**2. Informal residential environments monitoring**

Although there is a strong need to obtain spatial information about informal settlements in order to increase living conditions for its residents and regarding the fact that remote sensing images offer a well suited data source, studies on informal settlements with VHR data are not frequent. Nevertheless, in Hoffman (2001), first results of detecting informal settlements from IKONOS data in Cape Town showed the principle feasibilities using object-oriented approach. The results were promising but seemed to be very dependent on the data. Later on Hoffman et al. (2006) showed that several adaptations were necessary to OBIA algorithm improvement when applying their extraction methods to the QuickBird scene. Automatic image analysis procedures for a rapid and reliable identification of refugee tents from IKONOS imagery over the Lukole refugee camp in Tanzania was made by Giada et al. (2002). Sliuzas and Kuffer (2008) analyzed the spatial heterogeneity of informal settlements using selected high resolution remote sensing based spatial indicators such as roof coverage densities and a lack of proper road network characterized by the irregular layout of settlements. Cooperation between KeyObs, UNOSAT, OCHA and Metria resulted in digitalization of VHR GeoEye satellite image of Afgooye corridor (Somalia) from 2009, where all temporary shelters were identified (UNHCR, 2010). Different methods to detect and monitor spatial behaviour of informal settlements were presented also by Lemma et al. (2005), Radnaabazar et al. (2004), Kuffer (2003), Sartori et al. (2002), Dare & Fraser (2001) and Mason et al. (1998).

#### **3. Study area description**

Kibera is a division of Nairobi area, Kenya, within Langata constituency. Located southwest of the city centre of Nairobi, Kibera encompasses an area of 2.5 km2, accounting for less than percent of Nairobi's total area while containing more than 25% of its population. It is the

Object-Based Image Analysis of VHR Satellite Imagery for

Fig. 2. View over Kibera informal settlement (Photo: Primož Kovačič).

threats, and price controls with no clear perspective or solutions.

**3.2 Map Kibera Project and Map Kibera Trust** 

through a digital geo-referenced data base (MKP, 2011).

based development.

Population Estimation in Informal Settlement Kibera-Nairobi, Kenya 411

All these reasons lead to, as one resident of Kibera put it, "survival tactics". These "survival tactics" engulf communities, the provincial administration and the government, leading them into a vicious cycle of under the table dealings, vandalism, lack of engagement,

Kibera is likely one of the most photographed, researched, and well-known slums in the world but the complete and mapped information was not shared and not easily (if at all) accessible. Before October 2009, Kibera did not even appear on any of the online maps. Map Kibera Project (MKP) was first initiated in response to the lack of available data. The initiative wanted to produce reliable data and maps showing the actual physical and sociodemographic features of the Kibera informal settlement, making them publicly available

Map Kibera Project trained 13 youth from the slum in GPS system and basic GIS techniques to map points of interest in their community: clinics, schools, water sources, toilets, street lights, hot spots, businesses and other landmarks. The youth uploaded the data themselves

The Map Kibera Trust (MKT) offers organizational support for the mapping work, as well as other youth driven programmes such as video production and other new media tools (blog, twitter, SMS platforms). The mission of the MKT is to contribute to a culture where digital story-telling, open data and geographic information lead to greater influence and representation for marginalized communities in Kenya. MKT has since grown into a platform specializing in community-driven data for informal settlements and on community

American Association for the Advancement of Science supports the operation of MKT and other NGO activities and has donated several satellite images of the area. MKT activities

to OpenStreetMap (www.openstreetmap.org), a volunteer-built map of the world.

largest informal settlement in Nairobi, and the second largest urban slum in Africa, with population number varying with the season. The settlement is divided into a number of villages, including Kianda, Soweto West, Raila, Gatwekera, Kisumu Ndogo, Lindi, Laini Saba, Siranga, Kamdi Muru, Makina, Mashimoni and Soweto East (Fig. 1).

Fig. 1. Kibera settlement is divided into three formal and 12 informal villages.

#### **3.1 General background of Kibera, Nairobi**

Kibera emerged in 1912 when the British East African army, known as the King's African Rifles, granted temporary rights to a group of 300 former soldiers from the Nubian community, who had served in the army, to settle on a small piece of land near Nairobi's city centre. Temporary structures were put in place but as the Nubian soldiers grew older and became unable to continue their military service, they began to set up more permanent residence on the land (A history of Kibera, 2011). Turbulent years after the independence combined with socioeconomic factors brought a dramatic increase in the population of Kibera's residents.

Today Kibera consists of 15 villages out of which just 3 are formal and thus connected to the city's utility grids (water, sewage, electricity, waste collection etc.), however the rest (12) are informal and "disconnected" from the rest of the city. Apart from lacking basic services and adequate infrastructure it is also affected by population growth, the illegal construction of infrastructure, and the increasing degradation of the environment. Unclear land-tenure arrangements in informal settlements discourage investments in proper infrastructure and repair; structures are often owned and rented by people, who mostly do not have any rights to the land on which the structures stand. This leads to the lack of legal security of tenure for most of the residents.

Because of this lack of the legal security of tenure and neglectfulness from the city and the government there's little initiative from the residents to improve their living conditions. That is why most of the structures in Kibera are temporary, wooden, mud houses covered with corrugated iron sheets (Fig. 2) and most of the service providers are self-organized groups or cartels which drive up the prices of service delivery – in some cases residents pay 10 times as much as those in the rest of the city.

largest informal settlement in Nairobi, and the second largest urban slum in Africa, with population number varying with the season. The settlement is divided into a number of villages, including Kianda, Soweto West, Raila, Gatwekera, Kisumu Ndogo, Lindi, Laini

Saba, Siranga, Kamdi Muru, Makina, Mashimoni and Soweto East (Fig. 1).

Fig. 1. Kibera settlement is divided into three formal and 12 informal villages.

Kibera emerged in 1912 when the British East African army, known as the King's African Rifles, granted temporary rights to a group of 300 former soldiers from the Nubian community, who had served in the army, to settle on a small piece of land near Nairobi's city centre. Temporary structures were put in place but as the Nubian soldiers grew older and became unable to continue their military service, they began to set up more permanent residence on the land (A history of Kibera, 2011). Turbulent years after the independence combined with socioeconomic factors brought a dramatic increase in the population of

Today Kibera consists of 15 villages out of which just 3 are formal and thus connected to the city's utility grids (water, sewage, electricity, waste collection etc.), however the rest (12) are informal and "disconnected" from the rest of the city. Apart from lacking basic services and adequate infrastructure it is also affected by population growth, the illegal construction of infrastructure, and the increasing degradation of the environment. Unclear land-tenure arrangements in informal settlements discourage investments in proper infrastructure and repair; structures are often owned and rented by people, who mostly do not have any rights to the land on which the structures stand. This leads to the lack of legal security of tenure for

Because of this lack of the legal security of tenure and neglectfulness from the city and the government there's little initiative from the residents to improve their living conditions. That is why most of the structures in Kibera are temporary, wooden, mud houses covered with corrugated iron sheets (Fig. 2) and most of the service providers are self-organized groups or cartels which drive up the prices of service delivery – in some cases residents pay

**3.1 General background of Kibera, Nairobi** 

10 times as much as those in the rest of the city.

Kibera's residents.

most of the residents.

Fig. 2. View over Kibera informal settlement (Photo: Primož Kovačič).

All these reasons lead to, as one resident of Kibera put it, "survival tactics". These "survival tactics" engulf communities, the provincial administration and the government, leading them into a vicious cycle of under the table dealings, vandalism, lack of engagement, threats, and price controls with no clear perspective or solutions.

### **3.2 Map Kibera Project and Map Kibera Trust**

Kibera is likely one of the most photographed, researched, and well-known slums in the world but the complete and mapped information was not shared and not easily (if at all) accessible. Before October 2009, Kibera did not even appear on any of the online maps. Map Kibera Project (MKP) was first initiated in response to the lack of available data. The initiative wanted to produce reliable data and maps showing the actual physical and sociodemographic features of the Kibera informal settlement, making them publicly available through a digital geo-referenced data base (MKP, 2011).

Map Kibera Project trained 13 youth from the slum in GPS system and basic GIS techniques to map points of interest in their community: clinics, schools, water sources, toilets, street lights, hot spots, businesses and other landmarks. The youth uploaded the data themselves to OpenStreetMap (www.openstreetmap.org), a volunteer-built map of the world.

The Map Kibera Trust (MKT) offers organizational support for the mapping work, as well as other youth driven programmes such as video production and other new media tools (blog, twitter, SMS platforms). The mission of the MKT is to contribute to a culture where digital story-telling, open data and geographic information lead to greater influence and representation for marginalized communities in Kenya. MKT has since grown into a platform specializing in community-driven data for informal settlements and on community based development.

American Association for the Advancement of Science supports the operation of MKT and other NGO activities and has donated several satellite images of the area. MKT activities

Object-Based Image Analysis of VHR Satellite Imagery for

urban area land cover/use.

assessments.

satellite imagery from three different dates.

**4.1 Data pre-processing and preparation** 

imagery obtained for Kibera study (see section 3.3).

Population Estimation in Informal Settlement Kibera-Nairobi, Kenya 413

Object based classification of the Kibera informal settlement was performed on GeoEye image since its characteristics (close to nadir viewing angle, good spatial resolution, and fine contrast) were most promising to obtain adequate details on object recognition within the informal settlement area. Rooftops are covered with different materials, ranging from new to rusty sheets, bricks and other materials, each of them having specific reflectance characteristics (spectral representation) on satellite image (Fig. 3, Fig. 6a). For population estimation study we need to differentiate well rooftops, unpaved roads and non-build land and therefore discriminate residential areas from open soils, respectively. Object based segmentation automatically delimits satellite image into homogeneous elements (segments), where close correspondence to the real (geographical) objects on the Earth's surface is expected. Usage of thus obtained image elements (segments) has a number of benefits, one of them is ability to incorporate spatial and contextual information such as size, shape, texture and topological relationships (Blaschke et al., 2004; Benz et al., 2004) in contextual classification. In the stage of classification all these segments are classified according to their attributes into most appropriate classes (representing various geographical objects under study consideration), while obtaining detailed classification of

Fig. 3. Examples of rooftops, rooftops renovations and buildings constructions on VHR

With object-based analysis on rooftops morphology attributes we expected to improve the assessment of the potential population in slum areas. Since no complete and relevant field survey (official census) was recently performed, different density parameters were tested to approach the potential population and compared to other available population

Data preprocessing is important procedure in remote sensing technology. It meets issues that have to be carefully understood and solved before any data analysis process starts. In order to be able to compare satellite images taken for the same scene at different acquisition dates they have to be co-registered and radiometrically adjusted. Recent automatic registration algorithms can accomplish the task well when similar acquisition geometry among sensor systems is provided. Global geometric transformations are mostly appropriate for positional corrections in such cases. However, this was not the case with the

Obtained images were rectified but not precisely aligned one to another. Due to agitated terrain in Kibera and lack of any digital elevation model, semi-automated rigorous

include various Kibera specific phenomena mappings (www.mappingnobigdeal.com), though the assessment of potential of VHR satellite imagery for mapping purposes presents one of the recent examinations of their use for Kibera community.

### **3.3 Available VHR satellite data**

Six VHR satellite images were available for our research (Table 1): one GeoEye image and five QuickBird images. Satellite images were partly (pre)processed. This means images were roughly georeferenced and corrected for sensor radiometry, also pan-sharpened, and provided as a stack of three visible bands only.


Table 1. List of available satellite images and their main characteristics.

Besides different inherent spatial resolution the main differences among GeoEye and QuickBird images were sensor viewing angles, causing higher objects roof prints and shadows to have different positions among images. As Kibera informal settlement lies in a hilly terrain, the positional accuracy fit of geographical entities among images was not reached because much of distortion comes from the terrain as well. For the study no digital elevation model was available, thus ortorectification was not possible. However, GPS field walks tracks were available for the main roads and path-network in the area.
