* Corresponding Author
Potential of UAV-Generated Orthophotos in Assessing Environmental Vulnerability to Landslides in Ngasinan Village, Purworejo Regency, Central Java
https://doi.org/10.22146/ijg.83487 Yeni Astuti(1*), Junun Sartohadi(2), Guruh Samodra(3)
(1) Sekolah Pascasarjana, Universitas Gadjah Mada, Yogyakarta, Indonesia
(2) Fakultas Pertanian, Universitas Gadjah Mada, Yogyakarta, Indonesia
(3) Fakultas Geografi, Universitas Gadjah Mada, Yogyakarta, Indonesia
(*) Corresponding Author
Abstract
Ngasinan Village in Bener District, Purworejo Regency, has mountainous and sloping topography, which increases the risk of landslides. However, there is currently no available information regarding the village's environmental vulnerability to landslides, which is essential for disaster mitigation planning. This study aims to assess the environmental vulnerability to landslides in Ngasinan Village using orthophotos as an alternative to a census. The primary data used in this research include aerial photographs taken by an unmanned aerial vehicle (UAV) and Ground Control Points (GCPs) to ensure the accuracy of the orthophotos. The vulnerability parameters analyzed include socio-economic and physical environmental aspects. Aerial photo interpretation was used to identify building structures, the type of predominant walls, building age, building area, electricity usage, and distance from proper roads. The Digital Terrain Model (DTM) was used to extract parameters such as topographic clusters, topographic elevation, distance to steep slopes, and distance to very steep slopes. Environmental vulnerability analysis was conducted using interview data and questionnaires from research samples. The results show that Ngasinan Village falls into the medium vulnerability class. Orthophotos proved to be an accurate data source for assessing environmental vulnerability to landslides, with an accuracy rate of 86.66%. Furthermore, information on the vulnerability of houses to landslides can be obtained more easily and quickly through observation and interpretation of orthophotos compared to the census method.
Received: 2023-03-29 Revised: 2023-07-31 Accepted: 2025-06-05 Published: 2025-06-16
Keywords
References
Agliata, R., Bortone Antonio, & Mollo, L. (2022). The impact of the aggregation formula on indicator-based methods for the assessment of building susceptibility to hydro-meteorological hazards. International Journal of Disaster Risk Reduction. https://doi.org/10.1016/j.ijdrr.2022.102850
Case, E. A., & Sarkar, R. (2019). Determination of the Probabilities of Landslide. Hydrology, 6(52).
Darrozes, J., Pisano, L., Zumpano, V., Malek, Ž., Micu, M., Aucelli, P. P. C., Rosskopf, C. M., Balteanu, D., & Parise, M. (2018). Economic Losses for Rural Land Value Due to Landslides. Earth Science 1, 97. https://doi.org/10.3389/feart.2018.00097
Dias, M. C. de A., Saito, S. M., Alvalá, R. C. dos S., Seluchi, M. E., Bernardes, T., Camarinha, P. I. M., Stenner, C., & Nobre, C. A. (2020). Vulnerability index related to populations atrisk for landslides in the Brazilian Early Warning System (BEWS). International Journal of Disaster Risk Reduction, 49(June). https://doi.org/10.1016/j.ijdrr.2020.101742
Ebert, A., Kerle, N., & Stein, A. (2009). Urban social vulnerability assessment with physical proxies and spatial metrics derived from air- and spaceborne imagery and GIS data. Natural Hazards, 48(2), 275–294. https://doi.org/10.1007/s11069-008-9264-0
Fariz, T. R. (2019). Penilaian kerentanan fisik rumah terhadap longsor berdasarkan interpretasi foto udara format kecil di Sub DAS Bompon, Kabupaten Magelang. Tesis. Universitas Gadjah Mada.
Gao, Z., Ding, M., Huang, T., Liu, X., Hao, Z., Hu, X., & Chuanjie, X. (2022). Landslide risk assessment of high-mountain settlements using Gaussian process classification combined with improved weight-based generalized objective function. International Journal of Disaster Risk Reduction (Vol. 67). https://doi.org/10.1016/j.ijdrr.2021.102662
Guru, B., Veerappan, R., Sangma, F., & Bera, S. (2017). Comparison of probabilistic and expert-based models in landslide susceptibility zonation mapping in part of Nilgiri District, Tamil Nadu, India. Spatial Information Research, 25(6), 757–768. https://doi.org/10.1007/s41324-017-0143-1
Haneberg, W. C. (2007). Landslide: Processes, Prediction, and Land Use. Environmental and Engineering Geoscience. (Vol. 13, Issue 1). https://doi.org/10.2113/gseegeosci.13.1.90
Luo, H. Y., Fan, R. L., Wang, H. J., & Zhang, L. M. (2020). Physics of building vulnerability to debris flows, floods and earth flows. Engineering Geology (Vol. 271). https://doi.org/10.1016/j.enggeo.2020.105611
Luo, H. Y., Zhang, L. M., Wang, H. J., & He, J. (2021). Process of building collapse caused by the Po Shan Road landslide in Hong Kong on 18 June 1972. Landslides, 18(12), 3769–3780. https://doi.org/10.1007/s10346-021-01745-y
Mendonca, M. B. de, & Silva, D. R. da. (2020). Integration of census data based vulnerability in landslide risk mapping - The case of Angra dos Reis, Rio de Janeiro, Brazil. International Journal of Disaster Risk Reduction (Vol. 50). https://doi.org/10.1016/j.ijdrr.2020.101884
Mirdda, H. A., Bera, S., & Chatterjee, R. (2022). Vulnerability assessment of mountainous households to landslides: A multidimensional study in the rural Himalayas. International Journal of Disaster Risk Reduction (Vol. 71, p. 102809). Elsevier Ltd. https://doi.org/10.1016/j.ijdrr.2022.102809
National Disaster Management Agency (BNPB). 2008. Disaster Data, Landslide Disaster 2008, online at https://gis.bnpb.go.id/. accessed 24 June 2022
National Disaster Management Agency (BNPB). 2012. Regulation of the Head of the National Disaster Management Agency Number 02 of 2012 concerning General Guidelines for Disaster Risk Assessment. Jakarta: National Disaster Management Agency
National Disaster Management Agency (BNPB). 2023. Disaster Data, Landslide Disaster 2010-2022, online at https://gis.bnpb.go.id/. accessed 15 January 2023
Noveberian, (2017). Pemetaan Rumah Rentang Longsor dan Rentan Tertimbun Longsor di daerah Aliran Sungai (DAS) Bompon, Kabupaten Magelang. Tesis. Universitas Gadjah Mada.
Regulation of the Head of the Geospatial Information Agency Number 15 of 2014. Concerning Technical Guidelines for Base Map Accuracy. Geospatial Information Agency. Bogor.
Regulation of the Head of the Geospatial Information Agency Number 6 of 2018. Concerning Amendments to Regulation of the Head of the Geospatial Information Agency Number 15 of 2014 concerning Technical Guidelines for Accuracy of Base Maps. Geospatial Information Agency. Bogor.
Setyawan, B. (2016). Landslide Risk Assessment Through Interpretation of 2D Small Format Aerial Photos Penilaian Risiko Longsor Melalui Interpretasi Foto Udara Format Kecil 2D. Tesis. Universitas Gadjah Mada.
Subasinghe, C. N., & Kawasaki, A. (2021). Assessment of physical vulnerability of buildings and socio-economic vulnerability of residents to rainfall induced cut slope failures: A case study in central highlands, Sri Lanka. International Journal of Disaster Risk Reduction. 65. https://doi.org/10.1016/j.ijdrr.2021.102550
Surya, E., Sri, D., & Artikel, S. (2019). Penerapan Model Statistik Multivariat dalam Studi Kerawanan Longsorlahan di Daerah Aliran Sungai Kodil, Jawa Tengah. 16(1), 16–24. https://doi.org/10.15294/jg.v16i1.4961
DOI: https://doi.org/10.22146/ijg.83487
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