A Aplicação do índice estatístico e análise multicritério no mapeamento da suscetibilidade a deslizamentos, no município do Ipojuca, Pernambuco, Brasil
DOI:
https://doi.org/10.26848/rbgf.v17.2.p1015-1037Keywords:
suscetibilidade, deslizamentos, SIG, AHP, modelagem estatística, IpojucaAbstract
The present research aims to evaluate the performance of the application of the statistical bivariate analysis approach called Statistical Index (SI) integrated with the multicriteria analysis known as Analytic Hierarchy Process (AHP) in an urban expansion area in the municipality of Ipojuca, Pernambuco, Brazil, at a 1:10,000 scale. The research was based on the preparation and adaptation of thematic data to the mentioned scale, using orthophotomaps at a 1:1,000 scale and the Digital Terrain Model (DTM), which were generated by aerophotogrammetric survey and Light Detection and Ranging (LIDAR), respectively. It was observed that in the pilot area, landslides with a translational rupture surface parallel to the slope prevail, commonly triggered by rainfall and/or wastewater. Therefore, the following conditioning factors were used in the model: lithology, soils, land use and land cover, slope, and slope curvature, which were cross-referenced with the landslide inventory represented as point data on the rupture surface. The spatial unit was the grid cell (pixel). SI was used to determine the class weights for each conditioning factor, and the basic Accountability and Reliability indices, as well as the factor weights (Wf) generated based on the SI results, provided the degree of contribution of each conditioning factor to landslides and supported the completion of the paired comparison matrix of AHP. It was found that land use and land cover are more decisive in the occurrence of landslides, followed by slope, soil, curvature, and lithology. The model generated from the integration of the Statistical Index and AHP showed excellent performance with an AUC (Area Under the Curve) of 0.931 (93%) and outstanding performance with an AUC of 0.906 (90%) for the assessment of landslide susceptibility in the municipality of Ipojuca.
Downloads
References
Aleotti, P., R. & Chowdhury. (1999). Landslide Hazard Assessment: Summary Review and New Perspectives. Bulletin of Engineering Geology and the Environment, 58(1), 21–44.
https://doi.org/10.1007/s100640050066.
Aragão, M. L. & Duarte, C. C. (2023). Dinâmica climática, eventos extremos e impactos associados no município do Jaboatão dos Guararapes, Pernambuco, Brasil. Revista Brasileira de Geografia Física, 16(2), 818–836. https://doi.org/10.26848/rbgf.v16.2.p818-836.
Bandeira, A. P. N., & R. Q. Coutinho. (2015). Critical Rainfall Parameters : Proposed Landslide Warning System for the Metropolitan Region of Recife , PE , Brazil. Soils and Rocks. 38(1), 27–48. DOI: 10.28927/SR.381027
Barella, C. F., Sobreira, F. G. & Zêzere, J. L. (2019). A comparative analysis of statistical landslide susceptibility mapping in the southeast region of Minas Gerais state, Brazil. Bulletin of Engineering Geology and Environment, 78, 3205–3221. https://doi.org/10.1007/s10064-018-1341-3.
Berhane, G. E. & Tadesse, K. (2021). Landslide susceptibility zonation mapping using statistical index and landslide susceptibility analysis methods: A case study from Gindeberet district, Oromia Regional State, Central Ethiopia. Journal of African Earth Sciences. 180. https://doi.org/10.1016/j.jafrearsci.2021.104240.
Blahut, J. Van Westen, C.J., & Sterlacchini, S. (2010). Analysis of landslide inventories for accurate prediction of debris-flow source areas. Geomorphology. 119(1–2), 36-51. https://doi.org/10.1016/j.geomorph.2010.02.017.
Bonini, J. E., Bateira, C. V. D. M., Dias, V. C., Martins, T. D., & Vieira, B. C. Suscetibilidade a escorregamentos rasos a partir de parâmetros morfométricos e dos modelos SHALSTAB e do Valor Informativo. Confins, 46, 2020. https://doi.org/10.4000/confins.30323
Burrough, P. A. (1991). Principles of geographical information systems for land resources assessment. Oxford: Clarendon Press, 333 p. https://webapps.itc.utwente.nl/librarywww/papers_2009/general/principlesgis.pdf
Carvalho, C. S.; & Galvão, t. (Org.). (2006). Prevenção de risco de deslizamentos em encostas: guia para elaboração de políticas municipais. Brasília: Ministério das Cidades; Cities Alliance, 111 p.
Castellanos Abella, E.A. (2008). Provincial landslide risk assessment. In: Castellanos Abella, E.A., Multi-scale landslide risk assessment in Cuba, Utrecht, Utrecht University. ITC Dissertation 154, 101-152 p. https://www.researchgate.net/publication/43945886_Provincial_landslide_risk_assessment_THESIS_VERSION
Chung, C., & Fabbri, A.G. (2003). Validation of Spatial Prediction Models for Landslide Hazard Mapping. Natural Hazards, 30, 451-472. https://link.springer.com/content/pdf/10.1023/B:NHAZ.0000007172.62651.2b.pdf.
Corominas, J., van Westen, C., Frattini, P. et al. (2014). Recommendations for the quantitative analysis of landslide risk. Bull Eng Geol Environ, 73, 209–263 https://doi.org/10.1007/s10064-013-0538-8
Coutinho, R. Q. (Coord.). (2014). Carta geotécnica de aptidão à urbanização frente a desastres naturais do município do Ipojuca, Pernambuco: relatório técnico. Termo de Cooperação Ministério das Cidades e Universidade Federal de Pernambuco. Recife: GEGEP; UFPE.
Coutinho, R. Q., Henrique, H. M., Duarte, C. C., Nascimento, D. M. (2016). Risk mapping for landslides and erosion in the municipality of Ipojuca-PE—Rurópolis Community. In Aversa, S. et al. Landslides and Engineered Slopes. Experience, Theory and Practice. CRC Press, London. https://www.taylorfrancis.com/chapters/edit/10.1201/9781315375007-70/risk-mapping-landslides-erosion-municipality-ipojuca-pe%E2%80%94rur%C3%B3polis-community-coutinho-henrique-duarte-nascimento.
Cruden, D.M. & Varnes, D. (1996). Landslide Types and Processes. In Turner, A.K Schuster, R.L. (Eds). Landslides Investigation and Mitigation. National Academy Press, Special Report 247. Washington, p. 337-370. https://trid.trb.org/view/462501.
Dias, H.C., Hölbling, D., & Grohmann, C.H. (2021a). Landslide Susceptibility Mapping in Brazil: A Review. Geosciences, 11, 425. https://doi.org/10.3390/geosciences11100425.
Dias, H. C., Gramani, M .F., Grohmann, C. H., Vieira, B. C. (2021b). Statistical-based shallow landslide susceptibility assessment for a tropical environment: a case study in the southeastern Brazilian coast. Nat Hazards. 08, 205–223. https://doi.org/10.1007/s11069-021-04676-y.
Duarte, C. C., Nóbrega, R. S., Coutinho, R. Q., (2015). Análise climatológica e dos eventos extremos de chuva no município do Ipojuca, Pernambuco. Revista de Geografia (UFPE), [online] 32(2).
https://periodicos.ufpe.br/revistas/revistageografia/article/viewFile/229222/23602.
Esteves, L. V., Esteves, A. M. S. L., da Paz, D. H. F., & Coutinho, A. P. (2023). Caracterização Morfométrica e Uso do Solo da Bacia Hidrográfica do Rio Sirinhaém (BHRS), Pernambuco, Brasil. Revista Brasileira de Geografia Física, 16(5), 2609–2623. https://doi.org/10.26848/rbgf.v16.5.p2609-2623.
Fell, R., Corominas, J., Bonnard, C., Cascini, L., Leroi, E., & Savage, W. Z. (2008). Guidelines for landslide susceptibility, hazard and risk zoning for land use planning. Engineering Geology, 102 (3–4), 85-98. https://doi.org/10.1016/j.enggeo.2008.03.02.
Froude, M. J. & Petley, D. N (2018). Global fatal landslide occurrence from 2004 to 2016. Nat. Hazards Earth Syst. Sci., 18, 2161–2181. https://doi.org/10.5194/nhess-18-2161-2018.
Gama, W. M. & Falcão, N. A. M. (2023). Suscetibilidade a deslizamentos pelo método estatístico bivariado na bacia hidrográfica do Riacho do Silva, Maceió, Alagoas, Brasil. Revista Contexto Geográfico, 8(16), 46–61. https://doi.org/10.28998/contegeo.8i16.1548.
Garcia, R. A. C. (2012). Metodologias de avaliação da perigosidade e risco associado a movimentos de vertente: aplicação na bacia do rio Alenquer. 469 f. Tese (Doutorado em Geografia Física) – Universidade de Lisboa, Lisboa. https://repositorio.ul.pt/handle/10451/7377
Greenbaum, D., Bowker, M. R., Dau, I., Dropsy, H., Greally, K. B., Mcdonald, A., & Tragheim, D. G. (1995a). Rapid methods of landslide hazard mapping: Fiji case study. Technical Report WC/95/28, British Geological Survey (BGS), Natural Environmental Research Council, Keyworth, Nottingham. https://core.ac.uk/download/pdf/58059.pdf.
Greenbaum, D. et al. 1995b. Rapid methods for landslide hazard mapping: Papua New Guinea case study. Technical Report WC/95/27. British Geological Survey (BGS), Natural Environmental Research Council, Keyworth, Nottingham. https://nora.nerc.ac.uk/id/eprint/9967/1/WC95027.pdf
Guillard, G, & Zêzere, J. (2012). Landslide Susceptibility Assessment and Validation in the Framework of Municipal Planning in Portugal: The Case of Loures Municipality. Environmental management. 50, 721-35. https://link.springer.com/article/10.1007/s00267-012-9921-7.
Guzzetti, F. (2005). Landslide Hazard and Risk Assessment. Thesis Doctoral: 373. http://geomorphology.irpi.cnr.it/Members/fausto/PhD-dissertation.
Guzzetti, F., Reichenbach, P., Ardizzone, F., Cardinali, M., & Galli, M. (2006). Estimating the quality of landslide susceptibility models. Geomorphology, 81(1-2), 166-184. https://doi.org/10.1016/j.geomorph.2006.04.007.
Hungr, O., Leroueil, S. & Picarelli, L. (2014). The Varnes classification of landslide types, an update. Landslides, 11, 167–194. https://doi.org/10.1007/s10346-013-0436-y.
IBGE. Censo demográfico 2010: características da população e dos domicílios: resultados do universo. Rio de Janeiro, 2011. Não paginado.
IBGE. (2013) Manual técnico de uso da terra. 3. ed. 171 p. https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?id=281615&view=detalhes
IBGE (2018). População em áreas de risco no Brasil. https://www.ibge.gov.br/geociencias-novoportal/organizacao-do territorio/tipologias-doterritorio/21538-populacao-em-areas-de-risco-no-brasil.html?=&t=acesso-ao-produto
Kavzoglu, T., Kutlug Sahin, E. & Colkesen, I. 2015. An assessment of multivariate and bivariate approaches in landslide susceptibility mapping: a case study of Duzkoy district. Nat Hazards, 76, 471–496 https://doi.org/10.1007/s11069-014-1506-8.
Listo, F. L. & Santos, E. M. (2023). Scenarios of susceptibility to shallow landslides using the shalstab model and validation by roc curve, Metropolitan Region of Recife, Northeastern Brazil. Revista de Geografia (Recife). 40(1). https://doi.org/10.51359/22386211.2023.256630.
Macedo, E. S. & Sandre, L. H. (2022). Mortes por deslizamentos no Brasil: 1988 a 2022. Revista Brasileira de Geologia de Engenharia e Ambiental, 12(1), 110-117. https://www.abge.org.br/downloads/10.pdf.
Marengo, J. A., Alcantara, E., Cunha, A. P., M. Seluchi, Nobre, C. A., G. Dolif, Goncalves, D., Assis Dias, M., Cuartas, L.A., Bender, F., Ramos, A. M., Mantovani, J. R., Alvala, R. C., Moraes, O. L. (2023). Flash floods and landslides in the city of Recife, Northeast Brazil after heavy rain on May 25–28, 2022: Causes, impacts, and disaster preparedness. Water and Climate Extremes [Online], 39. https://www.sciencedirect.com/journal/weather-and-climate-extremes.
Melo, R., & Zêzere, J. L. (2017). Avaliação da suscetibilidade à rutura e propagação de fluxos de detritos na bacia hidrográfica do rio Zêzere (Serra da Estrela, Portugal). Revista Brasileira de Geomorfologia, 18(1). https://doi.org/10.20502/rbg.v18i1.985.
Mendes, R. M., Andrade, M. R. M., Tomasella, J., Moraes, M. A. E., & Scofield, G. B. (2018). Understanding shallow landslides in Campos do Jordão municipality – Brazil: disentangling the anthropic effects from natural causes in the disaster of 2000, Nat. Hazards Earth Syst. Sci., 18, 15–30, https://doi.org/10.5194/nhess-18-15-2018.
Moore, I. D.; & Grayson, R. B. (1991). Terrain-based catchment partitioning and runoff prediction using vector elevation data. Water Resources Research, 27(6), 1.171-1.191. https://doi.org/10.1029/91WR00090.
Myronidis, D., Papageorgiou, C., & Theophanous, S. (2016). Landslide susceptibility mapping based on landslide history and analytic hierarchy process (AHP). Nat Hazards. 81, 245–263. https://doi.org/10.1007/s11069-015-2075-1.
Nicu, I. C., & Asăndulesei, A. (2018). GIS-based evaluation of diagnostic areas in landslide susceptibility analysis of Bahluieț River Basin (Moldavian Plateau, NE Romania). Are Neolithic sites in danger?, Geomorphology, 314, 27-41. https://doi.org/10.1016/j.geomorph.2018.04.010.
Panchal, S., & Shrivastava, A. K. (2021). A Comparative Study of Frequency Ratio, Shannon’s Entropy and Analytic Hierarchy Process (AHP) Models for Landslide Susceptibility Assessment. ISPRS Int. J. Geo-Inf. 10, 603. https://www.mdpi.com/2220-9964/10/9/603
Pasang, S.; & Kubíček, P. (2020). Landslide Susceptibility Mapping Using Statistical Methods along the Asian Highway, Bhutan. Geosciences, 10, 430. https://doi.org/10.3390/geosciences10110430.
Pardeshi, S. D., Autade, S. E., & Pardeshi, S. (2013). Landslide Hazard Assessment: Recent Trends and Techniques. SpringerPlus 2(1): 1–23. https://doi.org/10.1186/2193-1801-2-523.
Pernambuco. (2016). Pernambuco Tridimensional: manual para obtenção dos dados. Consórcio Águas de Pernambuco, Governo do Estado de Pernambuco, Recife. http://www.pe3d.pe.gov.br/documentos/manual.pdf
Pfaltzgraff, P. A. S. (1998). Carta geotécnica e de suscetibilidade a processos geológicos do município de Ipojuca, Pernambuco. Recife: CPRM/Fidem, 18 p. https://rigeo.sgb.gov.br/bitstream/doc/17367/1/rel_carta_geotecnica_ipojucav2.pdf
Pfaltzgraff, P. A. S. (2007). Mapa de suscetibilidade a deslizamentos na região metropolitana do Recife. 153 p. Tese (Doutorado em Geociências). https://rigeo.cprm.gov.br/jspui/handle/doc/273
Santos, R. D., Santos, H. G., Ker, J. C., Anjos, L. H. C., & Shimizu, S. H. Manual de descrição e coleta de solos no campo. 7 ed. Sociedade Brasileira de Ciências do Solo. https://www.ofitexto.com.br/manual-de-descricao-e-coleta-de-solo-no-campo/p
Rai, D.K., Xiong, D., & Zhao, W. (2022). An Investigation of Landslide Susceptibility Using Logistic Regression and Statistical Index Methods in Dailekh District, Nepal. Chin. Geogr. Sci. 32, 834–851. https://doi.org/10.1007/s11769-022-1304-2.
Rasyid, A.R., Bhandary, N.P. & Yatabe, R. (2016). Performance of frequency ratio and logistic regression model in creating GIS based landslides susceptibility map at Lompobattang Mountain, Indonesia. Geoenviron Disasters, 3, 19. https://geoenvironmental-disasters.springeropen.com/articles/10.1186/s40677-016-0053-x.
Reichenbach, P., Rossi, M., Malamud, B. D., Mihir M., & Guzzetti, F. (2018). A Review of Statistically-Based Landslide Susceptibility Models. Earth-Science Reviews, 180, 60–91. https://doi.org/10.1016/j.earscirev.2018.03.001.
Rosa, M. L., Sobreira, F. G., & Barella, C. F. (2021). Landslide susceptibility mapping using the statistical method of Information Value: A study case in Ribeirão dos Macacos basin, Minas Gerais, Brazil. An Acad Bras Cienc 93(1). https://doi.org/10.1590/0001-3765202120180897.
Rossi, M. & Reichenbach, P. (2016). Land-se: a software for statistically based landslide susceptibility zonation, version 1.0, Geosci. Model, 9, 3533–3543. https://doi.org/10.5194/gmd-9-3533-2016.
Rossi, M., Bornaetxea, T., & Reichenbach, P. (2022). LAND-SUITE V1.0: a suite of tools for statistically based landslide susceptibility zonation. Geosci. Model Dev., 15, 5651–5666, https://doi.org/10.5194/gmd-15-5651-2022.
Saaty, R. W. (1987). The analytic hierarchy process—what it is and how it is used. Mathematical Modelling, 9,( 3–5), 161-176. https://doi.org/10.1016/027-255(87)90473-8.
Sabatakakis, N., Koukis, G., & Vassiliades, E. (2013). Landslide susceptibility zonation in Greece. Nat Hazards. 65, 523–543. https://doi.org/10.1007/s11069-012-0381-4.
SGB/CPRM - Serviço Geológico do Brasil. (1996). Mapa geológico das folhas Ipojuca/ Ponta da Gambôa e Sirinhaém- escala 1:25000. Recife: LAGESE, 53p. il. Lima Filho, M. (Org.)
Tating, F., & Hack, R. H. R. G. K. (2015). Landslide susceptibility assessment using information value statistical method: a case study on northern Kota Kinabalu, Sabah. Malaysian Journal of Remote Sensing & GIS. 4 (2), 94-111. https://www.researchgate.net/profile/Rabieahtul-Abu-Bakar/publication/330439928_MJRSGIS_vol_4_num_2/links/5c3ff79b299bf12be3cda65f/MJRSGIS-vol-4-num-2.pdf#page=49.
Torres, F. S. M., Coutinho, R. Q., Duarte, C. C., Menezes, J. B., Fonsêca, D. N., & Pfaltzgraf, P. A. S. (2015). Carta de suscetibilidade a movimentos de massa e erosão do município do Ipojuca-PE. Geotecnia, 135, 67-88. https://doi.org/10.24849/j.geot.2015.135.
Vakhshoori, V.; & Zare, M. (2018). Is the ROC curve a reliable tool to compare the validity of landslidesusceptibility maps? Geomatics, natural hazard and risk. 9(1), 249-266. https://doi.org/10.1080/19475705.2018.1424043.
Van Westen, C.J. (1993). Application of Geographical Information System to Landslide Hazard Zonation. ITC Publication, 15, 245. https://www.researchgate.net/publication/233865351_Application_of_Geographic_Information_Systems_to_Landslide_Hazard_Zonation.
Van, Westen, C.J. (1997). Statistical Landslide Hazard Analysis. Ilwis: 1–10. https://www.itc.nl/ilwis/applications-guide/application-5/.
Wanderley, L. S. A.; Nóbrega, R. S.; Duarte, C. C.; Moreira, A. B.; & Anjos, R. S. (2021). Weather Types Associated with Daily Intense Rainfall Events in The City of Recife - PE, Brazil. Sociedade & Natureza, 33(1). https://doi.org/10.14393/SN-v33-2021-60520.
Xavier, J. P. de S., Listo, F. de L. R., & Nery, T. D. (2022). Escorregamentos no estado de Pernambuco. Mercator, 21, https://doi.org/10.4215/rm2022.e21003.
Yalcin, A., S., Reis, A. C. Aydinoglu, & T. Yomralioglu. (2011). A GIS-Based Comparative Study of Frequency Ratio, Analytical Hierarchy Process, Bivariate
Statistics and Logistics Regression Methods for Landslide Susceptibility Mapping in Trabzon, NE Turkey.j Catena, 85(3), 274–87. http://dx.doi.org/10.1016/j.catena.2011.01.014.
Yalcin, A. (2008). GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations. Catena, 72, 1-12. https://doi.org/10.1016/j.catena.2007.01.003.
Yan, F., Zhang, Q., Ye, S., & Ren, B. (2019). A Novel Hybrid Approach for Landslide Susceptibility Mapping Integrating Analytical Hierarchy Process and Normalized Frequency Ratio Methods with the Cloud Model. Geomorphology, 327, 170–87.https://doi.org/10.1016/j.geomorph.2018.10.024.
Zevenbergen, L. W., & Thorne, C. R. (1987). Quantitative analysis of land surface topography. Earth surface processes and landforms, 12(1), 47-56. https://doi.org/10.1002/esp.3290120107.
Zêzere, J. L. (2002). Landslide susceptibility assessment considering landslide typology. A case study in the area north of Lisbon (Portugal), Nat. Hazards Earth Syst. Sci., 2, 73–82. https://doi.org/10.5194/nhess-2-73-2002.
Zêzere, J.L., Pereira, S., Melo, R., Oliveira, S.C., & Garcia., R.A.C. (2017). Mapping landslide susceptibility using data-driven methods. Science of The Total Environment, 589, 250-267. https://doi.org/10.1016/j.scitotenv.2017.02.188.
Zhang, G., Cai, Y., Zheng, Z., Zhen, J., Liu, Y. & Huang, K. (2016). Integration of the Statistical Index Method and the Analytic Hierarchy Process technique for the assessment of landslide susceptibility in Huizhou, China. Catena, 142, 233-244. https://doi.org/10.1016/j.catena.2016.03.028.
Zhu, A. X., Wang, R., Qiao, J., Qin, Cheng-Z., Chen, Y., Liu. J., Du, F., Lin, Y., & Zhu, T. (2014). An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic. Geomorphology, 214, 128-138. https://doi.org/10.1016/j.geomorph.2014.02.003.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Brazilian Journal of Physical Geography

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with Revista Brasileira de Geografia Física agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted to make their work available online before or during the editorial process, on academic social networks, digital repositories, or preprint servers. After publication in Revista Brasileira de Geografia Física, authors are expected to update the preprint or postprint versions on the platforms where they were originally made available, providing a link to the final published version and any other relevant information, with proper recognition of authorship and the initial publication in this journal.
You are free to:
Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
Adapt — remix, transform, and build upon the material for any purpose, even commercially.
The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.