The Use of Geographical Information System (GIS) and Remote Sensing (RS) Technologies in Generation of Information Used to Mitigate Risks from Landslide Disasters: An Application Review

Ameria Nabukonde

School of Sciences, Nkumba University, P.O.Box 237, Entebbe, Uganda.

Alex Barakagira *

School of Sciences, Nkumba University, P.O.Box 237, Entebbe, Uganda and Faculty of Science, Kyambogo University, P.O.Box 1, Kyambogo, Uganda.

Dammalie Akwango

National Agricultural Research Organization, P.O.Box 295, Entebbe, Uganda.

*Author to whom correspondence should be addressed.


Abstract

Landslides, whether induced by nature, or human activities, are one of the most prominent disasters which are of great concern in the world. They cause a lot of havoc to the environment hence a necessity to avoid them whenever possible. This literature review is basically aimed at finding out how Geographical Information System (GIS) and Remote Sensing (RS) technologies are used in avoiding landslides and risks associated with them at different levels; Challenges encountered while using GIS and RS techniques for landslide disaster risk reduction are identified; and therefore, dealing with them requires the involvement of developed countries who have the capacity to provide the necessary equipment to the developing countries that are faced with disasters. This study discusses the use of GIS and RS in mitigation of risks from landslides, and mainly points out how these techniques are applied to avoid disaster risks.  Secondary data was reviewed from journal articles, institutional reports, and online publications from similar studies. GIS and RS tools are important in predicting, monitoring and managing landslide disasters.  It was concluded that GIS and RS tools provide cheaper, reliable, and faster techniques of accessing spatial data in a given area, therefore regarded as essential technologies that may be necessary for predicting landslide occurrences, these technologies need to be considered in communities which are prone to landslides.

Keywords: Geographical information system, landslides, landslide disaster risk reduction, spatial data, remote sensing


How to Cite

Nabukonde , A., Barakagira , A., & Akwango , D. (2023). The Use of Geographical Information System (GIS) and Remote Sensing (RS) Technologies in Generation of Information Used to Mitigate Risks from Landslide Disasters: An Application Review. Archives of Current Research International, 23(2), 43–49. https://doi.org/10.9734/acri/2023/v23i2558

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References

Fathani TF, Karnawati D, Wilopo W. An integrated methodology to develop a standard for landslide early warning systems. Natural Hazards and Earth System Sciences. 2016;16(9): 2123-2135.

Ratemo S, Bamutaze Y. Spatial analysis of elements at risk and household vulnerability to landslide hazards on Mt. Elgon, Uganda. African Journal of Environmental Science and Technology. 2017;11(8): 438-447.

Van Westen CJ. Remote sensing for natural disaster management. International Archives of Photogrammetry and Remote Sensing. 2000;33(B7/4;PART 7):1609-1617.

Nor Diana MI, Muhamad N, Taha MR, Osman A, Alam M. Social vulnerability assessment for landslide hazards in Malaysia: A systematic review study. Land. 2021;10(3):315.

Mei G, Xu N, Qin J, Wang B, Qi P. A survey of Internet of Things (IoT) for geohazard prevention: Applications, technologies, and challenges. IEEE Internet of Things Journal. 2019;7(5):4371-4386.

Fathani TF, Karnawati D, Wilopo W. An adaptive and sustained landslide monitoring and early warning system. In Landslide science for a safer geo-environment. Springer, Cham. 2014;563-567.

Riegel RP, Alves DD, Schmidt BC, de Oliveira GG, Haetinger C, Osório DMM, de Quevedo DM. Assessment of susceptibility to landslides through geographic information systems and the logistic regression model. Natural Hazards. 2020; 103(1):497-511.

Cheung RW. Landslide risk management in Hong Kong. Landslides. 2021;18(10):3457-3473.

Haque U, Da Silva PF, Devoli G, Pilz J, Zhao B, Khaloua A, Glass GE. The human cost of global warming: Deadly landslides and their triggers (1995–2014). Science of the Total Environment. 2019;682:673-684.

Sarwar GM. Landslide tragedy of Bangladesh. In the first world landslide forum. 2008;11.

Haque U, Blum P, Da Silva PF, Andersen P, Pilz J, Chalov SR, Keellings D. Fatal landslides in Europe. Landslides. 2016; 13(6):1545-1554.

Rossi M, Guzzetti F, Salvati P, Donnini M, Napolitano E, Bianchi C. A predictive model of societal landslide risk in Italy. Earth-Science Reviews. 2019;196, 102849.

Igwe O. The characteristics and mechanisms of the recent catastrophic landslides in Africa under IPL and WCoE projects. Landsli; 2018.

Bizimana H, Sönmez O. Landslide occurrences in the hilly areas of Rwanda, their causes and protection measures. Disaster Science and Engineering. 2015; 1(1):1-7.

Leone S. Deadly landslide an avoidable tragedy. Green Left Weekly. 2017;1150:15.

Thiebes B, Bell R, Glade T, Jäger S, Mayer J, Anderson M, Holcombe L. Integration of a limit-equilibrium model into a landslide early warning system. Landslides. 2014;11(5):859-875.

Broeckx J, Maertens M, Isabirye M, Vanmaercke M, Namazzi B, Deckers J, Poesen J. Landslide susceptibility and mobilization rates in the Mount Elgon region, Uganda. Landslides. 2019;16(3): 571-584.

Osuret J, Atuyambe LM, Mayega RW, Ssentongo J, Tumuhamye N, Bua GM, Bazeyo W. Coping strategies for landslide and flood disasters: A qualitative study of Mt. Elgon Region, Uganda. PLoS currents. 2016;8.

Atuyambe LM, Ediau M, Orach CG, Musenero M, Bazeyo W. Land slide disaster in eastern Uganda: Rapid assessment of water, sanitation and hygiene situation in Bulucheke camp, Bududa district. Environmental Health. 2011;10(1):1-13.

United Nations Office for Disaster Risk Reduction (UNDRR) 24 April 2012. Using GIS for Disaster Risk Reduction.

Van Westen CJ. The modelling of landslide hazards using GIS. Surveys in Geophysics. 2000;21(2):241-255.

Twumasi NYD, Shao Z, Orhan A. Remote sensing and GIS methods in urban disaster monitoring and management–An overview. International Journal of Trend in Scientific Research and Development. 2019;3(4):918-926.

Tulsi Vyas, Aneri Desai. Information Technology for Disaster Management; 2007.

Vyas T, Desai A. Information technology for disaster management. In Proceedings of National Conference INDIACom; 2007.

Tanavud C, Yongchalermchai C, Bennui A, Navanugraha C. Application of GIS and remote sensing for landslide disaster management in southern Thailand. Journal of Natural Disaster Science. 2000;22(2): 67-74.

Meena SR, Albrecht F, Hölbling D, Ghorbanzadeh O, Blaschke T. Nepalese landslide information system (NELIS): A conceptual framework for a web-based geographical information system for enhanced landslide risk management in Nepal, Nat. Hazards Earth Syst. Sci. 2021; 21:301–316. Available:https://doi.org/10.5194/nhess-21-301-2021

Dinesh Pathak. Remote sensing and GIS application in landslide risk assessment and management; 2016.

Singhroy V. Satellite remote sensing applications for landslide detection and monitoring. In Landslides–disaster risk reduction. Springer, Berlin, Heidelberg. 2009;143-158.

Merrett HC, Chen WW. Applications of geographical information systems and remote sensing in natural disaster hazard assessment and mitigation in Taiwan. Geomatics, Natural Hazards and Risk. 2013;4(2):145-163.

Al Rawashdeh R, Campbell G, Titi A. The socio-economic impacts of mining on local communities: The case of Jordan. The Extractive Industries and Society. 2016; 3(2):494-507.

Schetselar EM. On preserving spectral balance in image fusion and its advantages for geological image interpretation. Photogrammetric Engineering and Remote Sensing. 2001; 67(8):925-934.

Lee S, Choi J, Min K. Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea. International Journal of Remote Sensing. 2004;25(11):2037-2052.

Lee SARO. Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. International Journal of Remote Sensing. 2005;26(7): 1477-1491.

Arnous MO. Integrated remote sensing and GIS techniques for landslide hazard zonation: A case study Wadi Watier area, South Sinai, Egypt. Journal of Coastal Conservation. 2011;15(4): 477-497.

Omieno K. Kelvin, Khabamba Innocent. ICT in disaster risk reduction: The Kenyan experience. International Journal of Disaster Management and Risk Reduction. 2012;4(2):ISSN: 1992-2744.

Bhavika Varma, Jeetendra Pande, Joshi VK. Use of IT for disaster management and mitigation. Proceedings of the 3rd National Conference; INDIACom. 2009; 2009.

Pradhan B, Mansor S, Pirasteh S, Buchroithner MF. Landslide hazard and risk analyses at a landslide prone catchment area using statistical based geospatial model. International Journal of Remote Sensing. 2011;32(14):4075-4087.

Ahmed B. Landslide susceptibility mapping using multi-criteria evaluation techniques in Chittagong Metropolitan Area, Bangladesh. Landslides. 2015;12(6): 1077-1095.

Mavroulis S, Lekkas E. Special issue on mapping, monitoring and assessing disasters. Applied Sciences. 2023;13(2): 963.

Fabbri AG, Chung CJF, Cendrero A, Remondo J. Is prediction of future landslides possible with a GIS? Natural Hazards. 2003;30:487-503.

Mersha T, Meten M. GIS-based landslide susceptibility mapping and assessment using bivariate statistical methods in Simada area, northwestern Ethiopia. Geo-environmental Disasters. 2020;7(1):1-22.

Ram L. Ray, Maurizio Lazzari, Tolulope Olutimehin. Remote Sensing Approaches and Related Techniques to Map and Study Landslides; 2020. DOI: 10.5772/intechopen.93681

Bello OM, Aina YA. Satellite remote sensing as a tool in disaster management and sustainable development: towards a synergistic approach. Procedia-Social and Behavioral Sciences. 2014;120:365-373.

Bang HN. Governance of disaster risk reduction in Cameroon: The need to empower local government. Jàmbá: Journal of Disaster Risk Studies. 2013; 5(2):1-10.