4. Analysis results

#### 4.1 Hazard analysis in Yun-Chia plain areas

In this study, soil liquefaction is adopted as hazard. Referring to the maximum PGA of the three different design earthquakes force aforementioned for the NJRA method to assess soil liquefaction potential, also considering the effect of depth presented by [21], anti-liquefaction coefficient of different ground layers and the depth weighting factor are combined to obtain liquefaction potential index PL of each drilling.

Previously, soil liquefaction potentials and different return periods of earthquake forces were usually discussed separately. This research takes different soil liquefaction potential indices PL induced by three different return periods of earthquake forces to separate the level of hazard, such as high, medium, and low. The three different return periods of earthquake forces are 30, 475, and 2500 years (Figure 5a–c), respectively. The basis classification of hazard degree is shown in Table 1. Hazard distribution condition is shown in Figure 5d.

### 4.2 Vulnerability analysis in Yun-Chia plain areas

The definition of vulnerability in this study is "the degree to which the area may be damaged." Vulnerability indicator introduction and calculation method are shown below.

Population density is a commonly used quantitative indicator reflecting the density of population distribution, which is the ratio of the total number of inhabitants under the unit area, as shown in Eq. (3). The density of grid units can reflect the seriousness of the people casualties in disaster-hit areas.

$$\text{Population density} = \left(\frac{\text{village population}}{\text{village area}}\right) \tag{3}$$

4.3 Resilience analysis in Yun-Chia plain areas

Figure 5.

liquefaction.

67

The definition of resilience in this study is "the ability of the region to adapt frequent disasters, the ability of the plains to rebuild and improve after the disaster." Resilience indicator introduction and calculation method are shown below. Due to the fact that this indicator is country scale, this study refers to the concept presented by [22], which took mortality, the proportion of higher

Three different return periods of earthquake forces and Hazard distribution condition. (a) Soil liquefaction for earthquakes with a 30-year return period, (b) Soil liquefaction for earthquakes with a 475-year return period, (c) Soil liquefaction for earthquakes with a 2500-year return period, and (d) Hazard level induced by soil

The Study of Risk Assessment of Soil Liquefaction on Land Development and Utilization by GIS…

DOI: http://dx.doi.org/10.5772/intechopen.82417

Gross industrial output is critical to measure the economic status and regions development level. It is the total output value of various industries in a unit area, as shown in Eq. (4). The level of the total industrial output within a grid of units can reflect the degree of economic loss that may be caused when a disaster strikes the area.

$$\text{Grid industrial total output} = \sum \left( \frac{\text{gross industrial output}}{\text{total industrial area}} \times \text{in industrial area in grid} \right) \tag{4}$$

Environmentally sensitive areas are basically equipped with special biological value or highly vulnerable to environmental impacts due to improper development activities. Based on the database platform established by the Construction and Planning Agency, Ministry of the Interior (http://60.248.163.236/SEPortal/), this study sets first-grade and second-grade environmentally sensitive area as the most vulnerable area, and non-environmentally sensitive areas are considered as low vulnerability.

Natural Breaks (Jenks) is used to speed up by dividing different PR scores into five different levels of vulnerability. The classification is shown in Table 2. The research of the result shows that the most vulnerable level is the Yunlin Industrial and Commercial Zone, the south of Koch Township, the Dongshih Township of Chiayi County, the coastal areas of Budai Township, and the residential areas in the center of Chiayi City. Yun-Chia plain area's vulnerability distribution and grading chart is shown in Figure 6.

The Study of Risk Assessment of Soil Liquefaction on Land Development and Utilization by GIS… DOI: http://dx.doi.org/10.5772/intechopen.82417

#### Figure 5.

4. Analysis results

each drilling.

shown below.

chart is shown in Figure 6.

66

4.1 Hazard analysis in Yun-Chia plain areas

Geographic Information Systems and Science

In this study, soil liquefaction is adopted as hazard. Referring to the maximum PGA of the three different design earthquakes force aforementioned for the NJRA method to assess soil liquefaction potential, also considering the effect of depth presented by [21], anti-liquefaction coefficient of different ground layers and the depth weighting factor are combined to obtain liquefaction potential index PL of

Previously, soil liquefaction potentials and different return periods of earthquake forces were usually discussed separately. This research takes different soil liquefaction potential indices PL induced by three different return periods of earthquake forces to separate the level of hazard, such as high, medium, and low. The three different return periods of earthquake forces are 30, 475, and 2500 years (Figure 5a–c), respectively. The basis classification of hazard degree is shown in

The definition of vulnerability in this study is "the degree to which the area may

be damaged." Vulnerability indicator introduction and calculation method are

Population density is a commonly used quantitative indicator reflecting the density of population distribution, which is the ratio of the total number of inhabitants under the unit area, as shown in Eq. (3). The density of grid units can reflect

Population density <sup>¼</sup> village population

Gross industrial output is critical to measure the economic status and regions development level. It is the total output value of various industries in a unit area, as shown in Eq. (4). The level of the total industrial output within a grid of units can reflect the degree of economic loss that may be caused when a disaster strikes the area.

Environmentally sensitive areas are basically equipped with special biological value or highly vulnerable to environmental impacts due to improper development activities. Based on the database platform established by the Construction and Planning Agency, Ministry of the Interior (http://60.248.163.236/SEPortal/), this study sets first-grade and second-grade environmentally sensitive area as the most vulnerable area, and non-environmentally sensitive areas are considered as low vulnerability. Natural Breaks (Jenks) is used to speed up by dividing different PR scores into five different levels of vulnerability. The classification is shown in Table 2. The research of the result shows that the most vulnerable level is the Yunlin Industrial and Commercial Zone, the south of Koch Township, the Dongshih Township of Chiayi County, the coastal areas of Budai Township, and the residential areas in the center of Chiayi City. Yun-Chia plain area's vulnerability distribution and grading

village area 

total industrial area � industrial area in grid 

(3)

(4)

Table 1. Hazard distribution condition is shown in Figure 5d.

the seriousness of the people casualties in disaster-hit areas.

Grid industrial total output <sup>¼</sup> <sup>∑</sup> gross industrial output

4.2 Vulnerability analysis in Yun-Chia plain areas

Three different return periods of earthquake forces and Hazard distribution condition. (a) Soil liquefaction for earthquakes with a 30-year return period, (b) Soil liquefaction for earthquakes with a 475-year return period, (c) Soil liquefaction for earthquakes with a 2500-year return period, and (d) Hazard level induced by soil liquefaction.

#### 4.3 Resilience analysis in Yun-Chia plain areas

The definition of resilience in this study is "the ability of the region to adapt frequent disasters, the ability of the plains to rebuild and improve after the disaster." Resilience indicator introduction and calculation method are shown below.

Due to the fact that this indicator is country scale, this study refers to the concept presented by [22], which took mortality, the proportion of higher


#### Table 1.

Classification of hazard.


#### Table 2.

The classification of vulnerability based on PR score.

education population, and the average individual income tax as alternatives to health, knowledge, and living standard. The higher the indicator, the better is its ability to cover from upcoming disasters. The data of this study are based on the report published by the Directorate-General of Budget, Accounting and Statistics, Executive Yuan, R.O.C. (Taiwan) in 2015. And its formula is calculated as shown in Eqs. (5)–(7). The Human development index (HDI) value is the geometric mean of the three basic indicators in Eq. (8).

$$\text{Life expectation index} = 1 - \left[ \frac{(death\ rate - 5)}{maximum\ mortality\ rate} \right] \tag{5}$$
 
$$\text{If } \text{number of the population of higher education}$$

$$\begin{aligned} \text{Education index} &= \frac{2}{3} \left( \frac{\text{percentage of the population of higher reduction}}{4596} \right) \\ &+ \frac{1}{3} \left( \frac{\text{literacy rate of population over 15 yrs}}{100\%} \right) \end{aligned} \tag{6}$$

County financial budget <sup>¼</sup> county budget

and the higher the resilience.

Figure 6.

69

Insurance coverage rate is the percentage given by the amount of earthquake insurance divided by the number of households in counties. The more insurance coverage rate, the more citizen can be recovered by the insurance after the disaster,

Yun-Chia plain area's vulnerability distribution and grading chart. (a) Population density, (b) Gross

The Study of Risk Assessment of Soil Liquefaction on Land Development and Utilization by GIS…

DOI: http://dx.doi.org/10.5772/intechopen.82417

industrial output, (c) Environmentally sensitive areas, and (d) Vulnerability distribution.

Social welfare workers aim to prevent or relieve social problems by assisting individuals, families, groups, and communities in adapting their social functions, enhancing or restoring the energy of their social functions, and creating social conditions that achieve goals. The more staff members, the higher the resilience. Communal participation rate reflects the local populace's income and preference for leisure. It is influenced by individual labor supply choices, which are affected by personal and social factors. Communal participation rate is the percentage given by

county population � village population (9)

$$\text{Living standard index} = \frac{\left[\log\left(\frac{\text{average\\_hour} \text{oldd\\_dispoable\\_income}}{\text{US dollar}}\right) - \log\left(\text{100}\right)\right]}{\left[\log\left(75000\right) - \log\left(100\right)\right]} \tag{7}$$

$$\text{HDI} = \sqrt[3]{(\text{life\ exponent} \times \text{education index} \times \text{standard of living index})} \tag{8}$$

The counties and counties' financial budgets are related to the recovery potential after the counties and cities encountered disaster. The data of this study are based on the report published by Directorate-General of Budget, Accounting and Statistics, Executive Yuan, R.O.C. (Taiwan) in 2015. And its formula is calculated as shown in Eq. (9).

The Study of Risk Assessment of Soil Liquefaction on Land Development and Utilization by GIS… DOI: http://dx.doi.org/10.5772/intechopen.82417

Figure 6.

education population, and the average individual income tax as alternatives to health, knowledge, and living standard. The higher the indicator, the better is its ability to cover from upcoming disasters. The data of this study are based on the report published by the Directorate-General of Budget, Accounting and Statistics, Executive Yuan, R.O.C. (Taiwan) in 2015. And its formula is calculated as shown in Eqs. (5)–(7). The Human development index (HDI) value is the geometric mean of

5 The areas are high potential when the seismic design made by guideline happens (15 < PL). 4 The areas are medium potential when the seismic design made by guideline happens

3 The areas are medium potential when the seismic design made by guideline happens

However, the areas are high potential when the maximum considered earthquake happens

In addition, the areas are medium potential when the maximum considered earthquake

However, the areas are medium potential when the maximum considered earthquake happens

Classification Level 1 Level 2 Level 3 Level 4 Level 5

Natural Breaks(Jenks) 0�2.14 2.14�4.06 4.06�7.21 7.21�9.80 9.80�14.18

2 The areas are low potential when the seismic design made by guideline happens (PL < 5).

1 The areas are low potential when the seismic design made by guideline happens (PL < 5). In addition, the areas are low potential when the maximum considered earthquake happens

Life expectation index <sup>¼</sup> <sup>1</sup> � ð Þ death rate � <sup>5</sup>

maximum mortality rate � �

½ � log 75000 ð Þ� log 100 ð Þ (7)

percentage of the population of higher education 45% � �

h i

literacy rate of population over 15 yrs 100% � �

> log average household disposable income US dollar � �

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ð Þ life expectancy � education index � standard of living index <sup>3</sup>

The counties and counties' financial budgets are related to the recovery potential after the counties and cities encountered disaster. The data of this study are based on the report published by Directorate-General of Budget, Accounting and Statistics, Executive Yuan, R.O.C. (Taiwan) in 2015. And its formula is calculated as

(5)

(6)

(8)

� log 100 ð Þ

the three basic indicators in Eq. (8).

The classification of vulnerability based on PR score.

Level The classification of hazard

Geographic Information Systems and Science

(5 ≤ PL ≤ 15).

(5 ≤ PL ≤ 15).

(5 ≤ PL ≤ 15).

(PL < 5).

Classification of hazard.

PR score of distribution

Table 1.

Table 2.

happens (5 ≤ PL ≤ 15).

(15 < PL).

3

þ 1 3

Living standard index ¼

q

Education index <sup>¼</sup> <sup>2</sup>

HDI ¼

shown in Eq. (9).

68

Yun-Chia plain area's vulnerability distribution and grading chart. (a) Population density, (b) Gross industrial output, (c) Environmentally sensitive areas, and (d) Vulnerability distribution.

$$\text{County financial budget} = \left(\frac{\text{county budget}}{\text{county population}}\right) \times \text{village population} \tag{9}$$

Insurance coverage rate is the percentage given by the amount of earthquake insurance divided by the number of households in counties. The more insurance coverage rate, the more citizen can be recovered by the insurance after the disaster, and the higher the resilience.

Social welfare workers aim to prevent or relieve social problems by assisting individuals, families, groups, and communities in adapting their social functions, enhancing or restoring the energy of their social functions, and creating social conditions that achieve goals. The more staff members, the higher the resilience.

Communal participation rate reflects the local populace's income and preference for leisure. It is influenced by individual labor supply choices, which are affected by personal and social factors. Communal participation rate is the percentage given by the number of people willing to participate in community affairs divided by the number of people in a community. The higher the community participation rate, the higher the resilience.

Natural Breaks (Jenks) is used to speed up dividing different PR scores into five different levels of resilience. The classification is shown in Table 3. The research of the result shows that the highest resilience area is Maifeng Village, Yunlin County, HsinJei Village, Chiayi County, Ping Lin Lane, and Chiayi City District. Yun-Chia plain area's resilience distribution and grading chart is shown in Figure 7.

#### 4.4 Risk assessment of soil liquefaction

This study sets the definition of disaster risk as a result of disasters caused by soil liquefaction such as structure failure, property loss, and even casualties. And hazard was defined as the earthquake-induced soil liquefaction; vulnerability is dined as population distribution, economic development, and environmental development; resilience is for social development, community development, government resources, property protection, and social assistance showing the recovery from disaster.

Taking the above definition as main principle, hazard, vulnerability and resilience are cross calculated and graded accordingly and divide the disaster risk levels into 1–5 points. The grading index standard of each factor given in this study is shown in Table 4. The risk analysis procedure showed how the combination among hazard, vulnerability, and resilience is shown in Figure 8.

Based on the report published in [23], dividing risk levels as five parts help the decision maker to make the optimized decision. This study followed the guide and divided risk into five categories: "extremely high," "high," "medium," "low," and "extremely low." The categories could easily show the risk when different area encountered the disaster. The risk of soil liquefaction distribution condition is shown as Figure 9. The risk assessment result assessed by UNDRO method (Risk = Hazard\*Vulnerability) is shown in Figure 10.

By comparing the degree of vulnerability, resilience, and resilience used in this study, we can find that the risk analysis of joining resilience factor in this study is more effective than the risk analysis of two factors of degree of vulnerability and vulnerability in the past. When it comes to considering the resilience factor, the resilience of areas such as Mailiao Township, Lunbei Township, and Chiayi County of Yunlin City is better, and the degree of risk exposure in the event of a disaster is effectively reduced.

In this study, the soil liquefaction potential chart and the liquefaction risk chart obtained in 475 years of the return period of Yun-Chia plain and the soil liquefaction potential map in Yun-Chia area published by the CGS are analyzed and compared, as shown in Figure 11. It is found that the distribution of soil liquefaction potential obtained in 475 years (Figure 5b) of the study area of Yun-Chia Plain is similar to the distribution of soil liquefaction potential in Yun-Chia area published by the CGS. However, the risk analysis shows that most of the areas are high soil liquefaction potential area. But if we take the region's resilience into consideration, the risk level it faces in the event of soil liquefaction-induced disaster is not as severe as imagined.


Figure 7.

71

rate distribution, and (f) Resilience distribution.

Yun-Chia plain area's resilience distribution condition. (a) HDI distribution, (b) County budgetdistribution, (c) Insurance coverage rate distribution, (d) Social welfare workers distribution, (e) Communal participation

The Study of Risk Assessment of Soil Liquefaction on Land Development and Utilization by GIS…

DOI: http://dx.doi.org/10.5772/intechopen.82417

#### Table 3. Classification of resilience based on PR score.

The Study of Risk Assessment of Soil Liquefaction on Land Development and Utilization by GIS… DOI: http://dx.doi.org/10.5772/intechopen.82417

#### Figure 7.

the number of people willing to participate in community affairs divided by the number of people in a community. The higher the community participation rate,

plain area's resilience distribution and grading chart is shown in Figure 7.

Natural Breaks (Jenks) is used to speed up dividing different PR scores into five different levels of resilience. The classification is shown in Table 3. The research of the result shows that the highest resilience area is Maifeng Village, Yunlin County, HsinJei Village, Chiayi County, Ping Lin Lane, and Chiayi City District. Yun-Chia

This study sets the definition of disaster risk as a result of disasters caused by soil liquefaction such as structure failure, property loss, and even casualties. And hazard was defined as the earthquake-induced soil liquefaction; vulnerability is dined as population distribution, economic development, and environmental development; resilience is for social development, community development, government resources, property protection, and social assistance showing the recovery from disaster.

Taking the above definition as main principle, hazard, vulnerability and resilience are cross calculated and graded accordingly and divide the disaster risk levels into 1–5 points. The grading index standard of each factor given in this study is shown in Table 4. The risk analysis procedure showed how the combination among

Based on the report published in [23], dividing risk levels as five parts help the decision maker to make the optimized decision. This study followed the guide and divided risk into five categories: "extremely high," "high," "medium," "low," and "extremely low." The categories could easily show the risk when different area encountered the disaster. The risk of soil liquefaction distribution condition is shown as Figure 9. The risk assessment result assessed by UNDRO method

By comparing the degree of vulnerability, resilience, and resilience used in this study, we can find that the risk analysis of joining resilience factor in this study is more effective than the risk analysis of two factors of degree of vulnerability and vulnerability in the past. When it comes to considering the resilience factor, the resilience of areas such as Mailiao Township, Lunbei Township, and Chiayi County of Yunlin City is better, and the degree of risk exposure in the event of a disaster is effectively reduced. In this study, the soil liquefaction potential chart and the liquefaction risk chart obtained in 475 years of the return period of Yun-Chia plain and the soil liquefaction potential map in Yun-Chia area published by the CGS are analyzed and compared, as shown in Figure 11. It is found that the distribution of soil liquefaction potential obtained in 475 years (Figure 5b) of the study area of Yun-Chia Plain is similar to the distribution of soil liquefaction potential in Yun-Chia area published by the CGS. However, the risk analysis shows that most of the areas are high soil liquefaction potential area. But if we take the region's resilience into consideration, the risk level it faces in the event of soil liquefaction-induced disaster is not as

Classification Level 1 Level 2 Level 3 Level 4 Level 5

PR score of distance Natural breaks(Jenks) 05.24 5.246.10 6.107.33 7.339.36 9.3613.41

the higher the resilience.

4.4 Risk assessment of soil liquefaction

Geographic Information Systems and Science

hazard, vulnerability, and resilience is shown in Figure 8.

(Risk = Hazard\*Vulnerability) is shown in Figure 10.

severe as imagined.

Classification of resilience based on PR score.

Table 3.

70

Yun-Chia plain area's resilience distribution condition. (a) HDI distribution, (b) County budgetdistribution, (c) Insurance coverage rate distribution, (d) Social welfare workers distribution, (e) Communal participation rate distribution, and (f) Resilience distribution.

In formulating national strategy for disaster prevention, local governments can adjust and control the overall high soil liquefaction area and low potential in the event of soil liquefaction. The "Extremely High" and "High" risk region in this study should be the top priority improvements targets.


### Table 4.

Indicator grading and risk level.

5. Conclusions

Figure 9.

73

hazard, vulnerability, and resilience.

Resilience index grading, and (d) Risk of soil liquefaction.

DOI: http://dx.doi.org/10.5772/intechopen.82417

county recovers from the disaster.

This study takes the risk of soil liquefaction in Chiayi and Yunlin Plains, adopt those soil liquefaction potential index assessment which commonly used in Taiwan and worldwide as the basic reference. This study also uses the definition proposed by UNDRO as a basis for assessing soil liquefaction risks but resilience was added into this study's risk assessment method, and considers risk as the combination of

Risk of soil liquefaction distribution condition. (a) Hazard index grading, (b) Vulnerability index grading, (c)

The Study of Risk Assessment of Soil Liquefaction on Land Development and Utilization by GIS…

This research took different soil liquefaction potential index PL induced by three different return periods of earthquake forces such as 30, 475, and 2500 years as Hazard. Vulnerability took four indicators representing factors such as population density, gross industrial output and environmentally sensitive areas, and land use. Resilience took social development, government resources, property protection, social assistance, and community development as the main points to show how the

According to the results of vulnerability analysis and resilience analysis, the vulnerability and resilience of Yunlin County are weaker than those of Chiayi

Figure 8. Procedure of the risk level analysis.

The Study of Risk Assessment of Soil Liquefaction on Land Development and Utilization by GIS… DOI: http://dx.doi.org/10.5772/intechopen.82417

Figure 9.

In formulating national strategy for disaster prevention, local governments can adjust and control the overall high soil liquefaction area and low potential in the event of soil liquefaction. The "Extremely High" and "High" risk region in this

Indicator grading Risk level 1 Risk level 2 Risk level 3 Risk level 4 Risk level 5 Hazard 1 2 3 4 5 Vulnerability 1 2 3 4 5 Resilience 5 4 3 2 1

study should be the top priority improvements targets.

Geographic Information Systems and Science

Table 4.

Figure 8.

72

Procedure of the risk level analysis.

Indicator grading and risk level.

Risk of soil liquefaction distribution condition. (a) Hazard index grading, (b) Vulnerability index grading, (c) Resilience index grading, and (d) Risk of soil liquefaction.

### 5. Conclusions

This study takes the risk of soil liquefaction in Chiayi and Yunlin Plains, adopt those soil liquefaction potential index assessment which commonly used in Taiwan and worldwide as the basic reference. This study also uses the definition proposed by UNDRO as a basis for assessing soil liquefaction risks but resilience was added into this study's risk assessment method, and considers risk as the combination of hazard, vulnerability, and resilience.

This research took different soil liquefaction potential index PL induced by three different return periods of earthquake forces such as 30, 475, and 2500 years as Hazard. Vulnerability took four indicators representing factors such as population density, gross industrial output and environmentally sensitive areas, and land use. Resilience took social development, government resources, property protection, social assistance, and community development as the main points to show how the county recovers from the disaster.

According to the results of vulnerability analysis and resilience analysis, the vulnerability and resilience of Yunlin County are weaker than those of Chiayi

County in the general areas, so in the event of a disaster, Yunlin County will likely face more serious losses in densely populated areas and high-output-value

worst, followed by Beigang Town (16%) and Turku Town (14%).

From the risk analysis results, we can see that in the face of the impact of soil liquefaction disasters, the population in Kouhu Township, Beigang Township, Tucu Town, Shui Lin Township, Dapi Township, Yuanchang Township, Dongsiang Township, and Baozhong Township of Yunlin County, was significantly lower than that of other large areas and low resilience led to these townships being over 10% at risk "extremely high" and "high," of which Kwuchu Township (26%) was the

The Study of Risk Assessment of Soil Liquefaction on Land Development and Utilization by GIS…

This study discussed soil liquefaction from the perspective of risk. Compared with the CGS, "Soil liquefaction potential" can better reflect the relative risk among different regions and is more effective in concentrating decision makers in regional

The authors gratefully acknowledge the financial support of the Ministry of Science and Technology (No. MOST 106-2621-M-019-005-MY2) and Center of Excellence for the Ocean. Finally, the authors want to thank the reviewers for their

industries.

DOI: http://dx.doi.org/10.5772/intechopen.82417

risk management.

Acknowledgements

very valuable comments.

Author details

75

Lien-Kwei Chien\*, Jing-Ping Wu and Wen-Chien Tseng

\*Address all correspondence to: ntoulkchien@gmail.com

provided the original work is properly cited.

Department of Harbor and River Engineering, and Center of Excellence for the

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

Oceans, National Taiwan Ocean University, Keelung, Taiwan (R.O.C)

Figure 10. The risk assessment result assessed by UNDRO method.

Figure 11. Soil liquefaction potential map in Yun-Chia area published by the CGS.

The Study of Risk Assessment of Soil Liquefaction on Land Development and Utilization by GIS… DOI: http://dx.doi.org/10.5772/intechopen.82417

County in the general areas, so in the event of a disaster, Yunlin County will likely face more serious losses in densely populated areas and high-output-value industries.

From the risk analysis results, we can see that in the face of the impact of soil liquefaction disasters, the population in Kouhu Township, Beigang Township, Tucu Town, Shui Lin Township, Dapi Township, Yuanchang Township, Dongsiang Township, and Baozhong Township of Yunlin County, was significantly lower than that of other large areas and low resilience led to these townships being over 10% at risk "extremely high" and "high," of which Kwuchu Township (26%) was the worst, followed by Beigang Town (16%) and Turku Town (14%).

This study discussed soil liquefaction from the perspective of risk. Compared with the CGS, "Soil liquefaction potential" can better reflect the relative risk among different regions and is more effective in concentrating decision makers in regional risk management.
