Flood analysis in Peru using satellite image: The Summer 2017 case

Descripción del Articulo

At the beginning of the year 2017, different regions of Peru suffered from heavy rains mainly due to the 'El Niño' and 'La Niña' phenomena. As a result of these massive storms, several cities were affected by overflows and landslides. Chosica and Piura were the most affected citi...

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Detalles Bibliográficos
Autores: Roman Gonzalez, Avid, Meneses Claudio, Brian
Formato: artículo
Fecha de Publicación:2019
Institución:Universidad de Ciencias y Humanidades
Repositorio:UCH-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.uch.edu.pe:uch/294
Enlace del recurso:http://repositorio.uch.edu.pe/handle/uch/294
http://doi.org/10.14569/IJACSA.2019.0100246
https://thesai.org/Publications/ViewPaper?Volume=10&Issue=2&Code=IJACSA&SerialNo=46
Nivel de acceso:acceso abierto
Materia:Landslide
natural disasters
Satellite image
Descripción
Sumario:At the beginning of the year 2017, different regions of Peru suffered from heavy rains mainly due to the 'El Niño' and 'La Niña' phenomena. As a result of these massive storms, several cities were affected by overflows and landslides. Chosica and Piura were the most affected cities. On the other hand, the satellite images have many applications, one of them is the aid for the better management of the natural disasters (post-disaster management). In this sense, the present work proposes the use of radar satellite images from Sentinel constellation to make an analysis of the most-affected areas by floods in the cities of Chosica and Piura. The applied methodology is to analyse and compare two images (one before and one after the disaster) to identify the affected areas based on differences between both images. The analysing process includes radiometric calibration, speckle filtering, terrain correction, histogram plotting, and image binarization. The results show maps of the analysed cities and identify a significant number of areas flooded according to satellite images from March 2017. Using the resulting maps, authorities can make better decisions. The satellite images used were from the Sentinel 1 satellite belonging to the European Union.
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