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IntroductionThe eradication of slums is currently on the global agenda.One of the Millennium Development Goals (MDGs) is to‘achieve significant improvement in the lives of at least 100million slum dwellers, by 2020’ (UNDP, 2003). Efforts arebeing made to localise the MDGs. But in many developingcities, the scarcity of relevant data – coupled with lack of bothhuman and financial resources for data collection and analy-sis – is a significant constraint.

The large-scale implementation of slum upgrading andimprovement programmes is one of the biggest challengesthat communities and municipalities in developing countriesface today. Such programmes aim to overcome diverse prob-lems such as poor housing conditions, limited access toimproved water and sanitation, insecure tenure, hazard risks,and high unemployment.

In this article, we describe a participatory approach thatcould improve slum monitoring processes. It involves variousactors with local knowledge and uses Geographic Informa-tion Technology (GIT). The approach reduces resourcerequirements while providing locally relevant and spatiallydetailed information. The data can be used for both planningand monitoring the effectiveness of slum intervention proj-ects. This low cost participatory approach has been tested in

Addis Ababa, the capital of Ethiopia – a large city with a highproportion of slum households.

We used rapid urban appraisal methods, supported byGIT tools to map and analyse the slums. The methods andtechniques used included focus group discussions, fieldobservation with community members and local experts, andvisual image interpretation using satellite images and aerialphotographs. The approach has potential for replication andup-scaling to produce a city-wide database of slums thatcould be used to monitor the effectiveness of ongoingupgrading projects.

BackgroundOne important prerequisite for improving slum conditions islocal intervention strategies that build on adequate andtimely available information that spatially locates slum areas– but which also reflects their diversity in a local context. Theuse of performance targets such as the MDGs requires aworkable monitoring mechanism so that the societiesinvolved can measure its progress.

Addis Ababa has estimated population of over 3 million,with ten sub-cities. Between 85% and almost 100% of itspopulation are slum dwellers (UN-Habitat, 2004). But thecentral government has only recently given urban develop-

by TSION LEMMA, RICHARD SLIUZAS and MONIKA KUFFER

A participatory approach tomonitoring slum conditions: an example from Ethiopia

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A participatory approach to monitoring slum conditions: an example from Ethiopia 7

ment issues any attention, as agriculture is still the dominantsource of livelihoods for most Ethiopians.

The neglect of urban issues has had severe consequencesfor the physical, social and economic development of AddisAbaba (Solomon, 2005). Recently, the national governmentand the local government of Addis Ababa have formulatedpolicies to target urban poverty reduction and slum upgrad-ing by:• providing infrastructure;• improving tenure security; • improving water supply and sanitation; • improving housing conditions; and • improving the urban environment (e.g. improving the solid

waste management).(AAWSA, 2004; HDPO, 2004; MOFED, 2002).

Main strategic decisions about slum intervention andbudget allocation are still done at the city level. The actual

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implementation and resource mobilisation is prepared on thelowest administrative level, or kebele, and is based oncommunity participation. There are 203 kebeles in the city.The sub-city level is not very involved in this process.

The importance of the kebeles is rooted in the reform ofthe administrative structure in 2003. This emphasised decen-tralisation and public participation. But the programmes onpoverty reduction and slum upgrading increase the need fordetailed information on slum areas. So information isrequired to gain a better understanding of the complexityand diversity of such areas – and to support the more strate-gic allocation of scarce resources for slum upgrading.

The local demand for information on slum areas goesbeyond the simple classifications that characterise most partsof Addis Ababa as ‘slums’. This demand reflects the viewsand needs of the inhabitants. It calls for ‘high-resolution’ aswell as qualitative information (Kumar, 1987). Because fast

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but also reliable data collection methods are needed, wefound participatory assessment to be a highly appropriatemethodology for slum surveys. This approach focuses onlocal people’s perceptions of slums and their diverse charac-teristics. We used participatory approaches that incorporatethe use of Geographic Information Technologies (GIT) such ashigh resolution QuickBird satellite imagery and aerial photo-graphs at scale 1:10,000.1

This approach could be an alternative to overcome thelack of conventionally available data for local upgrading strate-gies (Sliuzas, 2004). The approach offers several advantagesover conventional, more technocratic approaches such as:• its timeliness and low cost;• the increased ownership of the data collection process and

the revealed problems; • the local learning that results from participation; and • a greater ease of embedding locally generated information

in institutions such as city and sub-city authorities andcommunity-based organisations (CBOs) (Turkstra andRaithelhuber, 2004).

In this article, we describe the work carried out in AddisKetema sub-city and Kebele 14.2 This kebele was selected todemonstrate the different levels of information that can beobtained from local knowledge in combination with satelliteimagery and aerial photos.

Addis Ketema is part of the old city centre and is domi-nated by a mixture of commercial activities and deteriorat-ing residential areas. It includes the largest market place ofthe nation, Merkato, and the intercity bus terminal. Kebele14 is one of the most densely populated areas within AddisKetema, with approximately 700 inhabitants per hectare.

MethodologyAcquiring comprehensive slum information for slum improve-ment in cities like Addis Ababa is entwined with issues ofextreme resource constraints, data limitations and the hetero-geneous characteristics of the city. We employed rapidappraisal techniques, integrating local knowledge with GITusing a participatory approach. This approach is preferableas it is cheap to build, easy to use, robust and flexible in itsapplication (Sliuzas, 2004). Through focus group discussions,direct field observation, and visual image interpretationcomplemented by secondary data we were able to generateboth spatial and non-spatial information on slums in the formof thematic layers in a GIS environment.

Using focus groupsFocus group discussions were held at city, sub-city and kebelelevel with different types of participants. This enabled us toobserve the differences in the competencies and knowledgebetween professionals, technicians and residents. We heldten focus group discussions involving three to eight partici-pants each. Similar sets of open-ended questions (checklists)were developed and used (see Box 1).

It was essential to form a shared conceptual base foridentification, characterisation and analysis of slums. Soduring the focus group discussions, slums were defined inthe local context. Indicators considered relevant by eachgroup were developed (e.g. access route condition, accessto improved water and sanitation). The indicators thenprovided a basis for conducting slum identification. In addi-tion, existing interventions in slums were discussed and

• How is ‘slum’ defined in the local context of Addis Ababa?a) Are there official definitions related to slums that are used for policypurposes or other official use?b) Is there a local language term used (for example, like cherekabet forinformal settlements)?c) If not, how would you define slum in a local context?• What characteristics do slum areas have?• What are the most common characteristics (list and prioritiseaccordingly)? Why?

Box 1: An example of questions to explore how peopleunderstand the term ‘slum’

Photo 2: Participants of a city-level professional focus groupmarking slum areas on asatellite image of Addis Ababa

1 For more information about very high resolution satellite imagery visit one ofthe following websites: www.terraserver.com/; www.digitalglobe.com (QuickBird)or www.spaceimaging.com (Ikonos). 2 The full study covered three sub-cities and four kebeles and is reported inLemma, 2005.

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related problems were identified (e.g. affordability ofimproved water).

Organisations and administrative offices involved in thephysical development of slums were selected at all adminis-trative levels. The local authority focus group participantswere experts involved in municipal works such as urban plan-ning, urban management, land administration, housingdevelopment and water supply. Six experts in urban planningand urban infrastructure from Addis Ketema sub-city partic-ipated in the sub-city level focus group discussion. At kebelelevel, three representatives from the Kebele DevelopmentCommittee were identified and invited to participate, as theywere all key actors in slum upgrading projects. This commit-tee has an important role in raising local funds, mobilisingand organising the community, prioritising needs, and raisingfunds via NGOs.

Each focus group was asked to discuss and agree on aset of variables that could be used to characterise slums intheir area. They were then asked to identify and delineateslum areas within the city, the sub-city or the kebele based onthe agreed characteristics. Each delineation was done on apiece of tracing paper overlaying a QuickBird satellite image,scale 1:15000, that included the sub-city boundary. Thisprocess involving considerable discussion and exchange oflocal knowledge by all group members (see Photo 2).

An important characteristic of Addis Ababa is that thereis a high degree of spatial mixing between slum and non-slum areas. This often makes it impossible to separate slumand non-slum areas at the working scale used for this study.

So groups were asked to classify the identified areas contain-ing slums into one of three classes: • Low (5-20% slum houses) • Medium (21-74% slum houses)• High (75-95% slum houses)

The delineation of slum areas by lower level focus groups(i.e. sub-city and kebele) were more detailed than thatobtained from city level groups (see Figure 1). The lower levelgroups were better able to discuss the prioritisation of specificareas, according to the severity of problems, with selectedvariables.

Direct field observationWe also used direct field observation for primary data collec-tion within the city. This approach was used for three differ-ent purposes:• To better understand and describe the diversity of physical

conditions and characteristics of the slum areas and in orderto validate delineation of the slum areas done by the experts.

• To identify areas of inadequate water supply with the helpof field technicians from the water and sewerage author-ity. The existing water supply map does not indicate thelayout of the water pipe to individual housing units. It wasnot possible to get the spatial information from the second-ary data. So field technicians were chosen for their richerknowledge of areas with limited piped water supply. As thetechnicians were sometimes unable to indicate problemareas on the image or maps, field observation was chosenas a means of data capture for this variable.

Figure 1: Some sketch map outputs from focus groups for slum identification at sub-city and city level

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• To identify and describe specific problem areas with thehelp of the kebele neighbourhood development commit-tee. It was easier for the committee members to indicatespecific problem areas through direct field observationrather than relying solely on the QuickBird image.

Visual image interpretationImage interpretation was very effective for capturing datathat could not be easily captured using field observations orin focus groups. The focus group discussions revealed keyvisual image interpretation elements for slum identificationand delineation (i.e. irregular street and building pattern and

small, densely distributed houses). As Addis Ababa has beengrowing spontaneously without any significant guiding planor standards for many years, irregular layout and high densityare two key manifestations of poor living conditions in thebuilt environment of the city.

Based on two elements of image interpretation patternand size, we identified groups of buildings with an irregularlayout and lacking open space (see Figure 2). We also usedthe QuickBird image and aerial photographs when clarifica-tion was needed. This process of data capture has helped infilling the data gaps that remained after the focus groups andfield observation (e.g. due to poor accessibility).

Public water tapin Kebele 14

Typical street after firstlevel improvement

Figure 2: Examples of slums delineated by T. Lemma on a QuickBird image of 2002:

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tion strategies and programmes in the local context. The focus groups identified and prioritised poor sanita-

tion, poor housing conditions and poor access routes as themain physical manifestations of slums in Addis Ababa. Watersupply was not included into the first rank of slum indicatorsbecause of the widespread nature of this problem, i.e. watersupply problems are also common in newly developedmiddle class residential areas, which the focus groupmembers do not consider to be slums.

We can’t show all results in this article. But we will givean example of the data collected for two variables in AddisKetema: poor housing conditions and poor access roads (seefigure 4). Although substantial data on slums, policies, andintervention programmes is captured at city level, theseexamples show that the diversity of local living conditions islost at higher spatial (administrative) levels. Even in acentrally located and relatively well established central areasuch as Addis Ketema, there are substantial differencesbetween the data derived on housing and access conditionsfrom the different levels. Clearly the level of detail increasesfrom city to sub-city to kebele level. But we also observedinconsistencies between the different levels. Areas consid-ered by one level to have serious problems with poorhousing or access may be excluded from higher or lowerlevel representations.

There are several disconcerting features of such differ-ences that can be illustrated by comparing the city and sub-city levels. The sub-city level is mainly concerned with theimplementation of various plans formulated at city level.However, these results reveal that even there, the two levelsmay not have a common view of the problems and theirspatial extent. This could lead to miscommunication andexcessive or inadequate resource allocations for plan imple-mentation. Our focus groups revealed that with the excep-tion of the higher management staff, sub-city staff tendedto be less well-informed concerning areas of the existingpolicy and strategy, as well as the future plans of the govern-ment in relation to slums.

At kebele level, the residents of the area have beendirectly involved through the neighbourhood developmentcommittee, so more detailed data could be captured.However, the neighbourhood development committee iseven less knowledgeable than sub-city staff on the existingand future government plans and strategies for the specificarea. There are apparently significant weaknesses in the flowof information and sharing of knowledge between adminis-trative levels and these weaknesses are apparent in bothdirections (i.e. top-down and bottom-up).

Integrating multi-source slum data The identified set of slum variables was established and delin-eated through a combination of the three methods. Focusgroups, image interpretation and field observation were allsupported by available secondary data. In producing the finaldata products, the initial classification by the focus groupswas adopted as the major source because of the richness anddetail that was available from the various groups. Anoverview of this process is shown in Figure 3. The finalproduct was a set of delineations of problem (slum) areas,with deficiencies related to housing condition, sanitation,access routes, tenure security and water supply.

Discussion of resultsThe focus group approach that we used provided an oppor-tunity for direct learning by the study team. It allowed foran adaptive methodological approach. Minor deficienciesin the pre-set discussion guide were revealed and we madesome adjustments during a group meeting while maintain-ing the main framework of each focus group. We thenacquired information about the local views of slum defini-tion, slum characteristics, and also existing slum interven-

Figure 3: Overview of the data collection and integrationprocess

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Figure 4: Comparison of problem area delineation (housing and access route conditions) at three administrative levels

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Clearly, more detailed data could be captured at loweradministrative and community levels, enabling a deeperunderstanding of the multifaceted nature of specific slumareas. Such detailed information on slums is essential forlocal level decision-making and to form local policiesthrough which sectoral or geographically targeted inter-ventions can be planned and implemented. Each level has itsown role in slum improvement. So the inclusion of all admin-istrative levels and the community in data acquisition andmonitoring processes should help develop a more relevantand accurate information system on slums in the city. Themethodology we used seems to offer some potential forfurther development and implementation in Addis Ababa. Ithas at least pointed to weaknesses in information handlingand sharing that could potentially undermine the develop-ment of effective strategies toward the elimination of slumsin accordance with the MDG campaign.

ConclusionsWe acquired a richer understanding of slums and their char-acteristics through the combination of focus group discus-sion, field observation and image interpretation. Thisexperience has shown that it could be an effective, econom-ical and reliable method that is suitable for replication andadoption throughout the city.

In particular, focus group discussions have the potentialfor gathering in-depth knowledge and insights in a rapid andeconomical way. These methods allow different actors –including the community – to participate and collaborate. Itcan create opportunities for data sharing and improvedmutual understanding that is needed for collaborative slumupgrading interventions.

The spatially heterogeneous character of the city oftenlimited the ability of participants to distinguish between ‘rela-tively poor’ and ‘relatively rich’ areas by visual image interpre-

Figure 5: Aerial photo of Kebele 14

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CONTACT DETAILSTsion LemmaAddis Ababa City Government, City Manager’sOffice, City Planning Preparation andInspection Department, P.O. Box 10653 AA,Ethiopia. Email: tsionlm@yahoo.com

Richard Sliuzas and Monika KufferInternational Institute for Geo-InformationScience and Earth Observation (ITC),Department of Urban and Regional Planningand Geo-information Management, PO Box 6,7500 AA Enschede, The Netherlands. Tel: +3153 487444; Fax: +31 53 4874575; Email:sliuzas@itc.nl, kuffer@itc.nl

REFERENCES AAWSA (2004). Sectoral DevelopmentProgramme. Addis Ababa Water and SewageAuthority: Addis Ababa.Abbott, J. (2003). ‘The use of GIS in informalsettlement upgrading: its role and impact onthe community and on local government.’Habitat International 27(4)HDPO (2004). Integrated housingdevelopment programme. HousingDevelopment Project Office: Addis Ababa.Kumar, K. (1987). ‘Rapid, low-cost datacollection methods for AID.’ Program Designand Evaluation Methodology Report 10. AID:Washington DCLemma, T. (2005) ‘A comparison ofmethodologies for monitoring slum conditionswithin millennium development goals: the casestudy of Addis Ababa, Ethiopia.’ UPLA MScthesis. , ITC: Enschede. Available online:www.itc.nl/library/Papers_2005/msc/upla/lemma.pdfMOFED (2002). Sustainable development andpoverty reduction programme. Ministry of

Finance and Economic Development: AddisAbabaSliuzas, R. V. (2004). ‘Managing InformalSettlements, a study using geo-information inDar es Salaam, Tanzania.’ ITC Publication Series 112. Available online:www.itc.nl/library/Papers_2004/phd/sliuzas.pdfSolomon, K. (2005). ‘Housing Development asInstrument to Alleviate Urban Poverty (TheCase of Addis Ababa).’ Paper presented at theInternational Conference for Integrating UrbanKnowledge & Practice, May 29 – June 3, 2005,Gothenburg, Sweden.Turkstra, J., & Raithelhuber, M. (2004). ‘Urbanslum monitoring.’ Available online:http://gis.esri.com/library/userconf/proc04/docs/pap1667.pdfUNDP (2003). ‘Millennium DevelopmentGoals: A compact among nations to endhuman poverty.’ Human Development Report2003: New York.UN-Habitat (2004). Internal report on urbaninequity in Addis Ababa (unpublished).

tation. This was especially problematic for the technicians fromthe water and sewerage authority. There are many small areaswithout access to these services scattered throughout the city.So it was important to crosscheck the information derived fromthe focus group discussions and the field observations.

The use of the satellite images with the focus groups wasnot entirely successful. This was due to difficulties that someparticipants – particularly the community representatives atthe kebele level and the utility company technicians – had ininterpreting the images. As such imagery has been very usefulin other studies, it is quite likely that these difficulties couldbe overcome with increased exposure to such images, partic-ularly if image scale is increased to make individual housesmore easily visible and recognisable.

Integrating methods and techniques had advantages overusing any single method. The limitation in one method canbe amended by the strength of the other. In particular theinteractive participatory mapping done by experts – and thecommunity representatives’ spatial knowledge translated into

maps – gave a rich information base for this analysis. It hasthe potential to create a basis for learning about the opin-ions, intents and needs of various technical and residentgroups. This can be a first step toward a better understand-ing the different perceptions of the slum characteristics invarious locations.

The problem areas identified at the different administra-tive levels were not entirely contradictory. But the richness ofdetail obtained at kebele level cannot be matched at higherlevels. The information gained at community level is of greatvalue, especially if scarce resources for slum improvement areto be effectively targeted. The exchange of informationgained from the different levels will be essential in generat-ing a shared vision and working in a coordinated mannertoward common goals. If community participation is to beused in future slum upgrading programmes in Addis Ababaand elsewhere, the further development of such participa-tory approaches to slum monitoring should be encouragedand adopted.