Citas bibligráficas
Vásquez, J., (2022). Identificación de áreas susceptibles a fenómenos de remoción en masa en obras lineales aplicando técnicas de geoprocesamiento [Tesis, Universidad Nacional de Ingeniería]. http://hdl.handle.net/20.500.14076/25243
Vásquez, J., Identificación de áreas susceptibles a fenómenos de remoción en masa en obras lineales aplicando técnicas de geoprocesamiento [Tesis]. PE: Universidad Nacional de Ingeniería; 2022. http://hdl.handle.net/20.500.14076/25243
@mastersthesis{renati/712622,
title = "Identificación de áreas susceptibles a fenómenos de remoción en masa en obras lineales aplicando técnicas de geoprocesamiento",
author = "Vásquez Acuña, Jenny Marina",
publisher = "Universidad Nacional de Ingeniería",
year = "2022"
}
In Peru and various parts of the world, disasters associated with mass elimination phenomena (FRM) generate negative impacts in the socio-economic and environmental spheres. In addition to the loss of life and damage to homes, in recent years, the destruction and deterioration of linear works has been of particular importance. Among the different highways in the country that are frequently affected by FRM associated with intense rains, are the highways that serve as a link between the departments of Lima and Junín. This study focuses on the analysis of the susceptibility to mass removal phenomena on the LM-116 highway, which is the highway that reports the highest number of FRM occurrences according to state inventories. This analysis involved the delimitation of the study area based on the micro-basins that limit the road, the delimitation of the FRM areas, as well as the elaboration of thematic cartography used as input for the application of three methodologies: the analysis hierarchical (AHP), statistical index (Wi) and weights of evidence (WofE). Six susceptibility maps of the region of interest were obtained and the results were analyzed through success curves (AUC). The FRM inventory is made up of 200 mass removal phenomena. The areas of very high susceptibility correspond to areas with a rugged relief, while the flat regions coincide with areas of very low susceptibility. The variation of the results expressed in the susceptibility maps prepared from the three methodologies showed that the model carried out with the Hierarchical Analysis tends to produce lower percentages in the area under the curve, while the methodologies Statistics obtain higher percentages confirming that these methods represent adequate tools in the evaluation of susceptibility to FRM.
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