Automated calculation of the susceptibility to mass movements through the phyton/arcgis interface

Authors

DOI:

https://doi.org/10.5902/2236499489613

Keywords:

Mass movements, Modeling, Landsides, PhytonToobox

Abstract

This work aimed to develop and implement an algorithm in the Python language, which integrates the various steps to calculate the spatial distribution of the susceptibility to mass movements, automating the flow of tasks that characterizes the process. The structuring of the flow of operations was based on the logic of multicriteria assessment through weighted linear combination. The algorithm includes geoprocessing operations for the generation of information plans, standardization of variables, weighting of conditioning criteria and subsequent integration through the weighted average of factors. This algorithm was implemented in the Python programming language, including the use of modules and functions provided by the ArcPy package, and included as a tool (script tool) in the ArcGIS software through functionalities allowed by the possibility of creating and editing tools using scripts in Python. The tool was submitted to tests in two different case studies, as a way to simulate the use of the tool in real situations and to validate its operation through the analysis of products obtained in the process execution. The results demonstrated significant advantages in the use of the tool, mainly through efficiency and flexibility gains and support to the user. The tool proved to be effective in assisting policies for urban planning, territorial occupation and monitoring of geological risks, and can assist in assessments of the susceptibility to this type of phenomenon, which are essential for the consolidation of urban agglomerations and prevention of natural disasters.

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Author Biographies

Antônio Henrique Caldeira Jorge Neves, Discente

Graduated in Geological Engineering from the Federal University of Ouro Preto (2015), having completed a Bachelor's degree at the University of Queensland (2013/2014).

Master's degree from Northern Arizona University, with a dissertation entitled: "Spatiotemporal Variability and Demographic Characteristics of Transit-Based Job Accessibility: A GIS Assessment of the Public Transit System in Flagstaff, Arizona."

Academic experience in Geosciences, with an emphasis on Geoprocessing and Geographic Information Systems.

Maria Augusta Gonçalves Fujaco, Universidade Federal de Ouro Preto

She holds a PhD in Crustal Evolution and Natural Resources from the Federal University of Ouro Preto. She is currently an adjunct professor at the Federal University of Ouro Preto. She has experience in Geosciences, with an emphasis on Remote Sensing and Geoprocessing.

Mariangela Garcia Praça Leite, Universidade Federal de Ouro Preto

He holds a degree in Geology from the Federal University of Rio de Janeiro (1987), a master's degree in Sedimentary Petrology and Sedimentology from the Federal University of Ouro Preto (1990), and a PhD in Civil Engineering - Water Resources from the Federal University of Rio de Janeiro (2001). He is currently a Full Professor at the Federal University of Ouro Preto (UFOP). He has experience in Geosciences, with an emphasis on Environmental Geology and Watersheds, working mainly on the following topics: impacts of mining, erosion, river and lake water and sediment quality, environmental geochemistry, and environmental recovery.

References

ALI, S. A., PARVIN, F., VOJTEKOVÁ, J., COSTACHE, R., LINH, N. T. T., PHAM, Q. B., & GHORBANI, M. A. GIS-Based Landslide Susceptibility Modeling: A Comparison between Fuzzy Multi-Criteria and Machine Learning Algorithms, 12 (2), 857-876. Geoscience Frontiers. https://doi.org/10.1016/j.gsf.2020.09.004. 2020. DOI: https://doi.org/10.1016/j.gsf.2020.09.004

ASSIS DIAS, M. C. de, SAITO, S. M., ALVALÁ, R. C. dos S., SELUCHI, M. E., BERNARDES, T., CAMARINHA, P. I. M., & NOBRE, C. A. Vulnerability index related to populations atrisk for landslides in the Brazilian Early Warning System (BEWS). International Journal of Disaster Risk Reduction, 49 (July). https://doi.org/10.1016/j.ijdrr.2020.101742. 2020. DOI: https://doi.org/10.1016/j.ijdrr.2020.101742

BOUDET, F., MACDONALD, G. K., ROBINSON, B. E., & SAMBERG, L. H. Rural-urban connectivity and agricultural land management across the Global South. Global Environmental Change, (60). https://doi.org/10.1016/j.gloenvcha.2019.101982. 2020. DOI: https://doi.org/10.1016/j.gloenvcha.2019.101982

CAGLAR, A., & SCHILLER, N. G. Migrants & City-making. Dispossession, Displacement & Urban Regeneration. Duke University Press, 2018. DOI: https://doi.org/10.1515/9781478091028

COELHO, J.C.C. Lógica Fuzzy e Geoprocessamento na Determinação da Vulnerabilidade à Ocupação Direta dos Mangues na Bacia Hidrográfica do Anil, na Ilha de São Luís-MA .2008. 211p. Federal University of Maranhão, Maranhão, 2008.

CREPANI, E., MEDEIROS, J. S. De, HERNANDEZ FILHO, P., FLORENZANO, T. G., DUARTE, V., & BARBOSA, C. C. F. Sensoriamento Remoto e Geoprocessamento Aplicados ao Zoneamento Ecológico-Econômico e ao Ordenamento Territorial. Inpe (Inpe-8454-Rpq/722), 103. https://doi.org/INPE-8454-RPQ/722. 2001.

DAI, F. C., & LEE, C. F. Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong. Geomorphology, 42 (3–4), 213–228. https://doi.org/10.1016/S0169-555X(01)00087-3. 2002. DOI: https://doi.org/10.1016/S0169-555X(01)00087-3

ESRI – ENVIRONMENTAL SYSTEMS RESEARCH INSTITUTE. ArcGIS Help 10.2. Available: http://resources.arcgis.com/en/help/main/10.2/.

FARIA, A. L. L. de, SILVA, J. X. da, & GOES, M. H. de B. Áreas com susceptibilidade à erosão do solo na bacia hidrográfica do ribeirão do Espírito Santo, Juiz de Fora ( MG ). Caminhos De Geografia, 4 (9), 50–65. 2003. DOI: https://doi.org/10.14393/RCG4915308

FEIZIZADEH, B., SHADMAN ROODPOSHTI, M., JANKOWSKI, P., & BLASCHKE, T. A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping. Computers and Geosciences, 73, 208–221. https://doi.org/10.1016/j.cageo.2014.08.001. 2014. DOI: https://doi.org/10.1016/j.cageo.2014.08.001

FROUDE, M. J., & PETLEY, D. N. Global fatal landslide occurrence 2004 to 2016. Natural Hazards and Earth System Sciences Discussions, 1–44. https://doi.org/10.5194/nhess-2018-49. 2018. DOI: https://doi.org/10.5194/nhess-2018-49

FUCHS, S., KEILER, M., & GLADE, T. Editorial to the special issue on resilience and vulnerability assessments in natural hazard and risk analysis. Natural Hazards and Earth System Sciences, 17(7), 1203–1206. https://doi.org/10.5194/nhess-17-1203-2017. 2017. DOI: https://doi.org/10.5194/nhess-17-1203-2017

GIAMBELLUCA T.W., Chen Q., Frazier A.G., Price J.P., Chen Y.-L., Chu P.-S., Eischeid J.K., & Delparte D.M. Online Rainfall Atlas of Hawai‘i. Bulletin American Meteorological Society. (94):313-316. 2013. DOI: https://doi.org/10.1175/BAMS-D-11-00228.1

GOGUEN, J. A, ZADEH, L. A.. Fuzzy sets. Information and control, vol. 8 (1965), pp. 338–353. 1973. DOI: https://doi.org/10.1016/S0019-9958(65)90241-X

HEINECK C. A., LEITE C. A. D. S., SILVA M. A., & VIEIRA V. S. Mapa geológico do Estado de Minas Gerais. Belo Horizonte, Convênio COMIG/CPRM, 1 mapa geológico, escala 1:1.000.000. 2003.

HIJMANS, R. J., CAMERON, S. E., PARRA, J. L., JONES, P. G., & JARVIS, A. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25(15), 1965–1978. https://doi.org/10.1002/joc.1276. 2005. DOI: https://doi.org/10.1002/joc.1276

LONGLEY P. A., GOODCHILD M. F., MAGUIRE D. J., & RHIND, D. W. Geographic Information Systems & Science. Chichester, Wiley. 2010.

MARCELINO, E. V. Mapeamento de áreas susceptíveis a escorregamento no município de Caraguatatuba (SP) usando técnicas de Sensoriamento Remoto, 2003, São José dos Campos/SP. (INPE-12146-TDI/970). 2003.

MARTINI, L. C. P., UBERTI, A. A. A., SCHEIBE, L. F., COMIN, J. J., & OLIVEIRA, M. A. T. de. (2006). Avaliação da suscetibilidade a processos erosivos e movimentos de massa: decisão multicriterial suportada em sistemas de informações geográficas. Geologia USP. Série Científica, 6 (1), 41–52. https://doi.org/10.5327/s1519-874x2006000200004. DOI: https://doi.org/10.5327/S1519-874X2006000200004

MATEOS, R. M., LÓPEZ-VINIELLES, J., POYIADJI, E., TSAGKAS, D., SHEEHY, M., HADJICHARALAMBOUS, K., & HERRERA, G. Integration of landslide hazard into urban planning across Europe. Landscape and Urban Planning, 196 (July 2019). https://doi.org/10.1016/j.landurbplan.2019.103740. 2020. DOI: https://doi.org/10.1016/j.landurbplan.2019.103740

PEDROSA, M. A. F. Avaliação de Susceptibilidade a Movimentos de Massa e Erosãono Município de Ouro Preto / MG em escala regional. (Master´s dissertation). Federal University of Ouro Preto, Ouro Preto, 2013.

PINTO, R.C., CANEPARO, S.C., & PASSOS, E. Avaliação Multicritério integrada aos Sistemas de Informações Geográficas para geração de cenário de suscetibilidade a deslizamentos rápidos em vertentes. Jornadas Lusófonas de Ciências e Tecnologias. DOI : https://doi.org/10.14195/978-989-26-0983-6_4. 2014. DOI: https://doi.org/10.14195/978-989-26-0983-6_4

PRESS, F., SIEVER, R., GROTZINGER, J., & JORDAN, T. H. Para Entender a Terra - 4 edição - Press Siever Grotzinger e Jordan - Cap. 12. 2006.

SAATY, T. Analytical Hierarchy Process: Planning, Priority Setting, Resource Allocation. New York, McGraw-Hill. 287p. 1980.

SHERROD R. D., SINTON J. M., WATKINS S. E., & Brunt K. M. Geologic Map of the State of Hawai‘i. Reston, U.S. Geological Survey. 85p. 2007. DOI: https://doi.org/10.3133/ofr20071089

VANACÔR, R. N. Sensoriamento Remoto e Geoprocessamento aplicados ao mapeamento das áreas susceptíveis a movimento de massa na região nordeste do Estado do Rio Grande do Sul. (Master´s dissertation). Federal University of Rio Grande do Sul, Rio Grande do Sul, 2006.

VARNES, D. J. Landslide hazard zonation: a review of principles and practice. Paris, UNESCO/IAEG. 1984.

WALLEMACQ, P. Economic Losses, poverty and Disasters Center for Research on the Epidemiology of Disasters (CRED) UNISDR. https://doi.org/10.13140/RG.2.2.35610.08643. 2019.

ZÊZERE, J. L. Dinâmica de vertentes e riscos geomorfológicos. Lisboa, Centro de Estudos Geográficos. 129p. 2005.

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Published

2025-11-03

How to Cite

Neves, A. H. C. J., Fujaco, M. A. G., & Leite, M. G. P. (2025). Automated calculation of the susceptibility to mass movements through the phyton/arcgis interface. Geografia Ensino & Pesquisa, 29, e89613. https://doi.org/10.5902/2236499489613

Issue

Vol. 29 (2025): Publicação Contínua

Section

Geoinformação e Sensoriamento Remoto em Geografia

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