Author details

phenomenon that the communities closer to the reservoir and contained inside the network of the water supply systems have lower resilience levels. These areas show closer exposure to the hazard and have less time to provide rapid responses, and also these communities take charge of the protection of network in disaster; reversely, the communities located far away from the reservoir, as well as the downtown area, have better economic status and higher service level. Absorptive, adaptive, and recovery capacities are analyzed, respectively, for Periods I, II, and III, with the results expressed in Figure 5. The complete clustering results are presented in Table 3 with associated FID. Figure 5 shows that for different periods, the resilience level of each community varies between three different capacities.

Period I Period II Period III

FID

13, 17,19,24,27

14, 18, 20, 26

27, 28

19, 26

0.0573 2, 5, 8, 10, 16, 22, 24, 25

0.0607 0, 4, 6, 9, 11, 13, 15

1.3633 3, 7, 26 0.4597 1,5,8,9,12,17,20,25

1.8941 0, 1, 2, 16 0.5284 2, 3, 6, 10, 13, 16,

0.9267 4, 9, 10, 11, 14, 15, 18, 20, 21, 22, 23, 25, 28

0.0669 4, 7, 8, 9, 10, 12, 15, 16, 21, 23, 24, 25, 27

3 0.8538 0, 3, 17, 19 0.1589 0, 3, 17, 19 0.3134 0, 3, 17, 19, 26 4 1.6285 22, 28 0.3322 22, 28 0.6941 22, 28

Dj Region unit FID

0.2692 4, 11, 14, 15, 18, 22, 23, 28, 26

0.4120 0, 2, 3, 7

19, 21, 24, 27

0.1216 4, 7, 8, 9, 10, 12, 15, 16, 21, 23, 24, 25, 27

0.1693 1, 2, 5, 6, 11, 13, 14, 18, 20

0.8393 2, 3, 7, 9, 12, 13, 14, 18, 26

0.9826 17, 20, 21, 23,

0.9858 0, 5, 10, 11, 15, 16, 22

1.1447 1, 4, 6, 8, 19,

27, 28

24, 25

Capacity D Region unit FID Dj Region unit

23, 28

20, 25

19, 21, 24, 27

11, 12, 13, 14, 15, 16, 18, 20, 21, 23, 25

Recovery 1 0.3043 4, 6, 9, 11, 15, 22, 25 0.0529 3, 7, 20, 21, 23,

20, 21, 24, 27, 28

20, 26

4 0.3460 1, 8, 12, 14, 23 0.0667 1, 12, 14, 17, 18,

2 0.3119 5, 7, 13, 16, 17, 19,

3 0.3295 0, 2, 3, 10, 13, 18,

Three capacity analyses under Periods I, II, and III.

3 0.7988 1, 5, 8, 9, 12, 17,

4 0.9418 2, 3, 6, 10, 13, 16,

2 0.7354 0, 2, 3, 7, 26 1.1995 5, 6, 8, 10, 12,

2 0.7357 5, 7, 24, 26, 27 0.0894 1, 2, 5, 6, 11, 13,

Absorptive 1 0.6163 4, 11, 14, 15, 18, 22,

Geographic Information Systems and Science

Adaptive 1 0.4996 1, 2, 4, 6, 8, 9, 10,

The objective of this study was to propose a decision-making process and a methodology of system resilience assessment for urban lifeline systems. In this work, formation of the concept "system" should not only be limited to system infrastructures but also be expanded to the combination of other related complex systems such as demographic system, economic system, and environmental system in the study region. The advantages of using ANP as weight methods for the

4. Conclusion

Table 3.

54

Wenjie Huang<sup>1</sup> \* and Mengzhi Ling<sup>2</sup>

1 Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore

2 Department of Architecture, School of Design and Environment, National University of Singapore, Singapore

\*Address all correspondence to: wenjie\_huang@u.nus.edu

© 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, provided the original work is properly cited.
