Ecological vulnerability in landslide risk measurement in the municipality of Barra do Turvo, São Paulo, Brazil
DOI:
https://doi.org/10.26848/rbgf.v18.4.p2621-2639Keywords:
Ecological values, susceptibility, remote sensing, Geographic Information Systems (GIS), three-dimensional modelAbstract
Landslides are one of the main types of geological disasters. They can result in material, economic, and life losses, as well as negatively impact the ecosystem and its services. This study establishes a three-dimensional model for assessing the ecological risk by landslide susceptibility, ecological vulnerability, and local population exposure. The ecological vulnerability assessment considered ecological values and regeneration delay. The model was applied in Barra do Turvo, a municipality in the state of São Paulo, Brazil, and situated in the Serra do Mar mountain range, which has records of previous landslides. The ecological vulnerability results showed that the territory presented a distribution of 45.55% low vulnerability and 41.96% moderate vulnerability, while only 11.56%, 0.82%, and 0.10% exhibited high, very low, and very high vulnerability indices, respectively. The study demonstrates that, despite the predominantly low ecological vulnerability of the study area, ecosystem conservation is still extremely important, as conserved ecosystems can mitigate risks and reduce environmental damage. The results obtained for risk were: 25.55% low risk; 23.01% moderate risk; and 20.15% high risk, with the very low and very high classes representing 15.47% and 15.82% respectively. In conclusion, we highlight the possibility of applying the proposed model in other locations, due to the use of open-access data, and the potential for it to be used by public managers to direct actions aimed at reducing risks.
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References
Aguirra, I.C.R., 2020. Rural livelihoods in the Ribeira Valley: differences in the use of forest resources and effects of the Bolsa Familia Program on subsistence practices and food security. Master’s Thesis, Instituto de Energia e Ambiente, Universidade de São Paulo, São Paulo. https://doi.org/10.11606/D.106.2020.tde-11082020-134735.
APRB. Autopista Régis Bittencourt, 2019. Gestão da segurança dos taludes rodoviários da rodovia Régis Bittencourt, trecho da Serra do Mar PR-SP: estudos probabilísticos e monitoramento geológico-geotécnico para mensuração de riscos através de critérios econômicos. Relatório Final de Recursos de Desenvolvimento Tecnológico. Curitiba,
Arrogante-Funes, P., Bruzón, A.G., Arrogante-Funes, F., Ramos-Bernal, R.N., Vázquez-Jiménez, R., 2021. Integration of vulnerability and hazard factors for landslide risk assessment. International Journal of Environmental Research and Public Health, 18. https://doi.org/10.3390/ijerph182211987.
Bielski, C., López-Vázquez, C., Grohmann, C. H., Guth, P.L., Group, T.T., 2023. DEMIX Wine Contest Method Ranks ALOS AW3D30, COPDEM, and FABDEM as Top 1''Global DEMs. arXiv preprint arXiv:2302.08425.
Bim, O.J.B., 2012. Mosaico do Jacupiranga - Vale do Ribeira / SP: conservação, conflitos e soluções socioambientais. Master’s Thesis, Universidade de São Paulo, São Paulo. https://doi.org/10.11606/issn.1808-1150.v0i18p4-36.
Brang, P., 2001. Resistance and elasticity: promising concepts for the management of protection forests in the European Alps. For Ecol Manage, 145, 107–119. https://doi.org/10.1016/S0378-1127(00)00578-8.
Cao, M., Prince, S.D., Small, J., Goetz, S.J., 2004. Remotely Sensed Interannual Variations and Trends in Terrestrial Net Primary Productivity 1981-2000. Ecosystems, 7, 3. https://doi.org/10.1007/s10021-003-0189-x.
Carvalho, N.O., 2008. Hidrossedimentologia prática. Editora Interciência. Rio de Janeiro.
CBH-RB. Comitê da Bacia Hidrográfica do Ribeira de Iguape e Litoral Sul, 2012. Caderno de informações sobre a Bacia da Unidade de Gerenciamento de Recursos Hídricos nº 11. Associação dos Mineradores de Areia do Vale do Ribeira e Baixada Santista.
Cerri, R.I., Reis, F.A.G.V., Gramani, M.F., Rosolen, V., Luvizotto, G.L., Do Carmo Giordano, L., Gabelini, B.M., 2018. Assessment of landslide occurrences in Serra do Mar Mountain range using kinematic analyses. Environ. Earth Sci., v. 77, p. 1-16, 2018. https://doi.org/10.1007/s12665-018-7508-1.
Chen, S., Chen, B., Fath, B.D., 2013. Ecological risk assessment on the system scale: A review of state-of-the-art models and future perspectives. Ecol. Model., 250, 25-33. https://doi.org/10.1016/j.ecolmodel.2012.10.015.
Chuvieco, E., Martínez, S., Román, M.V., Hantson, S., Pettinari, M.L., 2014. Integration of ecological and socio‐economic factors to assess global vulnerability to wildfire. Global Ecology and Biogeography, 23, 2, 245-258. https://doi.org/10.1111/geb.12095.
CRED. Centre for Research on the Epidemiology of Disaster, 2015. The Human Cost of Natural Disasters: A Global Perspective. Brussels, Belgium.
Cruden, D.M., Varnes, D.J, 1996. Chapter 3 landslide types and processes. Landslides: Investigation and Mitigation, Transportation Research Board Special Report 247, Washington, 36-75.
Dalmas, F.B., 2013. Análise da evolução do uso e ocupação do solo na UGRHI-11 e avaliação de cenários futuros em função de processos erosivos e de movimentos de massa utilizando técnicas de geoprocessamento. Doctoral Thesis, Instituto de Geociências da Universidade de São Paulo, São Paulo. https://doi.org/10.11606/T.44.2013.tde-11122013-101243.
De Lange, H.J., Sala, S., Vighi, M., Faber, J.H., 2010. Ecological vulnerability in risk assessment - A review and perspectives. Science of the total environment, 408, 18, 871-3879. https://doi.org/10.1016/j.scitotenv.2009.11.009.
Duro, D.C., Coops, N.C., Wulder, M.A., Han, T., 2007. Development of a large area biodiversity monitoring system driven by remote sensing. Progress in Physical Geography, 31, 3, 235-260. https://doi.org/10.1177/03091333070790.
Eastman, R., 2006. Guide to GIS and image processing: IDRISI Andes Manual: Version 15.0. Clarck labs of Clark Univesity, Massachusetts, 284.
EMBRAPA. Empresa Brasileira de Pesquisa Agropecuária, 2013. Sistema Brasileiro de classificação de solos. Rio de Janeiro: Centro Nacional de Pesquisa de Solos.
EMBRAPA. Empresa Brasileira de Pesquisa Agropecuária, 2020. Mapa da Erodibilidade dos Solos à Erosão Hídrica do Brasil. Available at: https://geoinfo.dados.embrapa.br/catalogue/#/dataset/2997. Accessed: Aug 27, 2024.
Faleiros, F., Pavan, M., 2013. Geologia e recursos minerais da folha Eldorado Paulista SG. 22-XB-VI.
Farina, A., 2006. Principles and methods in landscape ecology. Dordrecht: Springer Netherlands.
França, A.M., 2005. Vale do Ribeira (SP): Proposições econômicas, sociais, políticas e ambientais para o crescimento e desenvolvimento sustentável dos municípios da região administrativa de Registro. Master’s Thesis, Pontifícia Universidade Católica, São Paulo.
Guillard-Goncąlves, C., Cutter, S.L., Emrich, C.T., Zêzere, J.L., 2014. Application of Social Vulnerability Index (SoVI) and delineation of natural risk zones in Greater Lisbon, Portugal. Journal of Risk Research, 18, 5, 651-674. https://doi.org/10.1080/13669877.2014.910689.
Hawker, L., Neal, J., 2021. FABDEM V1-0. University of Bristol.
He, L., Shen, J., Zhang, Y., 2018. Ecological vulnerability assessment for ecological conservation and environmental management. Journal of environmental management, 206, 1115-1125. https://doi.org/10.1016/j.jenvman.2017.11.059.
Hunter, M., Calhoun, A.J.K., Szaro, R.C., Johnston, D.W., 1996. A triad approach to land-use allocation. A triad approach to land-use allocation., 477-491.
IBGE. Instituto Brasileiro de Geografia e Estatística, 2006, Unidades de Relevo 1:5.000.000. Available at: https://www.ibge.gov.br/geociencias/informacoes-ambientais/geomorfologia/15827-unidades-de-relevo.html?=&t=acesso-ao-produto. Accessed: Aug 27, 2024.
IBGE. Instituto Brasileiro de Geografia e Estatística, 2022. Censo 2022. Available at: https://censo2022.ibge.gov.br/panorama/. Accessed: Aug 27, 2024.
Kurki, S.P., Nikula, A., Helle, P., Lindén, H., 2000. Landscape Fragmentation and Forest Composition Effects on Grouse Breeding Success in Boreal Forests. Ecology, 81, 7, 1985-1997. https://doi.org/10.1890/0012-9658(2000)081[1985:LFAFCE]2.0.CO;2.
Lacerda, W.A., Palmeira, E.M., Netto, A.L.C., Ehrlich, M. (Eds.), 2014. Extreme rainfall induced landslides: an international perspective. Oficina de Textos, São Paulo.
Lin, J., Lin, M., Chen, W., Zhang, A., Qi, X., Hou, H., 2021. Ecological risks of geological disasters and the patterns of the urban agglomeration in the Fujian Delta region. Ecological Indicators, 125, 107475. https://doi.org/10.1016/j.ecolind.2021.107475
Medeiros, R., 2003. A Proteção da natureza: das estratégias internacionais e nacionais às demandas locais. Doctoral Thesis Universidade Federal do Rio de Janeiro, Rio de Janeiro.
Opdam, P., Steingröver, E., Rooij, S., 2006. Ecological networks: A spatial concept for multi-actor planning of sustainable landscapes. Landscape and Urban Planning, 75, 3-4, 322-332. https://doi.org/10.1016/j.landurbplan.2005.02.015.
Panagos, P., Hengl, T., Wheeler, I., et al., 2023. Global rainfall erosivity database (GloREDa) and monthly R-factor data at 1 km spatial resolution. Data in Brief, 50, 109482. https://doi.org/10.1016/j.dib.2023.109482.
Renaud, F.G., Sudmerier-Rieux, K., Estrella, M. (Eds.), 2013. The role of ecosystems in disaster risk education dissertation. United Nations University Press.
Riedel, P.S., Gomes, A.R., Ferreira, M.V., Sampaio Lopes, E.S., Sturaro, J.R., 2010. Identification of landslide scars in the region of the Serra do Mar, São Paulo State, Brazil, using digital image processing and spatial analysis tools. GIScience Remote Sens., 47, 498-513. https://doi.org/10.2747/1548-1603.47.4.498.
Riitters, K.H., Wickham, J.D., Wade, T.G., 2009. An indicator of forest dynamics using a shifting landscape mosaic. Ecological Indicators, 9, 1, 107-117. https://doi.org/10.1016/j.ecolind.2008.02.003.
Rong, G., Li, K., Han, L., Alu, S., Zhang, J., 2020. Hazard mapping of the rainfall-landslides disaster chain based on geodetector and bayesian network models in Shuicheng County, China. Water (Switzerland), 12, 9, 2572. https://doi.org/10.3390/w12092572. Accessed:
Ross, J.L.S., 2002. A Morfogênese da bacia do Ribeira do Iguape e os sistemas ambientais. Geousp: Espaço e Tempo (Online), 6, 2, 21-46. https://doi.org/10.11606/issn.2179-0892.geousp.2002.123770.
Rousselet-Gadenne, A., 2004. Etude originale Adoption d’innovations agroforestières à Barra do Turvo (Sao Paulo, Brésil). Cahiers Agricultures, 13, 391-402.
Running, S.W., Zhao, M., 2021. User’s Guide Daily GPP and Annual NPP (MOD17A2H/A3H) and Year-end GapFilled (MOD17A2HGF/A3HGF) Products NASA Earth Observing System MODIS Land Algorithm (For Collection 6) Process. DAAC. Available at: https://lpdaac.usgs.gov/documents/972/MOD17_User_Guide_V61.pdf. Accessed: Aug 27, 2024.
Soille, P., Vogt, P., 2009. Morphological segmentation of binary patterns. Pattern Recognition Letters, 30, 4, 456-459. https://doi.org/10.1016/j.patrec.2008.10.015.
SSE. Secretaria de Saneamento e Energia, 2010. Plano regional integrado de saneamento básico para UGRHI 11. São Paulo, Brasil.
Stuart Chapin, F., Matson, P.A., Vitousek, P.M., 2012. Principles of terrestrial ecosystem ecology. Principles of Terrestrial Ecosystem Ecology. Springer. New York, 1-529.
Thapa, P.S., Daimaru, H., Yanai, S., 2024. Analyzing vegetation recovery and erosion status after a large Landslide at Mt. Hakusan, Central Japan. Ecological Engineering, 198, 107144.
UNEP-WCMC. United Nations Environment Programme - World Conservation Monitoring Centre, 2023. Protected Planet: The World Database on Protected Areas (WDPA).
Vogt, P., 2023. User guide of GuidosToolbox: release 3.2, revision 1. Ispra, European Commission, Joint Research Centre, Institute for Environment and Sustainability, Forest Resources and Climate Unit.
Xiong, X., Wolfe, R., Barnes, W., Guenther, B., Vermote, E., Saleous, N., Salomonson, V., 2010. Terra and Aqua MODIS design, radiometry, and geometry in support of land remote sensing. Land Remote Sensing and Global Environmental Change: NASA's Earth Observing System and the Science of ASTER and MODIS, 133-164. https://doi.org/10.1007/978-1-4419-6749-7_7.
Zanaga, D., Van De Kerchove, R., Daems, D., et al., 2022. ESA WorldCover 10 m 2021 v200. https://doi.org/10.5281/zenodo.7254221.
Zong, L., Zhang, M., Chen, Z., Niu, X., Chen, G., Zhang, J., Liu, H., 2023. Ecological Risk Assessment of Geological Disasters Based on Probability-Loss Framework: A Case Study of Fujian, China. International Journal of Environmental Research and Public Health, 20, 5, p. 4428. https://doi.org/10.3390/ijerph20054428.
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