Developing a spatial solution for earthquake crisis management using volunteered geographic information and genetic algorithm: A case study of an earthquake, Tehran, Iran

Hosseinali, Farhad; Farhadpour, Sarah

doi:10.22059/eoge.2021.309028.1085

Developing a spatial solution for earthquake crisis management using volunteered geographic information and genetic algorithm: A case study of an earthquake, Tehran, Iran

Document Type : Original Article

Authors

Farhad Hosseinali ¹

Sarah Farhadpour ²

¹ Shahid Rajaee University

² Department of Surveying Engineering, Faculty of Civil Engineering, Shahid Rajaee University

10.22059/eoge.2021.309028.1085

Abstract

Natural disasters, such as floods and earthquakes, affect the societies more than people think. These effects range from economic effects to social harms and casualties. An earthquake may only last a few seconds, but its damage lasts for years. The purpose of this study is to collect volunteered geographic information from people in the affected areas using smartphones and to identify areas of high priority for relief using the collected data. Then, spatial analysis enables us to assess the condition of the road network after the earthquake and determine the degree of damage due to debris. Ultimately, using the genetic algorithm, the process of assigning rescuers to crisis points and routing is done considering the extent of road damage. The case study is district 2 of Tehran. In this paper, it will be shown that a mobile information system is necessary to fill the gap between the people, the crisis headquarters and the relief teams. Such systems collect crisis-related data with the help of people in crisis areas and help headquarters and relief decisions to be faster and better. The results indicate a high vulnerability of roads in most areas of district 2 of Tehran. Eventually, about 243.5 km of the region's roads, which also make up a quarter of the region's vital arteries, are damaged by at least 80% that make the relief process difficult.

Keywords

Natural disasters

Rescue operations

Vulnerable roads

Geocrowdsourcing

Genetic algorithm