Flood Disaster Identification and Decision Support System using Crowdsource Data Based on Convolutional Neural Network and 3S Technology

Supattra Puttinaovarat,Sompop Dangtia,Teerawad Sriklin,Kanit Khaimook

doi:10.3991/ijim.v14i20.17243

Abstract

Every flood causes damages to many lives and properties. Moreover, it affects the economy and lifestyle of people in the society in a short period and a long period. In consequence, this research would demonstrate techniques and flood detection analyzed through digital images and web application development for receiving reports and inspection of flood situation in every area. The process requires crowdsource data and uses 3S technology so it will receive the accurate and real-time data for making a decision in the flood management and aids to the people in the disastrous area. In this research, Convolutional neural network was applied for flood detection and classification using digital images and data from people or the victims. According to the study, it was found that convolutional neural network for flood classification has accuracy of data at the high level or 95.50%, 93.00%, 97.89%, and 0.91 which are the results of accuracy, producer accuracy, user accuracy, and kappa statistics, respectively. Besides, the use of this technique saves cost, time, and labors. Furthermore, the method could be applied to other disasters such as landslide, earthquake, and fire. It is able to monitor the incident in each type of disasters and also examines the damaged site after the incident.

Highlights

Flooding is a natural disaster that can cause a significant impact on the lives and property of people
The first is to distinguish between images of flood events in pictures and images without flood incidents occurring in the images by using the convolutional neural network (CNN) in order to be able to screen only the images related to the flood event in the developed web application
The criteria used to determine whether the image the user uploads is the flood image or non-flood image based on the class of images

Summary

Introduction

Flooding is a natural disaster that can cause a significant impact on the lives and property of people. Thailand has frequently suffered from flooding during the monsoon seasons [1]. Each flood area is spread over several provinces in various areas [2]. Using only human labour or government officials to investigate the suffering or damage that occurs each time requires a large amount of funding and human resources. It takes time to get the information on the flood areas in order to be used to make informed decisions concerning the provision of relief to flood victims. The information can be used to help flood victims or alleviate the iJIM ‒ Vol 14, No 20, 2020

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Conclusion