Flood Analysis in Peru using Satellite Image: The Summer 2017 Case
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2019, Vol 10, Issue 2
Abstract
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.
Authors and Affiliations
Avid Roman-Gonzalez, Brian A. Meneses-Claudio, Natalia I. Vargas-Cuentas
Keywords
Related Articles
- EP ID EP468387
- DOI 10.14569/IJACSA.2019.0100246
- Views 88
- Downloads 0
Greedy Algorithms to Optimize a Sentence Set Near-Uniformly Distributed on Syllable Units and Punctuation Marks
An optimum sentence set that near-uniformly dis-tributed on syllable units and punctuation marks is important to develop a syllable-based automatic speech recognition (ASR). It is usually extracted from a mother set of m...
Comparative Study of Bayesian and Energy Detection Including MRC Under Fading Environment in Collaborative Cognitive Radio Network
The most important component of Cognitive Radio Network (CRN) is to sense the underutilised spectrum efficiently in fading environment for incorporating the increasing demand of wireless applications. The result of spect...
Prediction of Stroke using Data Mining Classification Techniques
Stroke is a neurological disease that occurs when a brain cells die as a result of oxygen and nutrient deficiency. Stroke detection within the first few hours improves the chances to prevent complications and improve hea...
Framework Utilizing Machine Learning to Facilitate Gait Analysis as an Indicator of Vascular Dementia
Vascular dementia (VD), the second most common type of dementia, effects approximately 13.9 per cent of people over the age of 71 in the United States alone. 26% of individuals develop VD after being diagnosed with conge...
Coverage-Aware Protocols in Wireless Sensor Networks: A Review
Coverage plays a vital role in wireless sensor networks (WSNs), since it is used as one of the important measure to achieve the performance of the sensor network. The sensor nodes in WSN have limited power and energy res...