Global Report on Human Settlements 2007 - PoA-ISS

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196 Natural and human-made disasters …technical advances … for hazard mapping … are often lacking in developing countries… environment vis-à-vis an analysis of exposure to hazard and susceptibility to harm, as well as capacity to respond to disasters. Hazard and risk assessments employ a range of techniques, from quantitative analysis built around scenario modelling and mapping to qualitative, non-technical approaches, depending upon the kinds of data that need to be generated. Hazard mapping Hazard assessment involves an analysis of the likelihood of occurrence of natural or human-made hazards in a specific future time period, including their intensity and area of impact. 4 Data generated through hazard assessments needs to be presented to decision-makers and communities at risk to raise awareness and enable the design of appropriate interventions and policies. One approach is the use of maps to depict the spatial location, size and frequency of hazards. This allows general statements to be made about the exposure of national urban systems and individual cities to hazards. ■ Mapping natural hazard At the global scale, hazard mapping is well advanced for volcanic, earthquake, flood, wind and landslide hazards. 5 Many countries also have national hazard maps, particularly of geophysical hazards. While global- and national-scale hazard maps can help to identify national legislative or policy planning priorities, planning at the city level requires more detailed information. Many cities in middle- and highincome countries, particularly those which are administrative or industrial centres, have detailed single and multi-hazard maps. During the last decade, the number of cities with seismic hazard maps has increased. 6 Other hazards, such as flooding and extreme temperatures, vary spatially, requiring more continuous monitoring and mapping, which can be more costly. The advent of geographic information systems (GIS), coupled with satellite imagery of disaster events, have revolutionized the amount of data that is now available worldwide. While technical advances have increased the potential for hazard mapping, they have also generated inequalities in hazard assessment capacities. Technical approaches require financial investment in hardware and human resources that are often lacking in developing countries and are beyond reach for poorer urban authorities. Partnerships between technical advisory bodies and national centres for disaster management offer a potential mechanism for technology and skill transfer. One example of this is the Government of India–United Nations Development Programme (UNDP) Urban Earthquake Vulnerability Reduction Project, shown in Box 8.1. 7 Low-impact, high-frequency hazards are less likely to be mapped, despite their erosive impact on human health Box 8.1 India’s national hazard map: A foundation for coordinated disaster risk reduction An example of cooperation in disaster risk reduction between an international organization and a national government is the Government of India–United Nations Development Programme (UNDP) Disaster Risk Management Programme. A key subcomponent of this programme is the Urban Earthquake Vulnerability Reduction Project, implemented between 2003 and 2007. The project aims to raise awareness of earthquake risk in urban areas among decision-makers and the public and to improve disaster preparedness. Several of India’s populous cities, including the capital, New Delhi, are located in zones of high seismic risk. National data on seismic hazard has been used to identify 38 cities with populations of 500,000 or more that have become the focus for the project. The map in Figure 8.1 was developed by the project and shows four levels of seismic risk and 60 cities from which the 38 partner cities were selected. Key expected outcomes of the project, among others, include enhanced disaster risk management capacity, effective administrative and institutional frameworks for earthquake risk management in the most exposed urban centres, and development of emergency, preparedness and recovery plans for those urban centres. The project also intends to build local capacity for risk assessment, preparedness and response. Source: adapted from UNDP India, www.undp.org.in/index.php?option=com_ content&task=view&id=?84&Itemid=264 Jammu HARYANA Meend Delhi Banhilly UTTAR RAJASTHAN Agra PRADESH Jodhpur Lucknow Garabor Kanpur BIHAR Keta Allahabad Patna Varanasi GUJARAT Ahmadabad Bhopal Jabalpur Ranchi Asansol Jamnagar Rajkot Indore MADAYA Jamshedpur PRADESH Kolkata Vadodara Bhavnagar ORISSA Surat Nagpur Durg Raigarh Cuttack Nashik MAHARASHTRA Bassein Ahmadnagar Bhubaneswar Mumbai Pune Warangal Figure 8.1 Vishakhapatnam Hyderabad Indian earthquake ANDHRA Vijayawada zones indicating 60 Belgaum PRADESH Goa cities with a population exceeding 0.5 million Mangalore Bangalore Chennai Mysore TAMIL NADU Pondicherry Kozikhode Salem Coimbatore Tiruchirapalli Kochin Madurai LAKSHADWEEP PUNJAB KARNATAKA Trivandrum HIMACHAL PRADESH Dehra Dun KUMAUN City location Very high risk zone High risk zone Moderate risk zone Low risk zone ASSAM Gauhati
Policy responses to disaster risk 197 and livelihoods. This gap has been filled in some neighbourhoods by community-based hazard and risk mapping projects. This data, combined with national- and city-level records of past events, can be used to identify priorities for urban planning and construction standards. Less information is available at the global scale for hazards that affect the lifelines to a city such as drought, or emerging hazards such as heat and cold shocks. <strong>Global</strong>-scale data can be used to extend analyses of hazard exposure beyond the municipal boundary to demonstrate the vulnerability of cities to disasters affecting their hinterland by disrupting trade, or blocking access and flows of resources and waste. ■ Mapping human-made hazard National directories of human-made hazards are becoming more common, and many are open to the public. In the UK, the Environment Agency hosts a pollution and hazardous waste sites inventory. This is searchable by postal code and also provides information on water quality and flood hazard. 8 In the US, Green Media’s Toolshed website includes a searchable scorecard, which provides data on chemicals being released from any of 20,000 industrial facilities, or a summary report for any area in the country. 9 More difficult is the mapping of human-made risk associated with industrial facilities, buildings’ integrity or transport infrastructure. Much of the information needed to build comparative hazard datasets is commercially valuable and therefore not released to the public. Local authority land-use planning maps and schedules include information on industrial sites where hazardous activities are undertaken, and can be used as a basis for urban industrial hazard mapping. This is particularly valuable for assessing the risk of human-made disasters caused by natural hazards. More difficult is the acquisition of data on informal-sector industrial activities, such as tanneries or fireworks factories. These might not represent a significant hazard individually; but, in aggregate, unplanned industrial activity is a major risk to health from air, water and ground pollution and from fire and explosion hazards. Risk is heightened because of the unregulated nature of informal industrial activity and its close proximity to densely settled residential areas. Risk assessments for individual cities As noted in Chapter 7, there is limited comparative data on natural disaster risk and impacts at the city level. Two initiatives have made major contributions at this level of analysis – namely, the Natural Hazards Risk Index for Megacities by Munich Re (see Chapter 7) 10 and the Earthquake Disaster Risk Index used by GeoHazards International (GHI). GHI developed and applied an Earthquake Lethality Estimation Method in 2000/2001. The method produces results that indicate the relative severity of earthquake risk, the sources of risk within each city, and the relative effectiveness of potential mitigation options. The same results are also produced for the exposure of school children to collapse of educational buildings. The method was applied to cities in Box 8.2 Estimating urban loss of life to earthquakes GeoHazards International’s (GHI) Earthquake Lethality Estimation Method estimates the number of lives that would be lost if all parts of a city experience earthquake shaking at a level that has a 10 per cent chance of being equalled or exceeded in 50 years. The method has been applied to assess the risk of life loss in 22 cities in the Americas and Asia. Deaths caused by building collapse, earthquake-induced landslides and fires are included. Capacity for organized search, rescue and emergency medical care is also considered. Results are validated over time through a comparison of estimates with actual loss. GHI’s approach is especially noteworthy because of its emphasis on the safety of school children, which reflects the vulnerability of schools. Data is collected through meetings with local experts and city officials dealing with seismology, soils and landslides; city planning; building inventory; school buildings; emergency response; medical emergency preparedness; hospital emergency preparedness; and fire preparedness. Results show great variation in the risk of earthquake-induced loss of life in cities. For example, in the American region, a person living in Mexicali is almost three times more likely to be killed by an earthquake than a person living in Quito, and about ten times more likely than a person living in Santiago. In the Asian region, a person living in Kathmandu is about nine times more likely to be killed by an earthquake than a person living in Islamabad and about 60 times more likely than a person living in Tokyo. GHI’s approach is also able to identify differences in the immediate causes of death and, thus, guide the subsequent development of mitigation strategies and policies. For example, in a comparison between Delhi and San Salvador, while most of the deaths in Delhi will be due to building collapse and earthquake-induced fires, an important fraction of the deaths in San Salvador will be due to earthquake-induced landslides. The analysis of school risk also shows differentiated vulnerability across cities. A school child in Kathmandu is 400 times more likely to be killed by an earthquake than a school child in Kobe and 30 times more likely than a school child in Tashkent. Source: GHI, 2001 the Americas and Asia, differentiated by city size (see Box 8.2). The philosophy of GHI is that loss estimation is both a process and a product. The process aspect engages decisionmakers at the community and city levels and recognizes that data alone is insufficient to effect change in human behaviour. The process of assessment includes local expertise and favours rapid assessment that can feed into ongoing decision-making over possibly more accurate, but also more costly and less participatory, methods. Readily available information is supported with data from local experts. The final results allow a quantitative assessment of the effectiveness of mitigation options under consideration. Including indicators for social vulnerability in risk assessment at the city level is difficult since it requires the availability of relevant data on population and social indicators. For instance, research on risk of heat waves in London has used census data and is appropriate for those countries that have spatially disaggregated and high-quality census data. 11 In the majority of cities, especially those that are rapidly expanding in poorer countries, this is not a reliable source of data. Other methods, such as the use of satellite information on night-time lights and fires, offer an alternative, but still not comprehensive, measurement of population density in rapidly expanding and poor cities. Comparison of disaster risk between districts within a city has rarely been undertaken. One example of this …there is limited comparative data on natural disaster risk and impacts at the city level
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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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xviii Enhancing Urban Safety and Se
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LIST OF FIGURES, BOXES AND TABLES F
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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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126 Security of tenure Market-based
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128 Security of tenure Box 5.11 Urb
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130 Security of tenure Operation Mu
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132 Security of tenure Control of l
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134 Security of tenure Box 5.18 Sec
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136 Security of tenure NOTES 1 Habi
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138 Security of tenure Box 6.1 The
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140 Security of tenure It would be
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142 Security of tenure Box 6.7 Land
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144 Security of tenure Box 6.10 Wha
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246 Towards safer and more secure c
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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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