Spatial study of environmental vulnerability to earthquakes based on vegetation conditions
DOI:
https://doi.org/10.61511/calamity.v3i2.2026.2559Keywords:
active fault, environmental vulnerability, spatial analysis, vegetationAbstract
Background: Earthquakes are among the most destructive natural hazards, causing not only structural damage and loss of life but also long-term environmental degradation and vegetation decline. The ecological dimension of seismic vulnerability has often been overlooked in spatial studies, particularly in tropical regions. This research aims to assess environmental vulnerability to earthquakes based on vegetation conditions along the Opak Fault in the Special Region of Yogyakarta, Indonesia. Methods: The study employs a quantitative–spatial approach using Geographic Information Systems (GIS) to analyze vegetation coverage within three buffer zones at radii of 2 km, 5 km, and 10 km from the active fault line. Secondary data from the Geospatial Information Agency (BIG) and PVMBG were processed to calculate the Environmental Vulnerability Index (EVI) using the ratio of vegetated area to total buffer area, expressed as a percentage. Findings: Results indicate that vulnerability decreases with distance from the fault: 49% (high) for 0–2 km, 45% (high) for 2–5 km, and 40% (moderate) for 5–10 km. The innermost zones, dominated by irrigated rice fields on saturated alluvial soils, exhibit the highest susceptibility to liquefaction and ground shaking. In contrast, areas with greater forest cover show higher ecological resilience. Conclusion: The findings underscore the need to integrate vegetation-based management and Ecosystem-Based Disaster Risk Reduction (Eco-DRR) strategies into local spatial planning to strengthen environmental resilience in seismically active regions. Novelty/Originality of this article: This study uniquely combines GIS-based spatial analysis with vegetation data to assess earthquake vulnerability, highlighting ecological factors often overlooked in seismic risk assessments and informing ecosystem-based disaster risk reduction strategies.
References
Andriani, R., Saputra, E., & Wibowo, A. (2023). Environmental degradation following the 2006 Yogyakarta earthquake: Impacts on vegetation and soil stability. Environmental Earth Sciences, 82(6), 301. https://doi.org/10.1007/s12665-023-10831-7
Bayless, J., & Abrahamson, N. (2019). Summary of the BA18 ground‐motion model for Fourier amplitude spectra for crustal earthquakes in California. Bulletin of the Seismological Society of America, 5, 2088-2105. https://doi.org/10.1785/0120190077
BMKG. (2024). Seismic activity and fault mapping in Java Island, Indonesia. Badan Meteorologi, Klimatologi, dan Geofisika.
Coelho, C., Da Silva, D., Amorim, R., Vasconcelos, B., Possato, E., Filho, E., Brandão, P., Neto, J., & Silva, L. (2024). Development and application of an Environmental Vulnerability Index (EVI) for identifying priority restoration areas in the São Francisco River Basin, Brazil. Land, 13(9), 1475. https://doi.org/10.3390/land13091475
Ding, C., Dong, J., Béon, M., Lee, C., Ho, S., & Wang, S. (2024). Characterization of the active fault deformation zone of the Chegualin Fault in the alluvial plain of southwestern Taiwan. Engineering Geology, 342, 107740. https://doi.org/10.1016/j.enggeo.2024.107740
Dorn, H., Törnros, T., & Zipf, A. (2015). Quality evaluation of VGI using authoritative data: A comparison with land use data in southern Germany. ISPRS International Journal of Geo-Information, 4, 1657–1671. https://doi.org/10.3390/ijgi4031657
Ekarsti, L. D., Hadiana, R., & Setiadi, M. (2023). Mapping seismic vulnerability zones of the Opak Fault, Yogyakarta, using microtremor analysis and GIS. Journal of Asian Earth Sciences, 252, 106485. https://doi.org/10.1016/j.jseaes.2023.106485
FAO. (2020). Restoration guidelines for ecosystem recovery after natural disasters. Food and Agriculture Organization.
Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2021). Quantitative geography: Spatial analysis and GIS applications. Sage Publications.
Gan, W., Liu, X., & Zhong, L. (2019). Vegetation recovery after the 2008 Wenchuan earthquake: A decadal perspective. Remote Sensing of Environment, 235, 111444. https://doi.org/10.1016/j.rse.2019.111444
Giuliani, G., Rodila, D., Külling, N., Maggini, R., & Lehmann, A. (2022). Downscaling Switzerland land use/land cover data using nearest neighbors and an expert system. Land, 11(5), 615. https://doi.org/10.3390/land11050615
Goodchild, M. F. (2021). Spatial data accuracy and uncertainty in environmental modelling. International Journal of Geographical Information Science, 35(9), 1735–1752. https://doi.org/10.1080/13658816.2021.1897642
Hadiana, R., Ekaristi, L. D., & Masykuri, M. (2021). Seismic hazard and liquefaction potential in Yogyakarta: Integrating soil and fault line mapping. Geotechnical and Geological Engineering, 39, 5483–5502. https://doi.org/10.1007/s10706-021-01751-1
He, X., Xu, C., Xu, X., & Yang, Y. (2022). Advances on the avoidance zone and buffer zone of active faults. Natural Hazards Research. https://doi.org/10.1016/j.nhres.2022.05.001
IFRC. (2022). Green response quick guide: Environmentally sustainable disaster response. International Federation of Red Cross and Red Crescent Societies.
IUCN. (2021). Guidelines for ecosystem-based disaster risk reduction and climate change adaptation. International Union for Conservation of Nature.
Jena, R., Pradhan, B., & Homaifar, A. (2020). Spatial multi-hazard vulnerability assessment using GIS and machine learning. Sustainability, 12(9), 3676. https://doi.org/10.3390/su12093676
Li, D., Chen, W., & Sun, H. (2021). Quantifying vegetation contribution to seismic ecological resilience in fault-affected regions. Ecological Indicators, 131, 108192. https://doi.org/10.1016/j.ecolind.2021.108192
Li, J., Zhang, H., & Xu, Q. (2022). Ordinal classification of environmental vulnerability in seismically active mountain regions. Environmental Monitoring and Assessment, 194(10), 667. https://doi.org/10.1007/s10661-022-10302-4
Liu, P., Pei, J., Guo, H., Tian, H., Fang, H., & Wang, L. (2022). Evaluating the accuracy and spatial agreement of five global land cover datasets in the ecologically vulnerable South China karst. Remote Sensing, 14, 3090. https://doi.org/10.3390/rs14133090
Liu, Z., Gan, W., & Zhong, L. (2023). Ten years of vegetation recovery after the Wenchuan earthquake: A multi-sensor analysis. Remote Sensing, 15(3), 655. https://doi.org/10.3390/rs15030655
Luo, M., Jia, X., Zhao, Y., Zhang, P., & Zhao, M. (2024). Ecological vulnerability assessment and its driving force based on ecological zoning in the Loess Plateau, China. Ecological Indicators, 159, 111658. https://doi.org/10.1016/j.ecolind.2024.111658
Mardiatno, D., Handayani, T., Susanto, D., Faida, L. R., Kusumasari, B., & Malawani, M. N. (2020). Earthquake vulnerability mapping in the at-risk Opak fault, Sengon village, Central Java, Indonesia. E3S Web of Conferences, 200, 01002. https://doi.org/10.1051/e3sconf/202020001002
Perrin, C., Waldhauser, F., & Scholz, C. (2020). The shear deformation zone and the smoothing of faults with displacement. Journal of Geophysical Research: Solid Earth, 126. https://doi.org/10.1029/2020JB020447
Phiri, D., Simwanda, M., Salekin, S., Nyirenda, V., Murayama, Y., & Ranagalage, M. (2020). Sentinel-2 data for land cover/use mapping: A review. Remote Sensing, 12, 2291. https://doi.org/10.3390/rs12142291
PVMBG. (2023). Peta sesar aktif Indonesia. Pusat Vulkanologi dan Mitigasi Bencana Geologi.
Saputra, E., Wibowo, A., & Andriani, R. (2020). Integrating vegetation dynamics and seismic hazard mapping for environmental risk assessment. Natural Hazards, 104(3), 2575–2593. https://doi.org/10.1007/s11069-020-04250-6
Sedaghati, F., & Pezeshk, S. (2023). Machine learning–based ground motion models for shallow crustal earthquakes in active tectonic regions. Earthquake Spectra, 39, 2406–2435. https://doi.org/10.1177/87552930231191759
Singh, R., & Kumar, D. (2022). Global review of vegetation response to earthquakes: Mechanisms and monitoring perspectives. Progress in Earth and Planetary Science, 9, 14. https://doi.org/10.1186/s40645-022-00477-5
Trevisan, D., Bispo, P., Almeida, D., Imani, M., Balzter, H., & Moschini, L. (2020). Environmental vulnerability index: An evaluation of water and vegetation quality in a Brazilian savanna and seasonal forest biome. Ecological Indicators, 112, 106163. https://doi.org/10.1016/j.ecolind.2020.106163
UNDRR. (2015). Sendai framework for disaster risk reduction 2015–2030. United Nations Office for Disaster Risk Reduction. https://www.undrr.org/publication/sendai-framework-disaster-risk-reduction-2015-2030
UNDRR. (2023). Global assessment report on disaster risk reduction 2023: Our world at risk. United Nations Office for Disaster Risk Reduction. https://www.undrr.org/gar
UNEP. (2020). Ecosystem-based approaches to disaster risk reduction: Implementing nature-based solutions. United Nations Environment Programme.
Wang, H., Yan, H., Hu, Y., Xi, Y., & Yang, Y. (2022). Consistency and accuracy of four high-resolution LULC datasets: Indochina Peninsula case study. Land, 11(5), 758 https://doi.org/10.3390/land11050758
Wang, J., Zhang, Y., & Huang, Q. (2024). GIS-based environmental vulnerability mapping in seismically active regions. International Journal of Applied Earth Observation and Geoinformation, 127, 103602. https://doi.org/10.1016/j.jag.2024.103602
Wang, S., Li, J., & Zhou, X. (2022). Spatial modelling of vegetation-based environmental resilience to earthquakes. Ecological Modelling, 471, 110008. https://doi.org/10.1016/j.ecolmodel.2022.110008
World Bank. (2020). Forest restoration following earthquake damage. World Bank. https://openknowledge.worldbank.org/bitstreams/8c320cbc-1c7f-5c93-bb50-efac712da17d/download
Zhao, D., Qu, C., Bürgmann, R., & Shan, X. (2023). Characterizing deep, shallow, and surface fault zone deformation of the 2021 Mw 7.4 Maduo earthquake. Seismological Research Letters, 95(1), 277–287. https://doi.org/10.1785/0220230115
Zhong, L., Gan, W., & Liu, Z. (2021). Post-earthquake vegetation succession as an indicator of ecosystem resilience. Ecological Indicators, 129, 107924. https://doi.org/10.1016/j.ecolind.2021.107924
Zhou, X., Li, J., & Wang, D. (2023). Quantitative classification of environmental vulnerability based on vegetation index and fault proximity. Sustainability, 15(3), 2121. https://doi.org/10.3390/su15032121
Zou, T., & Yoshino, K. (2017). Environmental vulnerability evaluation using a spatial principal components approach in the Daxing’anling region, China. Ecological Indicators, 78, 405–415. https://doi.org/10.1016/j.ecolind.2017.03.039
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