Global Report on Human Settlements 2007 - PoA-ISS

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176 Natural and human-made disasters Table 7.5 Comparative exposure to large natural hazards for 50 cities Source: Munich Re, 2004 Megacity Country Sum of Population Area City GDP Individual natural hazard Munich Re natural (million, (km 2 ) as percentage exposure assessment Natural hazard 2003) of national Hazards exposure GDP E V St So F T SS Risk Index Manila Philippines 15 13.9 2200 30 3 2 3 2 2 2 1 31.0 Tokyo Japan 12 35 13,100 40 3 1 2 2 1 1 2 710.0 Kolkata India 12 13.8 1400 < 10 2 0 3 2 3 0 2 4.2 Osaka–Kobe– Kyoto Japan 12 13.0 2850 20 3 0 2 2 2 1 2 92.0 Jakarta Indonesia 12 12.3 1600 30 2 2 1 2 2 2 1 3.6 Dhaka Bangladesh 12 11.6 1500 60 3 0 3 2 3 0 1 7.3 Hong Kong China 11 7.0 1100 10 2 0 3 2 2 0 2 41.0 Shanghai China 10 12.8 1600 < 10 1 0 3 1 2 0 3 13.0 Karachi Pakistan 10 11.1 1200 20 3 0 1 1 2 1 2 3.1 Mexico City Mexico 9 18.7 4600 40 3 3 0 2 1 0 0 19.0 Istanbul Turkey 9 9.4 2650 25 3 0 0 2 2 1 1 4.8 Miami US 9 3.9 2900 < 5 0 0 3 2 1 0 3 45.0 Lima Peru 8 7.9 550 50 3 0 0 1 1 3 0 3.7 Los Angeles US 7 16.4 14,000 < 10 3 0 0 2 2 0 0 100.0 Buenos Aires Argentina 7 13.0 3900 45 1 0 0 2 2 0 2 4.2 London UK 7 7.6 1600 15 0 0 0 3 2 0 2 30.0 Randstad Netherlands 7 7.0 4000 50 0 0 0 3 2 0 2 12.0 Singapore Singapore 7 4.3 300 100 1 0 1 2 1 1 1 3.5 Alexandria Egypt 7 3.7 100 Unknown 2 0 0 1 1 2 1 1.4 New York US 6 21.2 10,768 < 10 1 0 1 2 1 0 1 42.0 Seoul Korea, Rep. of 6 20.3 4400 50 1 0 2 1 2 0 0 15.0 Mumbai India 6 17.4 4350 15 2 0 1 1 1 0 1 5.1 Delhi India 6 14.1 1500 < 5 2 0 0 2 2 0 0 1.5 Tehran Iran 6 7.2 500 40 3 0 0 2 1 0 0 4.7 Bangkok Thailand 6 6.5 500 35 1 0 1 2 2 0 0 5.0 Baghdad Iraq 6 5.6 500 Unknown 2 0 0 2 2 0 0 1.3 St Petersburg Russia 6 5.3 600 < 5 0 0 0 2 2 0 2 0.7 Athens Greece 6 3.2 450 30 2 0 0 2 1 0 1 3.7 Medellín Colombia 6 3.1 250 Unknown 3 0 0 2 1 0 0 4.8 Rio de Janeiro Brazil 5 11.2 2400 15 0 0 1 2 2 0 0 1.8 Ruhr area Germany 5 11.1 9800 15 1 0 0 2 2 0 0 14.0 Paris France 5 9.8 2600 30 0 0 0 3 2 0 0 25.0 Chicago US 5 9.2 8000 < 5 1 0 0 2 1 0 1 20.0 Washington, DC US 5 7.6 9000 < 5 0 0 1 2 1 0 1 16.0 Bogotá Colombia 5 7.3 500 20 3 0 0 1 1 0 0 8.8 San Francisco US 5 7.0 8000 < 5 3 0 0 1 1 0 0 167.0 Sydney Australia 5 4.3 2100 30 1 0 0 2 1 0 1 6.0 Cairo Egypt 4 10.8 1400 50 2 0 0 0 2 0 0 1.8 Beijing China 4 10.8 1400 < 5 2 0 0 2 0 0 0 15.0 Johannesburg South Africa 4 7.1 17,000 30 1 0 0 2 1 0 0 3.9 Bangalore India 4 6.1 300 Unknown 1 0 1 1 1 0 0 4.5 Santiago Chile 4 5.5 950 15 2 0 0 1 1 0 0 4.9 Milan Italy 4 4.1 1900 15 1 0 0 2 1 0 0 8.9 Sâo Paulo Brazil 3 17.9 4800 25 0 0 0 2 1 0 0 2.5 Lagos Nigeria 3 10.7 1100 30 0 0 0 2 1 0 0 0.7 Moscow Russia 3 10.5 1100 20 0 0 0 2 1 0 0 11.0 Madrid Spain 3 5.1 950 20 0 0 0 2 1 0 0 1.5 Berlin Germany 3 3.3 900 < 5 0 0 0 2 1 0 0 1.8 Abidjan Côte d’Ivoire 2 3.3 500 50 0 0 0 1 1 0 0 0.3 Notes: Natural hazards key is defined as follows (3 = high; 2 = medium; 1 = low; 0 = none): E = earthquake; V = volcanic eruption; St = tropical storm; So = other storms (winter storms, hailstorms, tornado); F = flood; T = tsunami; SS = storm surge.
Disaster risk: Conditions, trends and impacts 177 preparedness of individual cities. This is evident when comparing the contrasting cases of Kobe (Japan) (hit by a 7.2 Richter magnitude earthquake in 1995) and Marmara (Turkey) (hit by a 7.4 Richter magnitude earthquake in 1999). The Kobe (or Great Hanshin) earthquake was among the worst disasters to have befallen modern Japan since it claimed 6433 lives. The Marmara earthquake was similarly catastrophic; but with 18,000 lives lost, was three times as deadly as the Kobe earthquake. 17 In Kobe, strong engineering standards reduced losses; but a lack of planning for social systems to identify vulnerable groups and help in response, relief and reconstruction compounded losses. In Marmara, decades of ineffective building and planning regulation meant many modern buildings were not adequately resistant to earthquakes, and accumulated risk translated into high human loss. As in Kobe, failure in social planning also undermined response and reconstruction. The Tangshan earthquake in China in 1976 similarly illustrates how differential vulnerability shapes loss in different human settlements (see Box 7.4). DISASTER IMPACTS This section differentiates between and discusses the main impacts of disasters. The capacity for disaster impacts to cause knock-on consequences and additional risks through secondary human-made disasters and the ecological impacts in the city is also examined. Although the review of natural and human-made disasters goes some way in indicating their destructive power, it can only show tip-of-the-iceberg losses. Gaps in data and contradictory statements make comprehensive assessment of disaster impacts difficult. Even assessments of disaster incidence, although made easier by global media, are not easily undertaken at the global scale, where there is no standard system for verifying local reports. Systematic gaps in disaster data collection and presentation mean that loss is underestimated in three different ways: • Psychological and livelihood impacts are seldom recorded, with the majority of disaster impact data focusing on mortality and economic loss. 18 • Macro-economic loss estimates cannot easily capture the secondary and knock-on consequences of disaster for economic production and trade. • Disasters affecting small urban settlements and smallscale disasters in large cities are often overlooked, despite evidence suggesting that, in aggregate, smallscale disasters may be associated with at least as much suffering and loss as the large-scale disasters in cities that make front page news. 19 At a minimum, psychological trauma, livelihood losses and losses to productive infrastructure should be included in measuring the full impact of disasters. Box 7.4 The Great Tangshan earthquake, China The most destructive earthquake of the past 400 years occurred in Tangshan (China) in 1976. The magnitude 7.8 earthquake occurred in the early morning while the majority of the over 1 million residents slept and lasted 14 to 16 seconds. Later in the day, the city was further paralysed by an aftershock with a magnitude of 7.1. The official death toll published by the Chinese government was about 240,000. More recent estimates place the total for casualties at over 0.5 million. While nearly 50 per cent of the population of the city of Tangshan died during the earthquake, the neighbouring County of Qinglong had only one death out of 470,000 residents. Scientists from the State Seismological Bureau identified six main factors that contributed to the unprecedented destructiveness of the Tangshan earthquake, including high population density, existence of few earthquake-resistant buildings, occurrence of shock while people were sleeping followed by a strong aftershock later, paralysis of critical infrastructures and the geological conditions under the city. 20 Yet, the disparity between the death toll in Tangshan and Qinglong cannot be accounted for by these factors alone since both counties experienced similar vulnerabilities. The divergence in the death toll between Qinglong and Tangshan comes from an additional seventh factor: the difference in earthquake preparedness in the two areas. Tanghsan’s over-reliance on scientific monitoring of seismic activity for national preparedness partly contributed to the massive loss of life during the 1976 earthquake. Two years earlier, a report by the Chinese Academy of Science had advised greater preparedness and monitoring in North China. During the following two years, Qinglong County increased the number of earthquake monitoring stations and intensified public education using pamphlets, films, posters, drills and community discussions, far beyond those reported to have been undertaken in Tangshan. Qinglong’s successful disaster mitigation was a best-case outcome of the coordination between public administrators, scientists and the public. Source: Pottier et al, 2007 Direct and systemic impacts of disaster Disaster impacts can be classified as either direct or systemic. Direct impacts include damages directly attributable to the disaster, including lives lost and injuries and physical damage to infrastructure and buildings. Direct (and other) losses can also be caused by knock-on human-made or natural disasters. For example, an earthquake can trigger chemical fires or liquefaction. If uncontained, direct impacts can be magnified through failures in critical infrastructure and services in the city, leading to systemic impacts such as outbreaks of disease, social violence and lack of access to electricity, potable water or food. For instance, a review of health service infrastructure in Latin America and the Caribbean found that around half of all hospitals are sited in high-risk areas. Perhaps not surprisingly, this report also found that over the 1980s and 1990s, 100 hospitals and 650 health centres have been destroyed in disasters. This is a little over 5 per cent of all hospitals in this region. 21 In turn, such disruptions can lead to instabilities in the political economy of the city and undermine economic development. Systemic loss can further be differentiated into indirect losses and secondary effects. Indirect losses (sometimes called flow losses) are the costs of goods that will not be produced and services that will not be provided because of a disaster. Secondary effects are generated by macro-economic distortions. 22 Urban areas are characterized by great diversity in land use as well as environmental variability (e.g. in slope angle and direction, soil properties and land altitude). This Gaps in data … make comprehensive assessment of disaster impacts difficult
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ENHANCING URBAN SAFETY AND SECURITY
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First published by Earthscan in the
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INTRODUCTION Enhancing Urban Safety
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ACKNOWLEDGEMENTS The preparation of
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x Enhancing Urban Safety and Securi
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xii Enhancing Urban Safety and Secu
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xiv Enhancing Urban Safety and Secu
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xvi Enhancing Urban Safety and Secu
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xviii Enhancing Urban Safety and Se
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LIST OF FIGURES, BOXES AND TABLES F
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xxviii Enhancing Urban Safety and S
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xxx Enhancing Urban Safety and Secu
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xxxii Enhancing Urban Safety and Se
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4 Understanding Urban Safety and Se
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1 CHAPTER CURRENT THREATS TO URBAN
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Current threats to urban safety and
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2 CHAPTER VULNERABILITY, RISK AND R
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Vulnerability, risk and resilience:
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29 simply ‘give up’ in the face
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46 Urban crime and violence Box II.
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48 Urban crime and violence it has
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50 Urban crime and violence Formal
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52 Urban crime and violence Contact
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54 Urban crime and violence Per 100
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56 Urban crime and violence Burglar
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58 Urban crime and violence Percent
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60 Urban crime and violence Figure
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62 Urban crime and violence Table 3
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64 Urban crime and violence Youth g
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68 Urban crime and violence Type of
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70 Urban crime and violence From a
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72 Urban crime and violence One vio
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74 Urban crime and violence High ho
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76 Urban crime and violence Abused
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78 Urban crime and violence General
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82 Urban crime and violence porate
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4 CHAPTER URBAN CRIME AND VIOLENCE:
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86 Urban crime and violence UN-Habi
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88 Urban crime and violence Box 4.2
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90 Urban crime and violence Box 4.4
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92 Urban crime and violence Legisla
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94 Urban crime and violence above w
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96 Urban crime and violence Campaig
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98 Urban crime and violence Availab
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100 Urban crime and violence Box 4.
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102 Urban crime and violence In som
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104 Urban crime and violence Initia
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106 Urban crime and violence The mo
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108 Urban crime and violence Vander
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112 Security of tenure Box III.1 Se
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5 CHAPTER SECURITY OF TENURE: CONDI
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116 Security of tenure Table 5.1 A
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118 Security of tenure Fully legal
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120 Security of tenure Box 5.4 Secu
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122 Security of tenure Urban tenure
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124 Security of tenure At least 2 m
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226 Natural and human-made disaster
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236 Towards safer and more secure c
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11 CHAPTER ENHANCING TENURE SECURIT
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276 Enhancing Urban Safety and Secu
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12 CHAPTER MITIGATING THE IMPACTS O
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304 Summary of case studies Since i
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306 Summary of case studies • The
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308 Summary of case studies tions w
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310 Summary of case studies environ
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312 Summary of case studies others.
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314 Summary of case studies purpose
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316 Summary of case studies These e
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318 Summary of case studies develop
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320 Summary of case studies tion ex
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322 Summary of case studies Housing
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324 Summary of case studies Prolong
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326 Summary of case studies momentu
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330 Statistical annex Islands, Micr
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332 Statistical annex NOMENCLATURE
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334 Statistical annex Population, u
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336 Statistical annex SOURCES OF DA
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410 TABLE C.7 continued Enhancing U
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INDEX ACHR (Asian Coalition for Hou
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Index 435 security of tenure 134 co
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Index 437 domestic abuse see intima
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Index 439 hazard management 169 haz
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Index 441 Kosovo, security of tenur
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Index 443 participation 38, 296-299
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Index 445 individual 34-35 municipa
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Index 447 gun ownership 78 Homeless
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