ANALYSIS OF LAND USE FACTOR ON LANDSLIDE USING MODIFIED FREQUENCY RATIO
Abstract
Landslide is one of the most hazardous in Semarang Regency. This study was conducted to develop landslide susceptibility mapping (LSM) and analyzes land use and land cover (LULC) with other factors to landslide. Land use, ground motion, elevation, slope, soil type, rainfall, and Normal Difference Vegetation Index (NDVI) were used for landslide causative factor. 303 landslide data used for landslide inventory was randomly divided into data training (70%) and data validation (30%). Landslide inventory and landslide causative factors were performed using Geographic Information System (GIS) with method Modified Frequency Ratio. The result of Modified Frequency Ratio analysis for the highest value for each class factor was 3500-4000mm/year (rainfall): 1500-2000m (elevation), mid (ground motion): Settlement (LULC): Andosol (soil): 0 - 0.25 (NDVI): 15-25% (Slope). The highest value for Prediction rate was LULC. Landslide susceptibility was evaluated with the area under curve (AUC): the value showed 0.957 excellent analysis. LULC class settlement showed the highest landslide susceptibility in Semarang Regency.
References
Abedin, J., Rabby, Y.W., Hasan, I. (2020). An investigation of the characteristics, causes, and consequences of June 13, 2017, landslides in Rangamati District Bangladesh. Geoenvironmental Disasters 7(23):1–19. https://doi.org/10.1186/s40677-020-00161-z
Achour ,Y., Abderrahmane B., Riheb H., Abdelmadjid C., Victor C., and El A.B.. (2017). Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine, Algeria. Arabian Journal of Geosciences, 10(8): 1–16. http://dx.doi.org/10.1007/s12517-017-2980-6
Ajin, R. S., Sunil S., Anik S., Aparna B., Romulus-Dumitru C., and Sekhar L.K. (2022). Enhancing the Accuracy of the REPTree by Integrating the Hybrid Ensemble Meta-Classifiers for Modelling the Landslide Susceptibility of Idukki District, South-western India. Journal of the Indian Society of Remote Sensing, 50(13): 2245-2265.
https://doi.org/10.1007/s12524-022-01599-4
Arrisaldi., T, Wilopo, W., and Fathani, T.F. (2021). Landslide Susceptibility Mapping and Their Rainfall Thresholds Model inTinalah Watershed, Kulon Progo District, Yogyakarta Special Region, Indonesia. Journal of Applied Geology, 6(2): 112–118. http://dx.doi.org/10.22146/jag.59185
Bahrami, Y., Hassani, H. & Maghsoudi, A. (2021). Landslide susceptibility mapping using AHP and fuzzy methods in the Gilan province, Iran. GeoJournal, 86(4): 1797–1816. https://link.springer.com/article/10.1007/s10708-020-10162-y
Baral, N., Karna, A., and Gautam, S.. (2021). Landslide Susceptibility Assessment Using Modified Frequency Ratio Model in Kaski District, Nepal. International Journal of Engineering and Management Research. 11: 167-177.
https://doi.org/10.31033/ijemr.11.1.23
Campforts, B., Shobe, C.M., Overeem, I., & Tucker, G. E. (2022). The art of landslides: How stochastic mass wasting shapes topography and influences landscape dynamics. Journal of Geophysical Research: Earth Surface, 127(8): 1-22. https://doi.org/10.1029/2022JF006745
Çellek, S. (2020). Effect of the Slope Angle and Its Classification on Landslide. Nat. Hazards Earth Syst. Sci. Discuss, 87(1):1–28. https://doi.org/10.5194/nhess-2020-87
Chen, L., Guo, Z., Yin, K., Shrestha, D. P., and Jin, S. (2019). The influence of land use and land cover change on landslide susceptibility: a case study in Zhushan Town, Xuan'en County (Hubei, China): Nat. Hazards Earth Syst. Sci., 19(10):2207–2228. http://dx.doi.org/10.5194/nhess-19-2207-2019
De Medina, V., Hurlimann, M., Guo, Z., Lloret, A., & Vaunat, J. (2021). Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale. Catena, 201(105213). https://doi.org/10.1016/j.catena.2021.105213
Hamza, T., & Raghuvanshi, T. K. (2017). GIS-based landslide hazard evaluation and zonation–A case from Jeldu District, Central Ethiopia. Journal of King Saud University-Science, 29(2): 151–165. https://doi.org/10.1016/j.jksus.2016.05.002
Hürlimann, M., Guo, Z., Puig-Polo, C., and Medina, V. (2022). Impacts of future climate and land cover changes on landslide susceptibility: regional scale modeling in the Val d’Aran region (Pyrenees, Spain) Landslides, 19 (1): 99–118. http://dx.doi.org/10.1007/s10346-021-01775-6
Karsli, F., Atasoy, M., Yalcin, A. Reis, A., Demir, O., and Gokceoglu, C. (2009). Effects of land-use changes on landslides in a landslide-prone area (Ardesen, Rize, NE Turkey). Environ Monit Assess, 156, 241–255. https://doi.org/10.1007/s10661-008-0481-5
Kornejady, A., Ownegh, M., and Bahremand, A.. (2017). Landslide susceptibility assessment using maximum entropy model with two different data sampling methods, Catena, 152, 144–162. https://doi.org/10.1016/j.catena.2017.01.010
Makealoun, S., Putra, D.P.E., & Wilopo, W. (2014). Landslide Susceptibility Assessment Of kokap Area Using Multiple Logistic Regression. J.SE Asian Appl. Geol., 6(2): 53–61.
https://doi.org/10.22146/jag.7217
Meneses, B. M., Pereira, S., and Reis, E. (2019). Effects of different land use and land cover data on the landslide susceptibility zonation of road networks, Nat. Hazards Earth Syst. Sci., 19(3): 471–487.
Nurdin, P. F., & Kubota, T. (2018). GIS-based Landslide Susceptibility Assessment by Certainty Factor and Logistic Regression in Upstream of Jeneberang River, Indonesia. Geoplanning: Journal of Geomatics and Planning, 5(1): 75-90. https://doi.org/10.14710/geoplanning.5.1.75-90
Persichillo, M.G., Bordoni, M., And Meisina, C.. (2017). The role of land use changes in the distribution of shallow landslides. Sci. Total Environ. 574, 924 – 937.https://doi.org/10.1016/j.scitotenv.2016.09.125
Priyono, K.W., Jumadi, Saputra, A., And Fikriyah, V.N. (2020). Risk Analysis Of Landslide Impacts On Settlements In Karanganyar, Central Java, Indonesia. International Journal Of Geomate, 19(73), 100–107. https://doi.org/10.21660/2020.73.34128
Rabby, Y.W., Li, Y., Abedin, J., and Sabrina, S. (2022). Impact of Land Use/Land Cover Change on Landslide Susceptibility in Rangamati Municipality of Rangamati District, Bangladesh. ISPRS International Journal of Geo-Information, 11(2), 89. https://doi.org/10.3390/ijgi11020089
Rasyid, A.R., Bhandary, N.P. & Yatabe, R. (2016). Performance of frequency ratio and logistic regression model in creating GIS based landslides susceptibility map at Lompobattang Mountain, Indonesia. Geoenvironmental Disasters, 3(19), 1-16.
https://geoenvironmental-disasters.springeropen.com/articles/10.1186/s40677-016-0053-x
Selamat, S.N., Majid, N.A., Taha, M.R., and Osman, A. (2022). Landslide Susceptibility Model Using Artificial Neural Network (ANN) Approach in Langat River Basin, Selangor, Malaysia. Land, 11(6), 1-21. https://doi.org/10.3390/land11060833
Simanjuntak, Martin.R. and Tjahjono, H.. (2022). Analisis Ancaman Tanah Longsor dan Upaya Konservasi Lahan Dengan Sistem Agroforestri di Kecamatan Sukorejo Kabupaten Kendal. Geo Image, 11 (2) : 99-111. https://doi.org/10.15294/geoimage.v11i2.56573
Sunarta, I.N., Susila, K.D., and Kariasa, I.N. (2018). Landslide Hazard Analysis and Damage Assessment for Tourism Destination at Candikuning Village, Tabanan Regency, Bali, Indonesia. IOP Conf. Series: Earth and Environmental Science, 123(012006):1-10. http://dx.doi.org/10.1088/1755-1315/123/1/012006
Thapa, D. and Bhandari, B.P. (2019). GIS-Based Frequency Ratio Method for Identification of Potential Landslide Susceptible Area in the Siwalik Zone of Chatara-Barahakshetra Section, Nepal. Open Journal of Geology, 9(12), 873–896.
https://doi.org/10.4236/ojg.2019.912096
Vingiani, S., Mele, G., De Mascellis, R., Terribile, F., and Basile, A. (2015). Volcanic soils and landslides: a case study of the island of Ischia (southern Italy) and its relationship with other Campania events. Solid Earth, 6, 783–797.
https://doi.org/10.5194/se-6-783-2015
Wubalem, A. (2021). Landslide susceptibility mapping using statistical methods in Uatzau catchment area, northwestern Ethiopia. Geoenvironmental Disasters, 8(1),1-21.
https://doi.org/10.1186/s40677-020-00170-y
Zhang, Y. (2020). Research on the relationship between precipitation and landslide. E3S Web of Conferences, 198, 04027.https://doi.org/10.1051/e3sconf/202019804027
Achour ,Y., Abderrahmane B., Riheb H., Abdelmadjid C., Victor C., and El A.B.. (2017). Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine, Algeria. Arabian Journal of Geosciences, 10(8): 1–16. http://dx.doi.org/10.1007/s12517-017-2980-6
Ajin, R. S., Sunil S., Anik S., Aparna B., Romulus-Dumitru C., and Sekhar L.K. (2022). Enhancing the Accuracy of the REPTree by Integrating the Hybrid Ensemble Meta-Classifiers for Modelling the Landslide Susceptibility of Idukki District, South-western India. Journal of the Indian Society of Remote Sensing, 50(13): 2245-2265.
https://doi.org/10.1007/s12524-022-01599-4
Arrisaldi., T, Wilopo, W., and Fathani, T.F. (2021). Landslide Susceptibility Mapping and Their Rainfall Thresholds Model inTinalah Watershed, Kulon Progo District, Yogyakarta Special Region, Indonesia. Journal of Applied Geology, 6(2): 112–118. http://dx.doi.org/10.22146/jag.59185
Bahrami, Y., Hassani, H. & Maghsoudi, A. (2021). Landslide susceptibility mapping using AHP and fuzzy methods in the Gilan province, Iran. GeoJournal, 86(4): 1797–1816. https://link.springer.com/article/10.1007/s10708-020-10162-y
Baral, N., Karna, A., and Gautam, S.. (2021). Landslide Susceptibility Assessment Using Modified Frequency Ratio Model in Kaski District, Nepal. International Journal of Engineering and Management Research. 11: 167-177.
https://doi.org/10.31033/ijemr.11.1.23
Campforts, B., Shobe, C.M., Overeem, I., & Tucker, G. E. (2022). The art of landslides: How stochastic mass wasting shapes topography and influences landscape dynamics. Journal of Geophysical Research: Earth Surface, 127(8): 1-22. https://doi.org/10.1029/2022JF006745
Çellek, S. (2020). Effect of the Slope Angle and Its Classification on Landslide. Nat. Hazards Earth Syst. Sci. Discuss, 87(1):1–28. https://doi.org/10.5194/nhess-2020-87
Chen, L., Guo, Z., Yin, K., Shrestha, D. P., and Jin, S. (2019). The influence of land use and land cover change on landslide susceptibility: a case study in Zhushan Town, Xuan'en County (Hubei, China): Nat. Hazards Earth Syst. Sci., 19(10):2207–2228. http://dx.doi.org/10.5194/nhess-19-2207-2019
De Medina, V., Hurlimann, M., Guo, Z., Lloret, A., & Vaunat, J. (2021). Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale. Catena, 201(105213). https://doi.org/10.1016/j.catena.2021.105213
Hamza, T., & Raghuvanshi, T. K. (2017). GIS-based landslide hazard evaluation and zonation–A case from Jeldu District, Central Ethiopia. Journal of King Saud University-Science, 29(2): 151–165. https://doi.org/10.1016/j.jksus.2016.05.002
Hürlimann, M., Guo, Z., Puig-Polo, C., and Medina, V. (2022). Impacts of future climate and land cover changes on landslide susceptibility: regional scale modeling in the Val d’Aran region (Pyrenees, Spain) Landslides, 19 (1): 99–118. http://dx.doi.org/10.1007/s10346-021-01775-6
Karsli, F., Atasoy, M., Yalcin, A. Reis, A., Demir, O., and Gokceoglu, C. (2009). Effects of land-use changes on landslides in a landslide-prone area (Ardesen, Rize, NE Turkey). Environ Monit Assess, 156, 241–255. https://doi.org/10.1007/s10661-008-0481-5
Kornejady, A., Ownegh, M., and Bahremand, A.. (2017). Landslide susceptibility assessment using maximum entropy model with two different data sampling methods, Catena, 152, 144–162. https://doi.org/10.1016/j.catena.2017.01.010
Makealoun, S., Putra, D.P.E., & Wilopo, W. (2014). Landslide Susceptibility Assessment Of kokap Area Using Multiple Logistic Regression. J.SE Asian Appl. Geol., 6(2): 53–61.
https://doi.org/10.22146/jag.7217
Meneses, B. M., Pereira, S., and Reis, E. (2019). Effects of different land use and land cover data on the landslide susceptibility zonation of road networks, Nat. Hazards Earth Syst. Sci., 19(3): 471–487.
Nurdin, P. F., & Kubota, T. (2018). GIS-based Landslide Susceptibility Assessment by Certainty Factor and Logistic Regression in Upstream of Jeneberang River, Indonesia. Geoplanning: Journal of Geomatics and Planning, 5(1): 75-90. https://doi.org/10.14710/geoplanning.5.1.75-90
Persichillo, M.G., Bordoni, M., And Meisina, C.. (2017). The role of land use changes in the distribution of shallow landslides. Sci. Total Environ. 574, 924 – 937.https://doi.org/10.1016/j.scitotenv.2016.09.125
Priyono, K.W., Jumadi, Saputra, A., And Fikriyah, V.N. (2020). Risk Analysis Of Landslide Impacts On Settlements In Karanganyar, Central Java, Indonesia. International Journal Of Geomate, 19(73), 100–107. https://doi.org/10.21660/2020.73.34128
Rabby, Y.W., Li, Y., Abedin, J., and Sabrina, S. (2022). Impact of Land Use/Land Cover Change on Landslide Susceptibility in Rangamati Municipality of Rangamati District, Bangladesh. ISPRS International Journal of Geo-Information, 11(2), 89. https://doi.org/10.3390/ijgi11020089
Rasyid, A.R., Bhandary, N.P. & Yatabe, R. (2016). Performance of frequency ratio and logistic regression model in creating GIS based landslides susceptibility map at Lompobattang Mountain, Indonesia. Geoenvironmental Disasters, 3(19), 1-16.
https://geoenvironmental-disasters.springeropen.com/articles/10.1186/s40677-016-0053-x
Selamat, S.N., Majid, N.A., Taha, M.R., and Osman, A. (2022). Landslide Susceptibility Model Using Artificial Neural Network (ANN) Approach in Langat River Basin, Selangor, Malaysia. Land, 11(6), 1-21. https://doi.org/10.3390/land11060833
Simanjuntak, Martin.R. and Tjahjono, H.. (2022). Analisis Ancaman Tanah Longsor dan Upaya Konservasi Lahan Dengan Sistem Agroforestri di Kecamatan Sukorejo Kabupaten Kendal. Geo Image, 11 (2) : 99-111. https://doi.org/10.15294/geoimage.v11i2.56573
Sunarta, I.N., Susila, K.D., and Kariasa, I.N. (2018). Landslide Hazard Analysis and Damage Assessment for Tourism Destination at Candikuning Village, Tabanan Regency, Bali, Indonesia. IOP Conf. Series: Earth and Environmental Science, 123(012006):1-10. http://dx.doi.org/10.1088/1755-1315/123/1/012006
Thapa, D. and Bhandari, B.P. (2019). GIS-Based Frequency Ratio Method for Identification of Potential Landslide Susceptible Area in the Siwalik Zone of Chatara-Barahakshetra Section, Nepal. Open Journal of Geology, 9(12), 873–896.
https://doi.org/10.4236/ojg.2019.912096
Vingiani, S., Mele, G., De Mascellis, R., Terribile, F., and Basile, A. (2015). Volcanic soils and landslides: a case study of the island of Ischia (southern Italy) and its relationship with other Campania events. Solid Earth, 6, 783–797.
https://doi.org/10.5194/se-6-783-2015
Wubalem, A. (2021). Landslide susceptibility mapping using statistical methods in Uatzau catchment area, northwestern Ethiopia. Geoenvironmental Disasters, 8(1),1-21.
https://doi.org/10.1186/s40677-020-00170-y
Zhang, Y. (2020). Research on the relationship between precipitation and landslide. E3S Web of Conferences, 198, 04027.https://doi.org/10.1051/e3sconf/202019804027
Published
2023-08-11
How to Cite
KRISANDIKA, Kurnia; SUTRISNO, Alfred Jansen.
ANALYSIS OF LAND USE FACTOR ON LANDSLIDE USING MODIFIED FREQUENCY RATIO.
Proceeding Sustainable Agricultural Technology Innovation (SATI), [S.l.], v. 2, n. 1, p. 53-65, aug. 2023.
Available at: <http://ojs.unkriswina.ac.id/index.php/semnas-FST/article/view/532>. Date accessed: 30 apr. 2024.
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Articles
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