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

• Autor(a) principal: Junqueira, Adriano M. [UNESP]
• Data de Publicação: 2020
• Outros Autores: Andrade, Marcio R. M., Mendes, Tatiana S. G. [UNESP], Simoes, Silvio J. C. [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1007/s12665-019-8750-x; http://hdl.handle.net/11449/198347
• topic: Analytic hierarchy process (AHP); Electric power transmission; Geographic information system (GIS); Space–time data; Susceptibility; Vulnerability

In 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.