TY  - JOUR
T1  - Decadal evolution of GIS in disaster management and risk assessment
AU  - Tarhan, Çiğdem
AU  - Eminoğlu, Yusuf
PY  - 2025
DA  - July
Y2  - 2024
DO  - 10.26833/ijeg.1544048
JF  - International Journal of Engineering and Geosciences
JO  - IJEG
PB  - Murat YAKAR
WT  - DergiPark
SN  - 2548-0960
SP  - 173
EP  - 196
VL  - 10
IS  - 2
LA  - en
AB  - This study conducts a bibliometric analysis of the evolution of Geographic Information Systems (GIS) in disaster risk management and assessment over a 25-year period, from 2000 to 2024. Utilizing a dataset derived from academic publications indexed in prominent scientific databases, we examine the growth trajectory, thematic evolution, scholarly collaboration, and technological advancements within the field. Our findings reveal a significant increase in the volume of GIS-related research in disaster management, underscored by a shift from foundational applications toward the integration of cutting-edge computational techniques. Analysis of collaboration networks highlights the global nature of research efforts, demonstrating extensive international cooperation that transcends geographical and disciplinary boundaries. Thematic analysis indicates a progressive focus on vulnerability assessments, climate change impacts, and the incorporation of remote sensing and machine learning technologies, reflecting the field's response to emerging challenges and the dynamic landscape of disaster risk management. The study not only charts the historical development of GIS applications in this domain but also identifies key research trends, influential works, and potential future directions, underscoring the critical role of GIS in enhancing disaster resilience. This bibliometric perspective provides valuable insights into the maturation of GIS as an indispensable tool in disaster management and offers a roadmap for future research and technological innovation aimed at mitigating disaster risks and building resilient communities
KW  - GIS
KW  - Disaster Risk Management
KW  - Technological Advancements
KW  - Thematic Evolution
KW  - Bibliometric Analysis
CR  - Kwan, M. P., & Ransberger, D. M. (2010). LiDAR assisted emergency response: Detection of transport network obstructions caused by major disasters. Computers, Environment and Urban Systems, 34(3), 179–188. https://doi.org/10.1016/j.compenvurbsys.2010.02.001
CR  - McEntire, D. A. (2005). Why vulnerability matters: Exploring the merit of an inclusive disaster reduction concept. Disaster Prevention and Management: An International Journal, 14(2), 206–222. https://doi.org/10.1108/09653560510595209/full/html
CR  - Cutter, S. L. (2012). Hazards, vulnerability and environmental justice. Hazards, Vulnerability and Environmental Justice, 1–418. https://doi.org/10.4324/9781849771542
CR  - Coşkun, M., & Toprak, F. (2023). Coğrafi bilgi sistemleri (CBS) tabanlı orman yangını risk analizi: Bartın İli örneği. Geomatik, 8(3), 250–263. https://doi.org/10.29128/geomatik.1192219
CR  - Perry, R. W. (2007). What is a disaster?. In Handbooks of Sociology and Social Research (pp. 1–15). https://doi.org/10.1007/978-0-387-32353-4_1
CR  - Zerger, A., & Smith, D. I. (2003). Impediments to using GIS for real-time disaster decision support. Computers, Environment and Urban Systems, 27(2), 123–141. https://doi.org/10.1016/S0198-9715(01)00021-7
CR  - Sui, D. Z., & Sui, D. Z. (2008). The wikification of GIS and its consequences: Or Angelina Jolie’s new tattoo and the future of GIS. Computers, Environment and Urban Systems, 32(1), 1–5. https://doi.org/10.1016/j.compenvurbsys.2007.12.001
CR  - Zanuttigh, B., et al. (2014). THESEUS decision support system for coastal risk management. Coastal Engineering, 87, 218–239. https://doi.org/10.1016/j.coastaleng.2013.11.013
CR  - Napieralski, J., Barr, I., Kamp, U., & Kervyn, M. (2013). Remote sensing and GIScience in geomorphological mapping. In Treatise on Geomorphology: Volume 1-14, 1–14, 187–227. https://doi.org/10.1016/B978-0-12-374739-6.00050-6
CR  - Elwood, S. (2010). Mixed methods: Thinking, doing, and asking in multiple ways. In The SAGE Handbook of Qualitative Geography, 1, 94–114. Retrieved March 23, 2024, from https://www.torrossa.com/gs/resourceProxy?an=4913729&publisher=FZ7200#page=107
CR  - Cova, T. J. (1999). GIS in emergency management. Retrieved March 23, 2024, from https://www.geos.ed.ac.uk/~gisteac/gis_book_abridged/files/ch60.pdf
CR  - Miller, H. J., & Goodchild, M. F. (2015). Data-driven geography. GeoJournal, 80(4), 449–461. https://doi.org/10.1007/S10708-014-9602-6
CR  - Al Kalbanı, K., & Rahman, A. A. (2022). 3D city model for monitoring flash flood risks in Salalah, Oman. International Journal of Engineering and Geosciences, 7(1), 17–23. https://doi.org/10.26833/ijeg.857971
CR  - Morsy, S., & Hadi, M. (2022). Impact of land use/land cover on land surface temperature and its relationship with spectral indices in Dakahlia Governorate, Egypt. International Journal of Engineering and Geosciences, 7(3), 272–282. https://doi.org/10.26833/ijeg.978961
CR  - Yuan, M., & Nara, A. (2015). Space-Time Analytics of Tracks for the Understanding of Patterns of Life. In Space-Time Integration in Geography and GIScience (pp. 373–398). Springer Netherlands. https://doi.org/10.1007/978-94-017-9205-9_20
CR  - Tomaszewski, B. (2020). Geographic Information Systems (GIS) for Disaster Management. Geographic Information Systems (GIS) for Disaster Management. https://doi.org/10.4324/9781351034869/geographic-information-systems-gis-disaster-management-brian-tomaszewski
CR  - Cutter, S. L., Ash, K. D., & Emrich, C. T. (2014). The geographies of community disaster resilience. Global Environmental Change, 29, 65–77. https://doi.org/10.1016/j.gloenvcha.2014.08.005
CR  - Tate, E. (2013). Uncertainty Analysis for a Social Vulnerability Index. Annals of the Association of American Geographers, 103(3), 526–543. https://doi.org/10.1080/00045608.2012.700616
CR  - Batty, M. (2013). The New Science of Cities. The MIT Press. https://doi.org/10.7551/mitpress/9399.001.0001
CR  - Goodchild, M. F., & Glennon, J. A. (2010). Crowdsourcing geographic information for disaster response: a research frontier. International Journal of Digital Earth, 3(3), 231–241. https://doi.org/10.1080/17538941003759255
CR  - Kulkarni, A. V., Aziz, B., Shams, I., & Busse, J. W. (2009). Comparisons of Citations in Web of Science, Scopus, and Google Scholar for Articles Published in General Medical Journals. JAMA, 302(10), 1092–1096. https://doi.org/10.1001/JAMA.2009.1307
CR  - Harzing, A. W., & Alakangas, S. (2016). Google Scholar, Scopus and the Web of Science: a longitudinal and cross-disciplinary comparison. Scientometrics, 106(2), 787–804. https://doi.org/10.1007/S11192-015-1798-9/tables/4
CR  - Aksnes, D. W., Langfeldt, L., & Wouters, P. (2019). Citations, Citation Indicators, and Research Quality: An Overview of Basic Concepts and Theories. SAGE Open, 9(1). https://doi.org/10.1177/2158244019829575
CR  - Page, M. J., et al. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, n71. https://doi.org/10.1136/bmj.n71
CR  - van Eck, N. J., & Waltman, L. (2014). Visualizing Bibliometric Networks. In Measuring Scholarly Impact (pp. 285–320). Springer International Publishing. https://doi.org/10.1007/978-3-319-10377-8_13
CR  - van Eck, N. J., & Waltman, L. (2009). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/S11192-009-0146-3
CR  - Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
CR  - Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for Information Science and Technology, 62(7), 1382–1402. https://doi.org/10.1002/asi.21525
CR  - Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact?. Scientometrics, 105(3), 1809–1831. https://doi.org/10.1007/s11192-015-1645-z
CR  - Dai, F. C., Lee, C. F., & Ngai, Y. Y. (2002). Landslide risk assessment and management: an overview. Engineering Geology, 64(1), 65–87. https://doi.org/10.1016/S0013-7952(01)00093-X
CR  - Martínez, J., Vega-Garcia, C., & Chuvieco, E. (2009). Human-caused wildfire risk rating for prevention planning in Spain. Journal of Environmental Management, 90(2), 1241–1252. https://doi.org/10.1016/j.jenvman.2008.07.005
CR  - Guan, Q., et al. (2018). Source apportionment of heavy metals in agricultural soil based on PMF: A case study in Hexi Corridor, northwest China. Chemosphere, 193, 189–197. https://doi.org/10.1016/j.chemosphere.2017.10.151
CR  - Huang, Y., et al. (2018). Heavy metal pollution and health risk assessment of agricultural soils in a typical peri-urban area in southeast China. Journal of Environmental Management, 207, 159–168. https://doi.org/10.1016/j.jenvman.2017.10.072
CR  - Chuvieco, E., et al. (2010). Development of a framework for fire risk assessment using remote sensing and geographic information system technologies. Ecological Modelling, 221(1), 46–58. https://doi.org/10.1016/j.ecolmodel.2008.11.017
CR  - Alcántara-Ayala, I. (2002). Geomorphology, natural hazards, vulnerability and prevention of natural disasters in developing countries. Geomorphology, 47(2–4), 107–124. https://doi.org/10.1016/S0169-555X(02)00083-1
CR  - Babiker, I. S., Mohamed, M. A. A., Hiyama, T., & Kato, K. (2005). A GIS-based DRASTIC model for assessing aquifer vulnerability in Kakamigahara Heights, Gifu Prefecture, central Japan. Science of The Total Environment, 345(1–3), 127–140. https://doi.org/10.1016/j.scitotenv.2004.11.005
CR  - Benz, U. C., Hofmann, P., Willhauck, G., Lingenfelder, I., & Heynen, M. (2004). Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS Journal of Photogrammetry and Remote Sensing, 58(3–4), 239–258. https://doi.org/10.1016/j.isprsjprs.2003.10.002
CR  - Devkota, K. C., et al. (2013). Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling–Narayanghat road section in Nepal Himalaya. Natural Hazards, 65(1), 135–165. https://doi.org/10.1007/s11069-012-0347-6
CR  - Maanan, M., Saddik, M., Maanan, M., Chaibi, M., Assobhei, O., & Zourarah, B. (2015). Environmental and ecological risk assessment of heavy metals in sediments of Nador lagoon, Morocco. Ecological Indicators, 48, 616–626. https://doi.org/10.1016/j.ecolind.2014.09.034
CR  - Regmi, N. R., Giardino, J. R., & Vitek, J. D. (2010). Modeling susceptibility to landslides using the weight of evidence approach: Western Colorado, USA. Geomorphology, 115(1–2), 172–187. https://doi.org/10.1016/j.geomorph.2009.10.002
CR  - Saha, A. K., Gupta, R. P., Sarkar, I., Arora, M. K., & Csaplovics, E. (2005). An approach for GIS-based statistical landslide susceptibility zonation?with a case study in the Himalayas. Landslides, 2(1), 61–69. https://doi.org/10.1007/s10346-004-0039-8
CR  - Tran, P., Shaw, R., Chantry, G., & Norton, J. (2009). GIS and local knowledge in disaster management: a case study of flood risk mapping in Viet Nam. Disasters, 33(1), 152–169. https://doi.org/10.1111/j.1467-7717.2008.01067.x
CR  - Ullah, K., & Zhang, J. (2020). GIS-based flood hazard mapping using relative frequency ratio method: A case study of Panjkora River Basin, eastern Hindu Kush, Pakistan. PLoS One, 15(3), e0229153. https://doi.org/10.1371/journal.pone.0229153
CR  - Remondo, J., Bonachea, J., & Cendrero, A. (2008). Quantitative landslide risk assessment and mapping on the basis of recent occurrences. Geomorphology, 94(3–4), 496–507. https://doi.org/10.1016/j.geomorph.2006.10.041
CR  - Kusak, L., Unel, F. B., Alptekin, A., Celik, M. O., & Yakar, M. (2021). Apriori association rule and K-means clustering algorithms for interpretation of pre-event landslide areas and landslide inventory mapping. Open Geosciences, 13(1), 1226-1244
CR  - Dahal, R. K., Hasegawa, S., Nonomura, A., Yamanaka, M., Dhakal, S., & Paudyal, P. (2008). Predictive modelling of rainfall-induced landslide hazard in the Lesser Himalaya of Nepal based on weights-of-evidence. Geomorphology, 102(3–4), 496–510. https://doi.org/10.1016/j.geomorph.2008.05.041
CR  - Umar, Z., Pradhan, B., Ahmad, A., Jebur, M. N., & Tehrany, M. S. (2014). Earthquake induced landslide susceptibility mapping using an integrated ensemble frequency ratio and logistic regression models in West Sumatera Province, Indonesia. Catena (Amst), 118, 124–135. https://doi.org/10.1016/j.catena.2014.02.005
CR  - Mishra, K., & Sinha, R. (2020). Flood risk assessment in the Kosi megafan using multi-criteria decision analysis: A hydro-geomorphic approach. Geomorphology, 350, 106861. https://doi.org/10.1016/j.geomorph.2019.106861
CR  - Abdulwahid, W. M., & Pradhan, B. (2017). Landslide vulnerability and risk assessment for multi-hazard scenarios using airborne laser scanning data (LiDAR). Landslides, 14(3), 1057–1076. https://doi.org/10.1007/s10346-016-0744-0
CR  - Remondo, J., Bonachea, J., & Cendrero, A. (2005). A statistical approach to landslide risk modelling at basin scale: from landslide susceptibility to quantitative risk assessment. Landslides, 2(4), 321–328. https://doi.org/10.1007/s10346-005-0016-x
CR  - Yakar, M., Yılmaz, H. M., & Mutluoǧlu, Ö. (2010). Comparative evaluation of excavation volume by TLS and total topographic station based methods
CR  - Bou Kheir, R., Cerdan, O., & Abdallah, C. (2006). Regional soil erosion risk mapping in Lebanon. Geomorphology, 82(3–4), 347–359. https://doi.org/10.1016/j.geomorph.2006.05.012
CR  - Thiery, Y., Malet, J.-P., Sterlacchini, S., Puissant, A., & Maquaire, O. (2007). Landslide susceptibility assessment by bivariate methods at large scales: Application to a complex mountainous environment. Geomorphology, 92(1–2), 38–59. https://doi.org/10.1016/j.geomorph.2007.02.020
CR  - Shahabi, H., Khezri, S., Bin Ahmad, B., & Hashim, M. (2014). RETRACTED: Landslide susceptibility mapping at central Zab basin, Iran: A comparison between analytical hierarchy process, frequency ratio and logistic regression models. Catena (Amst), 115, 55–70. https://doi.org/10.1016/j.catena.2013.11.014
CR  - Zou, Q., Cui, P., He, J., Lei, Y., & Li, S. (2019). Regional risk assessment of debris flows in China—An HRU-based approach. Geomorphology, 340, 84–102. https://doi.org/10.1016/j.geomorph.2019.04.027
CR  - Erkal, T., & Yildirim, U. (2012). Soil Erosion Risk Assessment in the Sincanlı Sub-Watershed of the Akarçay Basin (Afyonkarahisar, Turkey) Using the Universal Soil Loss Equation (USLE). Ekoloji, 21(84), 18–29. https://doi.org/10.5053/ekoloji.2012.843
CR  - Ünel, F. B., Kuşak, L., Yakar, M., & Doğan, H. Coğrafi bilgi sistemleri ve analitik hiyerarşi prosesi kullanarak Mersin ilinde otomatik meteoroloji gözlem istasyonu yer seçimi. Geomatik, 8(2), 107-123
CR  - Abbasnia, A., et al. (2018). Groundwater quality assessment for irrigation purposes based on irrigation water quality index and its zoning with GIS in the villages of Chabahar, Sistan and Baluchistan, Iran. Data Brief, 19, 623–631. https://doi.org/10.1016/j.dib.2018.05.061
CR  - Shalyari, N., Alinejad, A., Hashemi, A. H. G., RadFard, M., & Dehghani, M. (2019). Health risk assessment of nitrate in groundwater resources of Iranshahr using Monte Carlo simulation and geographic information system (GIS). MethodsX, 6, 1812–1821. https://doi.org/10.1016/j.mex.2019.07.024
CR  - Goodchild, M. F., Anselin, L., & Deichmann, U. (1993). A Framework for the Areal Interpolation of Socioeconomic Data. Environment and Planning A: Economy and Space, 25(3), 383–397. https://doi.org/10.1068/a250383
CR  - Cutter, S. L. (2006). Hazards Vulnerability and Environmental Justice. Routledge. https://doi.org/10.4324/9781849771542
CR  - Demir, M., & Altaş, N. T. (2024). Kars kentinde deprem hasar risk potansiyeli taşıyan alanların CBS tabanlı AHP analizlerine dayalı olarak belirlenmesi. Geomatik, 9(1), 123–140. https://doi.org/10.29128/geomatik.1375650
CR  - Hamilton, J. D. (2003). Exploring Technical and Cultural Appeals in Strategic Risk Communication: The Fernald Radium Case. Risk Analysis, 23(2), 291–302. https://doi.org/10.1111/1539-6924.00309
CR  - (2014). Summary for Policymakers. In Climate Change 2013 – The Physical Science Basis. Cambridge University Press. https://doi.org/10.1017/CBO9781107415324.004
CR  - Yilmaz, H. M., Yakar, M., Mutluoglu, O., Kavurmaci, M. M., & Yurt, K. (2012). Monitoring of soil erosion in Cappadocia region (Selime-Aksaray-Turkey). Environmental Earth Sciences, 66, 75-81.
CR  - Barton, S., & Pineo, R. (2023). Human Benefits of Green Spaces | Cooperative Extension | University of Delaware. Retrieved September 24, 2023, from https://www.udel.edu/academics/colleges/canr/cooperative-extension/fact-sheets/human-benefits-of-green-spaces/
CR  - Cooper, R. (2022). Coronavirus: Scientists reveal reduction in global air pollution and nitrogen dioxide levels. Retrieved April 5, 2022, from https://www.climateaction.org/news/coronavirus-scientists-reveal-reduction-in-global-air-pollution-and-nitrogen-dioxide-levels
CR  - Partigöç, N. S., & Dinçer, C. (2024). The Multi–Disaster risk assessment: A-GIS based approach for Izmir City. International Journal of Engineering and Geosciences, 9(1), 61-76. https://doi.org/10.26833/ijeg.1295657
CR  - Polat, Z. A., Kırtıloğlu, O. S., & Kayalık, M. (2023). Evolution and future trends in global research on geographic information system (GIS): a bibliometric analysis. Advanced GIS, 3(1), 22–30. Retrieved from https://publish.mersin.edu.tr/index.php/agis/article/view/886
CR  - Şahin, M. A. ., & Yakar, M. (2021). WebGIS technology and architectures. Advanced GIS, 1(1), 22–26. Retrieved from https://publish.mersin.edu.tr/index.php/agis/article/view/63
CR  - Partigöç, N. S., & Dinçer, C. (2024). Coğrafi bilgi sistemleri (CBS) tabanlı afet risk analizi: Denizli ili örneği. Geomatik, 9(1), 27-44. https://doi.org/10.29128/geomatik.1261051
 
Adesina E., Ajayi O, Odumosu J & Illah A (2023). GIS-based soil loss estimation using revised universal soil loss equation (RUSLE). Intercontinental Geoinformation Days (IGD), 7, 44-48, Peshawar, Pakistan
CR  - Kankanamge , H. P. N. K. ., & Mahmood, S. (2024). Post-Flood Disaster Management Challenges and Issues in the Bulathsinghala Divisional Secretariat Division, Sri Lanka: A Comprehensive Analysis and Strategic Framework for Resilience and Recovery. Advanced Geomatics, 4(1), 09–16. Retrieved from https://publish.mersin.edu.tr/index.php/geomatics/article/view/1092
CR  - Noor, S., Mahmood, S., & Habib, W. (2024). Risk Assessment of Attabad lake Outburst Flooding using integrated Hydrological and Geo-spatial Approach. Advanced Geomatics, 4(1), 57–67. Retrieved from https://publish.mersin.edu.tr/index.php/geomatics/article/view/1322
CR  - Gull, A., Liaqut, A., & Mahmood, S. (2023). Landslide Risk Assessment using Geo-spatial Technique: A study of District Abbottabad, Khyber Pakhtunkhwa, Pakistan. Advanced Geomatics, 3(2), 47–55. Retrieved from https://publish.mersin.edu.tr/index.php/geomatics/article/view/983
UR  - https://doi.org/10.26833/ijeg.1544048
L1  - https://dergipark.org.tr/en/download/article-file/4192815
ER  -