Urban Slum Mapping in

Bangladesh

Center for Environmental and Geographic Information Services

Dhaka, Bangladesh

Iffat HuqueHead, Remote Sensing Division

Objectives of the presentation

To present different methods used for urban slum mapping in Bangladesh

Potential of very high resolution satellite images for identification and mapping of the urban slums in Bangladesh

Urban Population – Bangladesh

Total population 140 million

Total urban population 34 million (24 % of

Total)

Total number of urban households 3.9 million

Urban population growing 3.5% annually

Projected urban population in 2015 is 50

million

Basic Data on SlumsSix major cities

Total population of the cities 15.5 million

Total slum population 5.4 million (35% of total)

9000 slum clusters

Total number of slum households 1 million

Population density in slums about 200000/sq km

Between 1996 and 2005, the total population living in the slums of Dhaka more than doubled

Source: CUS, 2005

(Dhaka, Chittagong, Khulna, Rajshahi, Sylhet, Barisal )

Slum mapping/census

initiatives in Bangladesh

Bangladesh Bureau of Statistics (BBS)-

Census of Slums in Bangladesh 1985 and 1986

Census of Slum Areas and Floating Population 1997

Studies by Center for Urban Studies (CUS) – 1987, 1996 and 2005

Local Government Engineering Department

(LGED) – Spatial Poverty Mapping of Dhaka Metropolitan Area, 2005

BBS - Census of Slum Areas

1997Definition:A slum is a cluster of compact settlements of 5 or more households which generally grow very unsystematically and haphazardly in an unhealthy condition and atmosphere on government and private vacant land. Slums also exist in the owner based household premises

Criteria:Predominantly very poor housingVery high housing densityHousing materials are very cheap and low qualityPoor sewerage and drainage or even absence of such facilities

Inadequate, unhealthy drinking water supplyInsufficient or absence of street lightingLittle or no paved streetsInhabited by poor, uneducated and below poverty level people

BBS - Brief Methodology

Areas covered Dhaka Megacity, 3 other major cities, 14

smaller Cities and 100 paurashavas (municipalities)

Prepare maps and list of slum areas by quick count method

Large slums were divided into enumeration areas (EAs) each

compromising of about 200 households

Smaller slums were merged to form an EA of same size within

the same ward/municipality

Five percent sample HH were surveyed from each EA to

collect detailed data

For quality check

Post Enumeration Quality Check Survey

Special Evaluation Survey

BBS Census of

Slum Areas

1997

• Total Number of Slums

identified -2,991

• Collected Information• Slum areas

• Housing structure and

Characteristics

• Household size and

composition

• Household facilities (source of

light, sanitary facilities, drinking

water)

• Population size, distribution

and growth

• Employment and occupation

CUS - Mapping and Census, Slums

of Urban Bangladesh 2005

Mapping and census of 6 major cities was carried out as a basis for the 2006 Urban Health

Survey(UHS)

Carried out by Centre for Urban Studies for

National Institute of Population Research and

Training (NIPORT) and

MEASURE Evaluation of University of North

Carolina

Funded by USAID Bangladesh

Objectives Prepare maps to identify location and boundaries of all slums

Record the characteristics of slums and squatter settlements

Identify the slums and squatter settlements in terms of their physical, socio-economic and

environmental characteristics

Determine their overall legal status

Prepare a database

CUS Study

Predominantly very poor housing

Very high population density and room crowding

Very poor environmental services, especially water and

sanitation

Very low socio-economic status

Lack of security of tenure

Definition: Slums are defined as settlements with a

Minimum of 10 householdsAND

An urban community has to meet at least 4 of the above

criteria to qualify as a “slum”

CUS Study

Predominantly very poor housing( jhupris- shacks, kutcha, semi-pucca- over 75% of the structures in a community would have such poor construction)

Very high population density and room crowding(Overall density 300 persons/acre, predominantly (>75%) of single room family occupancy)

Very poor environmental services, especially water and sanitation

(key indicators- very poor sanitation and water access- <50% of HH are served with a sanitary latrine – sewerage, septic tank, or water sealed latrine- water access)

Very low socio-economic status(key indicators- high prevalence of low income people – over 75% with income below poverty level – Tk 5000 HH income per month –based on urban poverty line per capita income estimates)

Lack of security of tenure(Indicator- vulnerability to eviction)

Criteria for definition of “slum”

CUS Study

CUS Study

Base Map Preparationcollection of SOB and City Corporation maps

update road networks and major urban features from satellite images

final base map preparation

Preliminary identification of slumsidentification of slums from satellite images using visual interpretation

incorporating the identified slums in the base map

Ground truthingslums identified from images were verified on the ground

slums that are not readily apparent from the satellite images were also identified from ground truthing survey

Survey of Slum Clusters (key informant)slum size (physical area, number of households and population)

environmental and socio-economic conditions

Final slum map preparation and data processingdigitization of identified slums using GIS software

if any confusion during digitization revisit of the site was done

database preparation (data collected through slum survey)

Brief Methodology

CUS Study

GIS slum maps of six study cities

list of slums with addresses, number of households and

total population

Slum Censusnumber of slum clusters, slum size by households, slum population

area of land covered by slums, density of population in slums

housing conditions and floor space in slums

slum land ownership pattern

Environmental and Infrastructural FeaturesSources of drinking water and access to latrines

Drainage situation in slums, garbage disposal in slums

Occupational pattern and Income patterns

Tenure Insecurity

Results

CEGIS- Slum mapping from high

resolution satellite images

Objectives:Test methods of interpreting slums from high resolution satellite images

Study the potential of these image for slum mapping in Dhaka

Make recommendations on data and methodologies

Data Used

Satellite Images

IKONOS 1 m Pan, 2002

IKONOS 4 m Multispectral 2002

QuickBird 60 cm Pan 2004

QuickBird 2.4 m multispectral 2004

QuickBird 60 cm Pan-sharpened 2006

Slum GIS Data from CUS, 2005

Ground Truth Data

Methodology

Reconnaissance survey of physical

characteristics of slums which can help identify

them in images

Test various pixel based classification

Texture analysis

Visual interpretation - on screen digitization

Pattern, Shape, Size, Density, Color and association

Ground truthing

Comparison with slum data of CUS

Comparison with ground truth data

Some views….

• Very little or no vegetation

• Similar orientation of structures

• Contiguous large area

• Irregular street patterns

• With more vegetation

• Haphazard orientation of structures

• Contiguous large area

Types of Slums in Dhaka City

As seen in QuickBird Pan-sharpened image, 2006

• Corrugated iron roofs

• Width: 3m, Length: 5m -12m

• Housing structure –Jhuprior shacks-having roof top made of bamboo, sun grass, gunny bags and polythene sheets

• Size approximately 2m by 3m

• Plain/corrugated iron roofs

• Size approximately 10m by 7m

• Inside planned residential plots with regular street patterns

• Scattered concrete building (Not slum dwellings)

• Corrugated iron roof

• Width 3m by 5m

• Lined in long straight lines without any space between houses

• Contiguous large area

• Corrugated iron roof

• Mixed sizes

• In plots in un-planned residential areas (irregular street pattern)

• Scattered concrete building (Not slum dwellings)

• Plain/Corrugated iron roofs

• Various different sizes

• Mixed – small industries and slums

• Plain/Corrugated iron roofs

• Small sized structures

• Contiguous large area

• Corrugated iron roof

• Size 4m by 8m

• Looks like slum but actually market place

• Distance between structures are more than that of slums and more regular

• Mostly jhupri - shacks

• Roof top - bamboo, sun grass, gunny bags; most of the times covered by polythene sheets

• On roadside or railway track

• Mixture of corrugated iron roof and jhupri

• On roadside or railway track

Slum Mapping from high resolution

satellite images- CEGISTotal Dhaka Metropolitan Area 300 sq km

Number of Wards 91

Number of Unions 10

Area of Ward 02 2.5 sq km

Area of Ward 87 0.5 sq km

Ward-02

Ward-87

• Slums from CUS survey 2005

• Slum digitized from QuickBird image

Ward 2: QuickBird

image 2006

Area

(Acre)

% of

total

Ward-2 674 100

CUS

Slum120 18

Image Slum

140 21

Ward 2: QuickBird

image 2006

• Slums from CUS survey 2005

• Slum digitized from QuickBirdimage

Ward 87: QuickBird image 2006

Area

(Acre)

% of

total

Ward-87 124 100

CUS

Slum88 71

Image

Slum60 48

Ward 87: QuickBird image 2006

Pan-sharpen QuickBird, 2006

Comparison with CUS data –

WARD 87

Pan IKONOS, 2002

Slum identified from imageCUS Slum data

• Slum identified from image 2006 and field survey

• Slum found on image in 2002

• Not slum in image (Field verification done)

Pan-sharpen QuickBird, 2006

Comparison with CUS data –

WARD 87

Slum identified from imageCUS Slum data

• Cluster of corrugated iron roof structures

• Average size 12 m X 15 m• Factory

• Corrugated roof structures on the road side

• Shops

Comparison with CUS data –

WARD 87

Slum identified from image CUS Slum data

• Cluster of corrugated roof structures

• Average size 12 m X 15 m• Factory

• Not slum in image (Field verification done)

Multispectral IKONOS (4 m), 2002

Texture Analysis – Ward 2

Ward 2 Boundary

Slum Areas

Texture Analysis (Mean Euclidean Distance 15 X 15 window) on Multispectral IKONOS (4 m), 2002

Texture Analysis – Ward 2

Slum clusters

Slum clusters

IKONOS Pan (1 m), 2002

IKONOS Pan (1 m), 2002

Texture Analysis (Mean Euclidean Distance 15 X 15 window) on Multispectral IKONOS (4 m), 2002

Texture Analysis – Ward 2Texture AnalysisMean Euclidean Distance, 15 X 15 window

Ward 2 Boundary

CUS Slum data, 2005

Texture Analysis

Ward Boundary

CUS Slum data, 2005

Field/playground looks similar to slum clusters

Small slum clusters (40 m X 40 m) can not be detected

Roads look similar to slum clusters

Conclusions

For initial identification of slum clusters Texture Analysis is a promising method

Texture analysis with 4 m multispectral image gave better results than 2.4 m multispectral image

Visual interpretation of pan-sharpened high resolution images gives much more detail and accurate information –but special care must be taken to use expert knowledge for interpretation

Further study of characteristics of slums in terms of building materials, patterns, size, density and their manifestations in the images will provide better interpretation keys for identification of slums

Development of linkages with in-country institutions will

avoid duplication of work and improve the quality of

outputs and strengthen local institutions leading to

sustainability.

UN – HABITAT can make use of country generated data by

linking up with the existing or planned initiatives of other

donors such as USAID and World Bank in mapping the slums

UN – HABITAT can support Bangladesh Bureau of Statistics

to continue to carry out slum census

The methodologies currently being used can be further

improved with modern remote sensing technologies

Recommendations

Thank you

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