Spatial Analysis of Environmental Hazards

Spatial Analysis of Environmental Hazards

Urban Spatial Resilience Zonation after Earthquake in part of Tehran Metropolis (district 12) , Using OWA Algorithm.

Authors
Jalal Karami
Aminah Mohamadi
Mohammad SharifiKia
10.18869/acadpub.jsaeh.3.2.23
Abstract
Resilience are concepts that are finding increasing currency in several fields of research as well as in various policy and practitioner communities engaged in global environmental change science, climate change, sustainability science, disaster risk-reduction and famine interventions (Vogel, et.al, 2007). Where the risk is a probability of damage, injury, liability, loss, or any other negative occurrence that is caused by external or internal vulnerabilities, and that may be avoided through preemptive action (Benson, et.al, 2004). Among natural disasters, earthquakes, due to the unpredictable nature of these events, are one of the most destructive. Iran is one of the most earthquake-prone countries in the world that its cities most affected by this phenomenon. Among the cities of Iran, Tehran, as the country's first metropolis, due to dense population, poor physical development, structural density, and lack of standards, is potentially facing a serious threat. The purpose of this study is to investigate the spatial flexibility of Tehran over the region 12 after the earthquake incidence.

The present study is dealt with the data preparing and analysis using geospatial methods. The several geospatial data such as Peak Ground Acceleration (AGA) map, urban structure, infrastructure and population collected from Tehran Disaster Management Center were provided and analysis based some GIS known algorithms. In other to urban spatial resilience zonation the AHP (analytical Hierarchy Process) was implemented to generation risk map. Finally OWA (Ordered Weighted Average) method was implemented in order to Production spatial flexibility map of earthquake incidence over the District 12 of Tehran. AHP model uses of priorities straight experts, but OWA provides of control the level of compensation and risk-taking in a decision. Using the conceptual of fuzzy quantifier with OWA makes the qualitative data analysis enter to decision.

According to flexibility of the final map with fuzzy operator (All) equivalent to the operator MIN, the worst result Was obtained and resulting the highest risk and lowest flexibility respectively (Districts Nos. 2,12,7,8 and 11).By taking all the criteria of a criterion without compensation by other criteria as "non-risk" is obtained .

Map obtained with fuzzy operator (Half) has the high potential to provide suitable options, because in addition to integration criteria the importance of each parameter based on the weight given to the criteria are considered. In this map Districts Nos.2.6 and 8 (Baharestan, Emamzadeyahya and Sanglajedarkhangah) respectively were most Risk to earthquakes and therefore less flexibility to the earthquake. The map obtained with the fuzzy operator "Atleast one" is equivalent to MAX operator districts Nos. 2,12,7 and 8 (Baharestan ,DarvazehGhar of Shush,Abshardardar and Sanglajedarkhangah) respectively were most Risk to earthquakes and therefore less flexibility to the earthquake.

The fuzzy conceptual map quantifier showed that districts Nos. 2 and 12 (Baharestan and DarvazehGhar of Shush) were most vulnerable and therefore less flexibility to the earthquake as final results.
Keywords
Earthquake
Resilience
AHP
OWA method
Area12 Tehran
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