Landslide susceptibility mapping for transmission lines: dynamic monitoring, analysis and alerts for extreme natural events

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.contributorCentro Nacional de Monitoramento e Alerta de Desastres Naturais - CEMADEN-
Autor(es): dc.creatorJunqueira, Adriano M. [UNESP]-
Autor(es): dc.creatorAndrade, Marcio R. M.-
Autor(es): dc.creatorMendes, Tatiana S. G. [UNESP]-
Autor(es): dc.creatorSimoes, Silvio J. C. [UNESP]-
Data de aceite: dc.date.accessioned2022-02-22T00:24:18Z-
Data de disponibilização: dc.date.available2022-02-22T00:24:18Z-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2019-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/s12665-019-8750-x-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/198347-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/198347-
Descrição: dc.descriptionIn Brazil and other countries, most electric-sector enterprises do not present a systematic space–time evaluation of their structures to identify environmental vulnerabilities. Thus, this study aims to analyze the susceptibility of mass movements in transmission lines, in the Serra da Mantiqueira region (Brazil), subject to the effects of tropical rains to operationalize a dynamic platform of analysis and alertness in the most critical areas. For this study, static and dynamic data were collected in the region from public and private sources. Next, multiple criteria were defined through the analytic hierarchy process (AHP). Using geographic information systems (GIS) and map algebra, it was possible to determine a susceptibility map in five classes. Subsequently, based on the identified areas and dynamic meteorological and hydrological data, a real-time platform was operationalized for monitoring, analysis, and alerts to environmental risks. Consequently, a geographic database with a regional coverage (14,000 km2) was generated, involving seven criteria: slope, distance of transmission lines, drainage density, soil use, soil type, fracture and failure density, and precipitation. The susceptibility classes found in the study region were very low (1.5%), low (12%), average (34.9%), high (45.3%), and very high (6.2%). It was also possible to identify different mass movements in areas close to the transmission lines, as well as other risk elements such as dwellings, roads, reservoir borders, and telecommunications towers. The operationalized monitoring platform allowed the establishment of dynamic analyses on the occurrence of extreme natural events, by sending notifications and an online map of the affected areas. Thus, this platform developed in this study can become an instrument of evaluation, monitoring, and management for the public management and regulatory agencies of the electric sector.-
Descrição: dc.descriptionSão Paulo State University (UNESP) School of Engineering Guaratinguetá, Av. Dr. Ariberto Pereira da Cunha, 333-
Descrição: dc.descriptionCentro Nacional de Monitoramento e Alerta de Desastres Naturais - CEMADEN, Estrada Dr. Altino Bondensan, 500-
Descrição: dc.descriptionSão Paulo State University (UNESP) Institute of Science and Technology São José dos Campos, Rodovia Presidente Dutra, Km 137,8-
Descrição: dc.descriptionSão Paulo State University (UNESP) School of Engineering Guaratinguetá, Av. Dr. Ariberto Pereira da Cunha, 333-
Descrição: dc.descriptionSão Paulo State University (UNESP) Institute of Science and Technology São José dos Campos, Rodovia Presidente Dutra, Km 137,8-
Idioma: dc.languageen-
Relação: dc.relationEnvironmental Earth Sciences-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectAnalytic hierarchy process (AHP)-
Palavras-chave: dc.subjectElectric power transmission-
Palavras-chave: dc.subjectGeographic information system (GIS)-
Palavras-chave: dc.subjectSpace–time data-
Palavras-chave: dc.subjectSusceptibility-
Palavras-chave: dc.subjectVulnerability-
Título: dc.titleLandslide susceptibility mapping for transmission lines: dynamic monitoring, analysis and alerts for extreme natural events-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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