Landslide susceptibility analysis on road sections in Kaligesing District, Indonesia, using Frequency Ratio (FR) approaches
Road construction with intensive slope cutting increases landslide susceptibility along the road section, especially in hilly areas such as Kaligesing, Indonesia. This study aimed to compile a landslide susceptibility map along the road section in Kaligesing and evaluate the level of susceptibility...
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| Language: | English |
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University of Brawijaya
2025-07-01
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| Series: | Journal of Degraded and Mining Lands Management |
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| Online Access: | https://jdmlm.ub.ac.id/index.php/jdmlm/article/view/17046 |
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| author | Rianita Pertiwi Junun Sartohadi M. Anggri Setiawan Edwin Maulana |
| author_facet | Rianita Pertiwi Junun Sartohadi M. Anggri Setiawan Edwin Maulana |
| author_sort | Rianita Pertiwi |
| collection | DOAJ |
| description | Road construction with intensive slope cutting increases landslide susceptibility along the road section, especially in hilly areas such as Kaligesing, Indonesia. This study aimed to compile a landslide susceptibility map along the road section in Kaligesing and evaluate the level of susceptibility based on the main causal factors. GIS approach and quantitative statistical analysis Frequency Ratio (FR) were used in the susceptibility model. Eighty-two landslide points were randomly divided into training (70%) and testing (30%) datasets. Twelve causal factors were used in the analysis: slope direction, elevation, lithology, slope gradient, curvature, hemeroby degree, Topographic Wetness Index (TWI), distance from the river, distance from the road, rainfall, soil texture, and soil aggregate. Model validation used the Area Under Curve (AUC) value to evaluate model performance. The findings showed that the model is accurate, with an AUC value of 0.75 for the training set and 0.71 for the testing set. Furthermore, the level of landslide susceptibility is divided into four classes, namely very high (73 km), high (70.77 km), moderate (0.07 km), and very low (0.03 km). Thus, the findings can be used to support decision-making and planning for more adaptive road infrastructure development in landslide-prone areas. |
| format | Article |
| id | doaj-art-1e130b61fcd14365bdb4a3d896f24cb3 |
| institution | OA Journals |
| issn | 2339-076X 2502-2458 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | University of Brawijaya |
| record_format | Article |
| series | Journal of Degraded and Mining Lands Management |
| spelling | doaj-art-1e130b61fcd14365bdb4a3d896f24cb32025-08-20T02:38:25ZengUniversity of BrawijayaJournal of Degraded and Mining Lands Management2339-076X2502-24582025-07-011247913792210.15243/jdmlm.2025.124.791317048Landslide susceptibility analysis on road sections in Kaligesing District, Indonesia, using Frequency Ratio (FR) approachesRianita Pertiwi0Junun Sartohadi1https://orcid.org/0000-0002-0059-8335M. Anggri Setiawan2https://orcid.org/0000-0001-6586-1520Edwin Maulana3https://orcid.org/0009-0004-1582-1394Geoinformation Study for Disaster Management and Spatial Planning, The Graduate School of Gadjah Mada University, Yogyakarta, Indonesia Department of Soil Science, Gadjah Mada University, Yogyakarta, Indonesia Department of Environmental Geography, Gadjah Mada University, Yogyakarta, Indonesia Research Center for Land Resources Management, Gadjah Mada University, Yogyakarta, IndonesiaRoad construction with intensive slope cutting increases landslide susceptibility along the road section, especially in hilly areas such as Kaligesing, Indonesia. This study aimed to compile a landslide susceptibility map along the road section in Kaligesing and evaluate the level of susceptibility based on the main causal factors. GIS approach and quantitative statistical analysis Frequency Ratio (FR) were used in the susceptibility model. Eighty-two landslide points were randomly divided into training (70%) and testing (30%) datasets. Twelve causal factors were used in the analysis: slope direction, elevation, lithology, slope gradient, curvature, hemeroby degree, Topographic Wetness Index (TWI), distance from the river, distance from the road, rainfall, soil texture, and soil aggregate. Model validation used the Area Under Curve (AUC) value to evaluate model performance. The findings showed that the model is accurate, with an AUC value of 0.75 for the training set and 0.71 for the testing set. Furthermore, the level of landslide susceptibility is divided into four classes, namely very high (73 km), high (70.77 km), moderate (0.07 km), and very low (0.03 km). Thus, the findings can be used to support decision-making and planning for more adaptive road infrastructure development in landslide-prone areas.https://jdmlm.ub.ac.id/index.php/jdmlm/article/view/17046frequency ratiogeospatialkaligesinglandslide susceptibilityroad section |
| spellingShingle | Rianita Pertiwi Junun Sartohadi M. Anggri Setiawan Edwin Maulana Landslide susceptibility analysis on road sections in Kaligesing District, Indonesia, using Frequency Ratio (FR) approaches Journal of Degraded and Mining Lands Management frequency ratio geospatial kaligesing landslide susceptibility road section |
| title | Landslide susceptibility analysis on road sections in Kaligesing District, Indonesia, using Frequency Ratio (FR) approaches |
| title_full | Landslide susceptibility analysis on road sections in Kaligesing District, Indonesia, using Frequency Ratio (FR) approaches |
| title_fullStr | Landslide susceptibility analysis on road sections in Kaligesing District, Indonesia, using Frequency Ratio (FR) approaches |
| title_full_unstemmed | Landslide susceptibility analysis on road sections in Kaligesing District, Indonesia, using Frequency Ratio (FR) approaches |
| title_short | Landslide susceptibility analysis on road sections in Kaligesing District, Indonesia, using Frequency Ratio (FR) approaches |
| title_sort | landslide susceptibility analysis on road sections in kaligesing district indonesia using frequency ratio fr approaches |
| topic | frequency ratio geospatial kaligesing landslide susceptibility road section |
| url | https://jdmlm.ub.ac.id/index.php/jdmlm/article/view/17046 |
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