimated soil depth map, and it was found that the prediction results using the proposed method showed relatively high accuracy compared with other predictions overestimated by excessive soil depth.

Original languageEnglish
Pages (from-to)2711-2726
Number of pages16
Issue number11
Publication statusPublished - 2022 Nov

Bibliographical note

Funding Information:
This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2018R1A6A1A08025348).

Publisher Copyright:
© 2022, Springer-Verlag GmbH Germany, part of Springer Nature.

All Science Journal Classification (ASJC) codes

  • Geotechnical Engineering and Engineering Geology


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