MDG Goal 7 Target 7D (Target 11) Slum Target City Census Workshop, Beirut, 27-29 September 2010 Gora Mboup, Chief Global Urban Observatory 1
MDGs Goal 7 Target 7D Slum target In the aftermath of the Millennium Declaration in September 2000, UN-HABITAT has the added responsibility to report on the significant improvement in the lives of slum dwellers, Target 7D, of the Millennium Declaration Goals (MDG)
Slum : until 2002, no internationally agreed definitions, concepts and method of computation Lack of slum definition and concepts Lack of slum data and indicators Not included in most MDG country report
Expert Group meeting 2002 UN-HABITAT organized a gathering of experts and other stakeholders from around the globe, to reach to an agreement on the universal definition of slums, in Nairobi, 28-30 October 2002.
Expert Group meeting 2002 The Expert Group Meeting (EGM) was a major consensus building exercise on the definition of slums, which enabled, the measurable articulation of the meta-global indicators, indicators and sub-indicators of each concept.
Slum Household Indicators from the EGM In urban area, a slum household is considered to be a group of individuals living under the same roof that lack one or more of the below conditions: Access to improved water Access to improved sanitation Access to secure tenure Durability of housing Sufficient living area
Physical expressions of slum lack of water, lack of sanitation, overcrowded conditions, and nondurable housing structures measure physical expressions of slum conditions. They focus attention on the circumstances that surround slum life, depicting deficiencies and casting poverty as an attribute of the environments in which slum dwellers live., expressed as a percentage.
Legal expression: security of tenure security of tenure has to do with legality, which is not as easy to measure or monitor, as the tenure status of slum dwellers often depends on de facto or de jure rights or lack of them. This indicator has special relevance for measuring the denial and violation of housing rights, as well as the progressive fulfillment of these rights.
Operational Definitions 1. Water & sanitation 2. Housing Durability & Sufficient Living Area 3. Secure tenure Access to improved water Piped connection to house or plot Public stand pipe Bore hole Protected dug well Protected spring Rain water collection Bottle water Access to adequate sanitation Direct connection to public sewer Direct connection to septic tank Pour flush latrine Ventilated improved pit latrine Pit latrine with slab Housing durability Permanency of Structure Compliance of building codes Location of house (hazardous) Sufficient living area A house is considered to provide a sufficient living area for the household members if three or less people share the same room. Evidence of documentation that can be used as proof of secure tenure status Either de facto or perceived / protection from forced evictions
Sources of Data Used in the Estimation DHS MICS JMP/PAHO* other/census Total Africa 63 26 14 22 125 Asia 17 13 6 15 51 Latin America 20 7 15 48 90 Oceania 1 14 3 18 Europe/Baltic 5 8 7 10 30 North America 2 2 World 106 54 56 100 316
Data limitations 1. Water & sanitation 2. Housing Durability & Sufficient Living Area 3. Secure tenure Access to improved water Good coverage Lack of categories Shared public No distinction between protected and not protected well Different reference dates Access to adequate sanitation Good coverage Lack of categories -Shared toilet -Latrine covered or not -Pit Latrine vs.improved latrine Different reference dates Housing durability Fair coverage for African, Latin and Asian countries Lack of categories -wall and roof Conditions of dwelling used for American and European countries Sufficient living area -Fair coverage for African, Latin and Asian countries -Model has been developed to estimate overcrowding levels Very weak coverage for all regions
Percentage of slum dwellers by MDGs region, 2005 Northern Africa 13.4 Sub-saharan Africa 63 Latin America and the Caribbean Eastern Asia 25.5 33 Southern Asia South-eastern Asia 34.2 40 Western Asia 25.8 Oceania 24.1 Percentage of slum dwellers
GOOD NEWS: BAD NEWS: over 200 m. people has more acce to basic services (2000-2010) 22 m. people lifted out of slum conditions every year Efforts made are not satisfactory Numbers of slum dwellers are growing 777 m. in 2000 828 m. in 2010
Slums in Africa 212 m. slum dwellers 20% of new urban residents become slum dwellers/year SSA progress = 5% The living conditions of 24 m. were improved = 11% of global effort Most successful countries: Egypt (39%) Morocco (46%) Tunisia
Slums in Asia 506 m. slum dwellers 61% of world slum pop. South and Eastern Asia, greatest progress Western Asia increased 12 m Impressive Improvements China (65 m. or 25%) India (60 m. or 30%) Other successful countries: Indonesia (33%) Viet Nam (31%) Turkey (20%)
Slums in Latin A. 111 m. slum dwellers 5% of new urban residents become slum dwellers/year Progress = 20% The living conditions of 30 m. were improved = 13% of global effort Most successful countries: Argentina, Colombia Republic Dominican (30% each) Guatemala, Mexico, Nicaragua, Peru (27-21% each)
Notion of shelter deprivation A simple alternative approach is to group slum households into categories that can be aggregated into moderately deprived (one shelter deprivation), severely deprived (two shelter deprivations) and extremely severely deprived (three or more shelter deprivations) with all possible combinations of types of deprivation.
Limitation of the slum definition Defining slums by household-level shelter deprivations, however, does not fully capture the degree of deprivation experienced by a given household or slum community, or the specific needs of that community. The current definition masks which specific deprivations households experience, as well as the severity of combined deprivations, and creates a challenge for monitoring.
Shelter deprivations No shelter deprivation Moderate shelter deprivation Severe shelter deprivation Extreme shelter deprivation
Distribution of households by degree of shelter deprivations 1.7 12.8 30.8 5.9 21.1 12 6.6 21 5.3 18.7 30.9 31.5 85.5 73 72.5 76 57.1 37.8 North Africa Sub Saharan Africa Latin America & the Caribbean South Asia South-Eastern Asia Western Asia Regions Non-slum One shelter deprivation Two or more shelter deprivations
Distribution of slum households (moderate deprivation) by type of shelter deprivation (Asia) 9.5 2.1 12.8 15.2 8.9 13.6 23.2 8.7 19.4 0.1 3.7 9 2.9 1.8 12 2.6 0.9 1.4 5.4 1.2 Bangladesh Nepal Philippines Turkey Vietnam Yemen Moldova Countries 0.9 11.3 2.2 2.8 0.7 11.2 1.2 6.2 Improved water Improved sanitation Durable housing Sufficient living
Geographical concentration and clustering of slums We can count slum dwellers with their shelter basic needs, but to implement efficiently assistance programmes for water, sanitation and housing we need to locate them. Are slum dwellers in the inner-city, the outskirts of the city or have they settled through the city with any specific location? Slum households with their type of deprivation can be located in a slum area as well as in a non-slum area within a given city.
Geographical concentration and clustering of slums Some countries have tried to differentiate the urban setting by type of settlement (slum/non-slum) based on administrative definition. This has tendency to underestimate the slum population by considering only the settlement classified slum by officials.
Remote sensing and slum identification Expert Group Meeting (21-23 May 2008) on remote sensing and slum monitoring organised by UN-HABITAT, the International Institute for Geoinformation Science and Earth Observation (ITC), The Netherlands, University of Columbia and other partners.
Remote sensing and slum identification The EGM focus was to document methods for the identification and delineation of slum areas based on very high resolution (VHR) remote sensing and supplementary data sets (e.g. census and related GIS data on infrastructure and services).
Remote sensing and slum identification The Much work is now being done on using VHR imagery for urban mapping, but most of it is focused on cities in the developed world and on general topographic and land use and land cover mapping. Although slum identification and mapping has received relatively little attention until recently, much can be learnt by examining the general developments on urban remote sensing and the limited studies that deal specifically with slums
Remote sensing and slum identification With the development of satellite imagery and GIS, it is promising that the slum setting can be easily identified and incorporated to censuses and surveys. This approach is not yet fully implemented to allow global measurement and comparison of levels of slums.
Multiple faces of slums There is no universal model of a slum in a physical sense that would allow the development of a standard method for all slum identification and mapping. Although certain variables are likely to be important in most situations the parameter settings will almost certainly always require local tuning.
Multiple faces of slums The diversity of slum conditions is such that even within one city many different manifestations of slums may be found, each of which may require specific methodological adjustments for identification and mapping.
Multiple faces of slums It is necessary to understand both the nature of building construction (characteristics such as size, materials, shape), the nature of other objects (such roads, health and social service facilities, open space), the characteristics of the site conditions (such as location in urban area, slope, natural vegetation, hazards), as well as the slum development process itself.
Multiple faces of slums The development stage of a slum area (infancy, consolidation, maturity) must be considered when deciding how it is to be identified and mapped from VHR images. The development of slum identification and mapping methods will need to explicitly consider how slum characteristics may change according to the development stage of the slum
Multiple faces of slums Slum development is a process that can take several different forms. Slums can develop through the gradual degradation of formal housing and social filtering processes. They can also develop through a variety of informal housing development processes (e.g. incremental and structured, incremental and unstructured, sudden and structured, sudden and unstructured). Each form has its own distinctive characteristics.
From slum household to slum EA: an alternative solution An alternative approach is to bring the slum household definition at the enumeration area (EA). In other terms to define slum EA based on the concentration of slum households in the EA. EA is expected to be as homogeneous as possible. This makes the use of EA a powerful tool in localizing slum. EA can be classified into slum and non-slum according to the level of concentration of slum households.
Integrating household data and geographic information Input HH data Digitize Features from satellite images GIS System UrbanInfo/Lake Victoria Info Digitize EA boundaries Monitoring/Policy Field verification/ Quality Control maintainance the GIS and the database
UrbanInfo
Where collaboration is needed? Put urbanization on the statistical agenda: Africa is faced with doubling its urban infrastructure in the next 20-30 years. Inform this process! Incorporate slum v non-slum in the national census and household survey sample design. Use of Remote Sensing & GIS Include slum v non-slum in standard nationals reports Collaborate with and provide information to local authorities
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