A Study on Seismic Regional Characteristics in Urban City

Satoru SADOHARA ¹⁾, Go URAKAWA ²⁾, Suminao MURAKAMI³⁾

Abstract

This study aims at evaluating factors related to potential seismic risk in a city or a group of cities based on the concept of "macro-zonation". These factors are associated with regional characteristics including natural features such as topography, climate and location of active faults, human features such as population and population density and artificial features such as buildings and roads . Countermeasures such as disaster measure of local government in Japan were uniform all over Japan, so we focused on "Regional characteristics" of each cities and necessity of index to compare each cities. The main objective of this study is to develop a countermeasure system utilizing macro information of urban cities to mitigate earthquake disaster, especially near-field earthquake, considering their regional characteristics.

1. Introduction

In this study, we focused to utilize GIS (Geographic Information System) against the measure of an earthquake disaster and study how to evaluate the potential of hazard and lead to emergency activity after suffering an earthquake. Firstly, we investigated factors which affected big damage by earthquake from the past earthquake disaster. And we created the database for evaluating the potential of the seismic hazard by considering to use GIS and the method of evaluating that was considered.

Former, in the measure against an earthquake, the research and the measure on condition of using GIS (a series of flow in GIS as follows :classification of data, setting data by considering user and scale, examination of method of regional danger by various elements, the concrete correspondence method in the case of urgent, and so on) are not carried out and local government almost only constructed the system of estimation in order to know how many number of people was killed and injured and how many number of buildings were collapsed. Though these systems are important , we think we should consider the relationship between the potential of hazard and emergency response.

In this study, we investigated many factors affected damage by earthquake and we created database from case records and we still more created advanced database by using GIS. On creating advanced database, we placed three scale of GIS data.(1. GIS data for evaluating wide area, 2.GIS data of parcel, 3.GIS data in detail). By keeping relationship with each data, we can construct comprehensive system by using GIS. Especially, in this study, we studied about GIS data for evaluating wide area and the method of evaluation of the regional character regarding to the potential of hazard by an earthquake from the view “Macro”.

The macro region of an earthquake disaster generating danger considered by this study is the evaluation method that the regional character of the earthquake hazard of Yokohama city can be grasped relatively. And, it is thought that GIS is helpful as the time of a local government deciding concrete correspondence immediately after earthquake generating, and an index which can be used

for each emergency activity (fire-fighting activity, rescue activity, etc).

2. Database from Big Earthquake in the Past

Firstly, we created The Earthquake Disaster Chart by investigation of big earthquake disaster in the past. And, the earthquake disaster chart was created about six past typical examples (Kanto earthquake 1.Sep.1923, Fukui earthquake 28.Jun.1948, Niigata earthquake 16.Jun.1964, Tokachioki earthquake 16.May.1968, Miyagikenoki earthquake 12.Jun.1978, Hanshin-Awaji earthquake 17.Jan.1995). We extracted factors by investigating some events because each events has same and different characters regarding to damage by earthquake. The Earthquake Disaster Chart is classified into natural element, artificial element, human element, and a time element, and is arranged, according to the elements of the city used as a phenomenon and its factor.

Consequently, relation between phenomena when an earthquake disaster occurs and elements of the city which affects its phenomena is clarified. From these elements, when using GIS, we created advanced database. It is important in case GIS is used. And, it is useful to assumption of the phenomenon that may happen to an earthquake disaster which will be generated from now on and also we can know the relationship between each factors. And, it is thought by laying a different element that a new phenomenon can be forecasted. The form of a database classified the earthquake disaster into four (structure thing destruction, foundations damage, tsunami, fire), and arranged like an earthquake disaster chart. Here, an example is shown in Table 1 about structure thing destruction.

Thus, when an earthquake breaks out, there are a lots of city elements used as the factor which causes a disaster. In this study, many phenomena and elements are chosen in the example of the six past from the factors, and the regional characteristics was evaluated.

3. Examining Regional Characteristics in Yokohama City Analysis From Macro View

Firstly, especially we extracted the element considered to cause damage or control out of the whole database created for the preceding chapter was extracted, and it classified into the element which created them as mesh data, and the element created as real data.

Elements, such as the population and a building with which the city is dotted, are created as mesh data, and such as the surface geology and dangerous object possession institution considered that there is a problem making it a mesh used elements, as real data, and it created them in the form of each the point, the line, and the polygon.

Next we chose data used in this chapter. Data which we created as mesh data are as follows.

(Total number of Ridges of Building, Number of Ridges of Wooden Building, Number of Ridges of Wooden Building built before 1981,Number of Ridges of Wooden Building of a pile roof, Number of Ridges of a residence, Number of Ridges of a non-Wooden Building, Population of the night, Population of the night of 19-25 years old, Population of the night of 65 years old or more, Population of the night other than 19-25 years old and 65 years old or more, The total extended distance of a road, The total extended distance of a road with a width of a road of 6m or less, The total extended distance of a road with a width of a road of 6m or more, The total area of a road)

These GIS data is strong influenced about damage on earthquake and we can have properness by grasping the regional character in advance. Then, we performed factor analysis in a mesh unit using these data. The reason we perform factor analysis is the following two. First, since it is difficult to give a priority which element is the most important, it is for clarifying evaluation and making it intelligible. Secondly, since various elements are intermingled in the city, it is for performing analysis which also took mutual correlation into consideration. The analysis result is shown in Table 2. Each numerical value in a table shows the amount of factor loads.(Factor 1. The degree of high density of an old wooden building, Factor 2. The degree of high density of population, Factor 3.The degree of high density of the road of a large width, Factor 4. The degree of high density of an upper-layers non-wooden building, Factor 5. The degree of high density of the road of a narrow width)

Moreover, we performed cluster analysis using the factor score obtained by this analysis. The degree of high density was classified according to it into five stages, and the area where the degree of high density is the highest was extracted as a high-density area. The reason from which we extracted the high-density area is because a high-density area has the example of suffering big damage, from a past disaster.

Using this result, we performed relative evaluation by the high-density area extracted above, and examining regional characteristics. At first, we show the study area set up by this study in Fig.1. The high-density area of a wooden building is shown in Fig.2. Among the high-density area extracted for every factor. According to the result, it turns out that the high-density area of a wooden building spreads out over the large range in Naka-Ward and Tsurumi-Ward area. Moreover, we performed the work with the same said of other factors.

Next, the high-density area of the road where width is narrow is put on the high-density area of a wooden building, it will become as it is shown in Fig.3. It can be said that the area where it is both crowded with a wooden building and the road where width is narrow is a high area of the risk of a fire being expanded since existence of the road vacant lot which prevents the spread of a fire cannot be expected, either, when a fire breaks out. Furthermore, it can be said that not only an overlapping area but the adjoining area also has the same danger.

4. Examining by Overlay 250m Mesh Data and Real Data

In this clause, we performed evaluation which piles up real data as a result of being the danger evaluation by the mesh-data analysis performed for the preceding clause. First, we show some examples about the damage which can be evaluation by superposition.

(Introductory notes) Real data + Mesh data → Damage

Then, especially we describe the risk of being related with a fire here.

First, we extracted the high-density area of a wooden building and the high-density area of the road where width is narrow in the mesh data, and the weak ground, fire handing store, dangerous object possession institution and the wind for every season as the element in connection with fire generating and the spread of a fire. However, with the example of a past earthquake disaster, since the fire from a general home had occurred each time, we omitted a fire handing store and dangerous object possession institution, and imagined the outbreak of fore from a general home here.

Moreover, we extracted the high-density area of the road where width is wide and the high-density area of the upper-layers non-wooden building in the mesh data.

On the basis of these data, we actually performed evaluation danger and control.

The area regarded as danger being high about a fire is shown in Fig. 4. These area enclosed with the thick line is the high-density area of a wooden building on the weak ground. At the time of earthquake generating, it is easy to generate collapse of wooden building, and if fire breaks out there, the tiles and pebbles of wooden building are filling the road in these areas.

Therefore, these areas do not bring a fire truck close, either, but it is supposed that the spread of a fire is expanded. If Fig.4 is expanded and seen, in order that a wind may change with seasons, the danger of the spread of a fire can be referred to as being also in the area not made

into the dangerous area. Moreover, the area considered that there is control power of the spread of a fire is shown in Fig.5. It is because a possibility of stopping the spread of a fire can be considered since these areas fully have the road vacant lot.

5. Conclusion

This study estimated examining regional characteristics in Tsurumi-Ward, Naka-Ward, Asahi-Ward in Yokohama City experimentally. The method of relative evaluation was considered. Thus, by evaluating a city by the macro viewpoint, it is thought that it is enabled to form the effective prior measure for every area by administration. This contents in this study is first step in order to construct the comprehensive system¹⁾ as introduction by using GIS data for evaluating wide area. This methodology to evaluate the regional characteristics from macro view is useful for mayor to make decision on emergency. And now we are trying to study next step, which making many scenario in order to help emergency action for department of fire, police and so on based the result of this study²⁾.

Firstly, we grasp the regional characteristics from macro view and secondly making many scenario considering each emergency activity and we can discover problem. Lastly, we are studying the solution about problems and feedback database. This concept is comprehensive system by using GIS and we can use this system effectively on earthquake event.

And also in this contents of study, we can compare the potential of hazards regarding to earthquake easily, so inhabitants can know the potential of hazards by themselves. If they know their risk concerning to earthquake, they will prepare to protect by themselves. We will try theses data open and to consider many way to use this study.

Appendix

1) We are trying to construct the comprehensive system( The Scenario Type of Seismic Damage estimation System). And image of this system is as follows and we consider user, scale, data and so on by using GIS.

2) And now we are trying to study next step, which making many scenario in order to help emergency action for department of fire, police and so on based the result of this study.(Evaluation of the regional characteristics regarding seismic hazard from Macro-view.) In this step, we should consider “ Who use this system?”, “ Which kind of damage estimate for each area?”, “ Which kind of emergency response are requested for each area?” and so on. In order to construct the comprehensive system above, we must consider relationship between each scale and feedback database of seismic hazard. We describe the sample of an idea( Emergent response to Fire) of scenario follows.