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Guest blog: How technology is helping planners to improve slums

15 January 2016 Author: Nathaniel Williams

So, how do you plan for a rapidly growing informal settlement when access is difficult, safety is a concern and traditional data sources are out of date?

With Habitat III on the horizon, and international commitment for countries to achieve the United Nation’s new global Sustainable Development Goals (SDGs), how would you as a planner be able to implement these when facing such a daunting challenge?


This dilemma is faced by many planners in developing countries. Rapid urbanisation is one of the world’s biggest challenges with increasing pressure on housing and services. In developing countries this has resulted in ever expanding informal settlements. 

In the past, these communities were either ignored or re-located and shelters demolished.  Contemporary thinking now views informal settlements as part of society’s solution in quickly addressing housing shortages and affordability. Provided they are, for example, located on hazard-free areas and land ownership is not an issue, new strategies and planning policies advocate for upgrades.  But however well-intentioned, planning strategies are not always effective.

Town planners generally try to plan for increased populations by looking at the latest census data and undertaking traditional site surveys.  The census helps determine the growth and number of people living in an area.  Site surveys give an immediate snapshot on living conditions, number of shelters and people, community facilities available, employment opportunities, basic infrastructure and size of the settlements.  This information then helps determine for example the number of new houses, community facilities, infrastructure or upgrades required.   

However, there are drawbacks. Censuses are only conducted every 10 years and informal settlements grow rapidly in between surveys. Many inhabitants won’t participate in census recordings – due to safety concerns, unlawful trading activities or fear of deportation if they are illegal residents. Site surveys do not also give an accurate picture - access to properties can be difficult and in many cases there are safety concerns as crime is often higher in these areas.

How to obtain accurate data in informal settlements piqued the interest of Nathaniel Williams, a Geographic Information System (GIS) Specialist who has explored population analysis methods using Feature Extraction Analysis (FEA) software. Inspired by discussions with South African authorities he decided to test a new GIS software technique on Diepsloot.  

Diepsloot  is a densely populated settlement located between the cities of Johannesburg and Pretoria.  It contains both formal and informal houses, is home to many illegal immigrants and suffers from serious crime.  About 200,000 people live in low cost government housing and 20 000 reside in illegal backyard shelters measuring 2mx6m. Planners have struggled to keep abreast of how many people need formal housing and basic services as residents are wary of allowing authorities to enter properties.  Census data is therefore highly inaccurate. In summary, a perfect case study.

After consulting authorities and gaining permission from community leaders, Nathaniel used the FEA software to identify roofs, roads and trees on high quality aerial photographs. In order to the software’s accuracy, he also conducted a sample field survey comprising door-to-door interviews with the consent from community leaders. 

  Diepsloot Photo SS

(Picture: Door-to-door interviews in Diepsloot – author photograph)

Identifying roof coverage was seen as the best way of calculating the total population and household numbers as it was known that the size of the informal shelters was 6m² per person. The results revealed that the GIS software based method achieved an overall accuracy of 80.5 % when compared to manually outlining roofs by hand. The computer-based method was far quicker and cost effective and allowed calculation of difficult to reach houses. The results of the Diepsloot study provided the City of Johannesburg municipality with a more accurate picture which will help guide future planning policy.


(Pictures: screenshots of Diepsloot - actual roof coverage done manually (left), using Feature Extraction Survey software (middle) and the difference (right)  – author images)

This FEA method has also been used in Kenya, Tanzania and Brazil. It quickly indicates how an informal settlement is growing and impacting on services and the environment. It can also be used to measure consumption patterns and provide a basic risk analysis from existing hazards.

There are limitations such as having access to GIS and the FEA tool and when the aerial photographs are taken and these need to be taken into account.  The results must be considered as part of the answer in good policy-making . We can’t just rely on computers - planners plan for people and act on behalf of the public good. But, if we consult the community and use this in combination with traditional planning methods, computer-based techniques can help us create, better plans and policies for healthier, more sustainable informal settlements that can adapt to climate change and in turn help planners to implement the new Sustainable Development Goals.

The full results of this new Feature Extraction Analysis technique are published in the Applied Spatial Analysis and Policy journal.  

Further information can be sourced from Nathaniel Williams at


Nathaniel Williams

Nathaniel Williams

Nathaniel Williams (MSc) is a GIS and International Development Specialist with extensive experience in Sub-Saharan Africa working on multi-donor programs. Primarily at project management level, sectors have ranged from agriculture, livelihoods, health and private sector development within Uganda, Zimbabwe, Sierra Leone, Somaliland and South Africa. Nathaniel currently works as a Technical Director at the aBi Trust based in Uganda.