1. Introduction

For global environmental changing, the change of land use cause severe and straightforward impact [1]. The form of land use is determined by several of complex factors, such as politics, economics, society, culture, and natural environment. However, if the change of land use is based on those complex factors, it will easily bring huge impact to the environment [2].

Reference [3] indicated that in hazard-prone areas worldwide, cyclones, flooding, landslides, earthquakes, and volcanoes are the most common natural hazards. The report showed that 73% of Taiwan's citizens are exposed in the three or more hazards; 99% of people are exposed in two or more hazards. This analysis reveals is the extent to which, at global and regional scales, there is substantial overlap between different types of hazards and population concentrations. The result shows that large percentages of the population in Taiwan reside in hazardprone areas.

Reference [4] raises a new concept about three essential factors to cause a disaster such as Hazard, Exposure, and Vulnerability. In other words, risk management will rise to the top priority if we cannot predict or control the natural disaster. Mastering exposure and vulnerability is the first step. Reference [5] had pointed out that some of the researches that will consider Exposure as a part of Vulnerability

analysis. For instance, United Nations Development Program (UNDP) presented a brand new concept to explain how the risk be assessed, in which risk = Hazard � Exposure � Vulnerability. Report from [6] shows how Vulnerability and Exposure can be decided and the potential disaster happened under climate change.

Kaohsiung, Taiwan Meinong earthquake measuring 6.6 on the Richter scale happened in February 6, 2015; and became one of the most harmful disaster, which caused serious damage to the society. The damages are restricted in causing building failure and also make tons of people in suffer. Central Geological Survey (CGS) of MOEA has also started to do large-scale national geological drilling survey to set up Taiwan's own soil liquefaction potential inquiry system.

As high speed growth of Taiwan's population and rapid economic development, land use is becoming more and more diversity. Disaster impact will be changed in accordance to dissimilar regions, environments, and soil types. In summary, the main principle of this study is to use the Geographic Information Systems (GIS) tool, Chiayi and Yunlin plain survey result done by National Land Surveying and Mapping Center, Ministry of the Interior (NLSC); and combine with hazard, vulnerability, and resilience maps to do the soil liquefaction risk mapping. Based on the soil liquefaction risk map, proper development, and utilization strategy of the region will be established. This study also could become a reference of a general land protection strategy and regional development licensing and risk assessment and management.

mentioned in NJRA method, and considers different earthquake force designs as our hazard level grading. By comparing this study's result and CGS's result, people can figure out the difference between using normal soil liquefaction potential and our research's soil liquefaction potential that considers hazard, vulnerability, and

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

Second, vulnerability is based on the vulnerability indicators established by [9, 10]. To ensure that the database is correct, this study generally reviews the integrity of the indicators' data; ensures the indicators are selected appropriately and reflects the true development of the regions. Resilience indicators used in this study refer to [11, 12] for using the resilience indicators at all levels to consider the data integrity, the appropriateness of indicators which could showed the real condition of representative regions' development, and recovery. What is more, there is neither direct correlation nor the preference between the indicators. Therefore, the Pareto ranking (PR) method is used to standardize all the grading and abandon

This study seeks to simplify the mapping of potentially liquefiable areas by using

Cone penetration tests are used by the CGS in order to create GIS maps, but this is costly and not every county can afford to fund such studies on land. Geologic GIS layers are available due to the soil mapping of most counties by the CGS. Using the databank of social-economy and humanities in the county, along with other available data layers to narrow down the liquefaction risk of areas within the counties using ArcGIS and liquefaction criteria, the GIS layers for the Yun-Chia plain areas were modeled to select out the most liquefiable areas. These data layers were then combined to create a liquefaction risk map for Yunlin County and Chiayi County.

Before using PR analysis, those factors have to be standardized by Eq. (2). After getting a standardized grade, this study sums each region's vulnerability indicators total grade (grades of each factor vulnerability indicators are 1–5) and integrates those hazard indicators into six degrees. Hazard indicators are mean sea level rising, land subsidence, and storm surge flooding. And finally, use Pareto ranking (PR) analysis to evaluate general risk in coastal areas; and give each region a hazard risk

indicator weighing in order to establish the vulnerability and resilience.

This research can easily represent results straight forwardly.

damage in high risk areas of the county.

The concept of the three-dimensional risk matrix.

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

2.2 Pareto ranking (PR) analysis

61

Geographical Information Systems (GIS), and compared with the assessment method by the UNDRO to produce a map that could be used to evaluate potential

resilience.

Figure 1.

### 2. Research methodology

This study takes the risk of soil liquefaction in Chiayi and Yunlin plains, adopt those soil liquefaction potential index assessment which is commonly used in Taiwan and worldwide as the basic reference. United Nations Disaster Relief Organization (UNDRO) [7] proposed an operability definition for disaster risk: R(Risk) = H(Hazard) � V(Vulnerability), which is the most commonly used method of disaster risk assessment The study also uses this definition as a basis for assessing soil liquefaction risks. In order to fully realize the effect of land use, this study changes the past boundaries of risk, such as townships, towns, cities, and districts as the boundaries of risk allocation and takes the 100 � 100 m grid as the regional space unit.

#### 2.1 Risk matrix

This study takes resilience as an indicator that represented how the region recovers from the disaster. Therefore, the risk assessment method used in this study is as Eq. (1) and the concept of risk matrix is shown in Figure 1.

$$\text{Risk} = \text{H}(\text{hazzard}) \times \text{V} \left( \text{vulnerability} \right) \times \text{R} (\text{resilience}) \tag{1}$$

This study considered soil liquefaction as a cause of disaster, which is defined as hazard, the different phases of Taiwan society developments are named as Vulnerability and how Taiwan's response to upcoming disaster as Resilience. Taiwan soil liquefaction risk assessment will be done by combining hazard, vulnerability, and resilience into risk matrix.

In this study, CGS's drilling investigation result is selected as our database. Therefore, the assessment methodology used in this study is the same as CGS, which is called NJRA method [8]. This study adopts the soil liquefaction potential 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 1.

analysis. For instance, United Nations Development Program (UNDP) presented a brand new concept to explain how the risk be assessed, in which risk = Hazard � Exposure � Vulnerability. Report from [6] shows how Vulnerability and Exposure

Kaohsiung, Taiwan Meinong earthquake measuring 6.6 on the Richter scale happened in February 6, 2015; and became one of the most harmful disaster, which caused serious damage to the society. The damages are restricted in causing building failure and also make tons of people in suffer. Central Geological Survey (CGS) of MOEA has also started to do large-scale national geological drilling survey to set up

As high speed growth of Taiwan's population and rapid economic development, land use is becoming more and more diversity. Disaster impact will be changed in accordance to dissimilar regions, environments, and soil types. In summary, the main principle of this study is to use the Geographic Information Systems (GIS) tool, Chiayi and Yunlin plain survey result done by National Land Surveying and Mapping Center, Ministry of the Interior (NLSC); and combine with hazard, vulnerability, and resilience maps to do the soil liquefaction risk mapping. Based on the soil liquefaction risk map, proper development, and utilization strategy of the region will be established. This study also could become a reference of a general land protection strategy and regional development licensing and risk assessment

This study takes the risk of soil liquefaction in Chiayi and Yunlin plains, adopt those soil liquefaction potential index assessment which is commonly used in Taiwan and worldwide as the basic reference. United Nations Disaster Relief Organi-

This study takes resilience as an indicator that represented how the region recovers from the disaster. Therefore, the risk assessment method used in this study

This study considered soil liquefaction as a cause of disaster, which is defined as hazard, the different phases of Taiwan society developments are named as Vulnerability and how Taiwan's response to upcoming disaster as Resilience. Taiwan soil liquefaction risk assessment will be done by combining hazard, vulnerability, and

In this study, CGS's drilling investigation result is selected as our database. Therefore, the assessment methodology used in this study is the same as CGS, which is called NJRA method [8]. This study adopts the soil liquefaction potential

� R resilience ð Þ (1)

is as Eq. (1) and the concept of risk matrix is shown in Figure 1.

Risk ¼ H hazard ð Þ� V vulnerability

zation (UNDRO) [7] proposed an operability definition for disaster risk: R(Risk) = H(Hazard) � V(Vulnerability), which is the most commonly used method of disaster risk assessment The study also uses this definition as a basis for assessing soil liquefaction risks. In order to fully realize the effect of land use, this study changes the past boundaries of risk, such as townships, towns, cities, and districts as the boundaries of risk allocation and takes the 100 � 100 m grid as the

can be decided and the potential disaster happened under climate change.

Taiwan's own soil liquefaction potential inquiry system.

Geographic Information Systems and Science

and management.

regional space unit.

resilience into risk matrix.

60

2.1 Risk matrix

2. Research methodology

The concept of the three-dimensional risk matrix.

mentioned in NJRA method, and considers different earthquake force designs as our hazard level grading. By comparing this study's result and CGS's result, people can figure out the difference between using normal soil liquefaction potential and our research's soil liquefaction potential that considers hazard, vulnerability, and resilience.

Second, vulnerability is based on the vulnerability indicators established by [9, 10]. To ensure that the database is correct, this study generally reviews the integrity of the indicators' data; ensures the indicators are selected appropriately and reflects the true development of the regions. Resilience indicators used in this study refer to [11, 12] for using the resilience indicators at all levels to consider the data integrity, the appropriateness of indicators which could showed the real condition of representative regions' development, and recovery. What is more, there is neither direct correlation nor the preference between the indicators. Therefore, the Pareto ranking (PR) method is used to standardize all the grading and abandon indicator weighing in order to establish the vulnerability and resilience.

This study seeks to simplify the mapping of potentially liquefiable areas by using Geographical Information Systems (GIS), and compared with the assessment method by the UNDRO to produce a map that could be used to evaluate potential damage in high risk areas of the county.

Cone penetration tests are used by the CGS in order to create GIS maps, but this is costly and not every county can afford to fund such studies on land. Geologic GIS layers are available due to the soil mapping of most counties by the CGS. Using the databank of social-economy and humanities in the county, along with other available data layers to narrow down the liquefaction risk of areas within the counties using ArcGIS and liquefaction criteria, the GIS layers for the Yun-Chia plain areas were modeled to select out the most liquefiable areas. These data layers were then combined to create a liquefaction risk map for Yunlin County and Chiayi County. This research can easily represent results straight forwardly.

#### 2.2 Pareto ranking (PR) analysis

Before using PR analysis, those factors have to be standardized by Eq. (2). After getting a standardized grade, this study sums each region's vulnerability indicators total grade (grades of each factor vulnerability indicators are 1–5) and integrates those hazard indicators into six degrees. Hazard indicators are mean sea level rising, land subsidence, and storm surge flooding. And finally, use Pareto ranking (PR) analysis to evaluate general risk in coastal areas; and give each region a hazard risk

level; the highest risk region gets level 9 and the lowest gets level 1, based on the principle to do PR analysis and evaluate each regional vulnerability.

Pareto ranking is a method for ordering cases on multiple criteria that has become popular in the context of genetic algorithms, where it is particularly valued because it often gives high rankings to those cases that only score heavily on one factor [13]. PR analysis is based on the principle of Pareto optimality. "Pareto optimality" is a formally defined concept used to determine when an allocation is optimal. An allocation is not Pareto optimal if there is an alternative allocation where improvements can be made to at least one participant's well-being without reducing any other participant's well-being. When no further Pareto improvements are possible, the allocation is a "Pareto optimum." A primary factor is selected from each vulnerability indicator. As shown in Figure 2, each point represents a grade of factor 1 and factor 2. If there is no point staying in the first quadrant, and there is no point ranked as high vulnerability degree. By taking same grade range region as a degree and following up the same step, this study can show each region's vulnerability distribution.

$$\text{z-score} = (\mathbf{X}\_i - \mathbf{M}) / \text{S} \tag{2}$$

3. Analysis resources of database

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

3.1 General introduction of study area

as high as 57%.

shown in Figure 3.

Figure 3.

63

Study area—the plate area in Yunlin and Chiayi.

According to the CGS disclosed geological drilling database, the Yunlin and Chiayi areas have relatively complete drilling data and complicated geographical environment. The area of environmental sensitive areas in Chiayi area of Yunlin is

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

The strata along the western coast of Taiwan, especially the Chiayi area of Yunlin, are mostly modern alluvial strata. Because of their unconsolidated strata, the soil layers are mostly interbedded layers of sand and clay. In the past, soil liquefaction took place in sites containing particles with a diameter of about 0.01-cm loose fine sand-based and high groundwater level characteristics of the soil. Therefore, this study focuses on the Yushe River alluvial fan plain in Yunlin County, Chiayi County in the Chia-Nan Plain, the grid scale is 100 100 m, as

where Xi is the different indicators' data; M is the average grade, S is the standard deviation, S ¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi <sup>Σ</sup>ð Þ Xi � <sup>M</sup> <sup>2</sup> =ð Þ N � 1 r� �, and <sup>N</sup> is the number of data

Figure 2. Concept of PR 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
