Bibliographic citations
Laura, J., Tacuri, S. (2024). Calibración de áreas de inundación mediante los índices espectrales de imágenes de satélite, caso: Evento 2017 - Piura - Perú [Tesis, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/682133
Laura, J., Tacuri, S. Calibración de áreas de inundación mediante los índices espectrales de imágenes de satélite, caso: Evento 2017 - Piura - Perú [Tesis]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2024. http://hdl.handle.net/10757/682133
@misc{renati/1299652,
title = "Calibración de áreas de inundación mediante los índices espectrales de imágenes de satélite, caso: Evento 2017 - Piura - Perú",
author = "Tacuri Ciña, Sebastian David",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2024"
}
In the course of this research, the topic of flood area calibration was addressed through 2D hydraulic modeling, employing spectral indices from satellite images, specifically NDWI and NDBI. The focus is directed to the El Niño Phenomenon event of March 2017 in the urban area of Piura, Peru, with the purpose of obtaining a 2D model that accurately represents the flooding of that event. The specific objectives cover the delimitation of the study area and land use assessment, the generation of spectral indices from satellite data, and the use of HEC-RAS 2D software to model and calibrate the flooding. Base parameters of the El Niño event were incorporated into this software, which were calibrated through iterations that led to obtaining a calibrated flood model. The accuracy assessment of the model was carried out using the Kappa coefficient, which provided a measure of the model's ability to predict the observed floods. The expected result is to obtain the highest percentage of accuracy that between the 2D model and the actual conditions of the 2017 flood event in Piura. This study has significant value in improving the understanding of flood events in the region and offers practical applications in disaster management and urban planning. It will facilitate more effective decision making to mitigate the effects of future floods, thus contributing to the safety and resilience of urban communities to extreme weather events.
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