**6. Discussion**

Informal settlements are a very dynamic phenomenon in space and time and the number of people living in these areas is growing worldwide. The reasons for this are many-sided

MapKibera Project (2008) 0.0951 3.04 4,343 IRIN (2006) 0.2000 6.40 9,131 AHI US (2005) 0.3000 9.60 13,697 Sartori et al. 1 (2002) 0.3300 10.56 15,067 Sartori et al. 2 (2002) 0.3900 12.48 17,806

Table 6. Density of people living in Raila village according to different sources and total residential area obtained from object-based classification of GeoEye 2009-07-25 image.

Fig. 14. Density of people according to different sources per typical size of houses in Raila

In Table 6 we presented also the density on 32 m2 unit since this size of house was measured to be a most typical and frequent (medium range size) housing unit in Raila village. It was also observed that size of small buildings is approximately 16 m2, while large buildings

When perfoming such population estimation it is assumed that all of the build-up area is used for dwelling, which is not allways true as houses may be also used for other activities. For the possible calibration of the above population densities field survey sampling would be required. Nevertheless, Table 6 clearly outlines how population estimation based on critera of simple density per area based modelling can propose up to 4-times higher

Informal settlements are a very dynamic phenomenon in space and time and the number of people living in these areas is growing worldwide. The reasons for this are many-sided

reach on average 65 m2. Fig. 14 summarise in addition the above relationship.

**Density [people/32m2]**  **Estimated population of Raila** 

**Source Density** 

village.

(different) population estimation.

**6. Discussion** 

**[people/m2]** 

and were not under detailed examination of this study. Informal settlements represent a particular housing and living conditions which is from a humanitarian point of view in most cases below acceptable standards (UN-HABITAT, 2004; MKP, 2011; Sartory et al. 2002). Due to informal character and low governmental management services in the past, reliable and accurate data about informal settlements and their population is rarely available. On the other side there is a strong need to transform informal into formal settlements and to gain more control about the actual urbanisation progress. Thus, obtaining spatially and temporally accurate information is a first step to establish proper actions in terms of local or regional planning. For these tasks, conventional data sources, such as maps, statistics or even GIS data are usually obsolete, not available, not as accurate as needed or do not hold the information needed (MKP, 2011; Sartory et al. 2002). The case study presented demonstrates how informal settlements can be approached from VHR satellite image data. Using an object based approach of image analysis detailed land cover/use within informal settlements can be obtained to facilitate GIS-based management tasks and population modelling. The application of automatic, even if simple pixel-based, change detection proved to support real-time observation of informal settlement areas whenever appropriate VHR satellite data are available with relatively low processing costs.

Merits of object-based image analysis in dense informal settlements analysis with VHR remote sensing data have been confirmed in several studies (section 2). However some drawbacks still resist. In case of residential land cover/use map derivation main unsolved difficulty is automatic detection and separation of individual houses. Although small differences in heights of rooftops create visually well distinguished boundaries of objects, the heterogeneity of rooftop material and its small scale changeability often overrule the value of neighbourhood houses boundaries relationship. Current limit of object based analysis is also that still requires substantial post-classification routines and check-over that can be done mainly manually through visual control. What characterise this procedure as time demanding whenever geometrically and semantically correct information is aimed.

Change detection applied revealed great potential for long-term monitoring and informal settlements urbanisation growth analysis. Hence more research is needed to provide sufficient detection rate of spectrally lower magnitude changes that are typical for informal settlements specifics and its reflectance intensity representation on satellite imagery. Due to rooftop material used bright (metal) materials are unproblematic to distinguish from soils, however dark rooftop materials (blue, brown colour) are spectrally closer to bare, unpaved (brown) or vegetated (green) soils. Here object based approaches would prove better option as sub-object attributes could be explored and used.

Valuable population estimation can be made with a relatively low cost if residential area if accurately estimated from high-resolution images, although some considerations exist. Area based population estimation model can be used for the informal settlements in other images of similar resolution knowing the number of people living per surface unit. Zhang (2002) exposed some problems of selection of the scales of remote sensing imagery, reduction of influence of plant cover on remote sensing data, stability of the correlation between population and remote sensing indicator variables and correction of building count. In this research we met all mentioned problems in order to accurately estimate

Object-Based Image Analysis of VHR Satellite Imagery for

satellite images of the area.

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population out of VHR satellite data. Nevertheless, if a clear understanding of mentioned issues is considered, reliable population model of population estimation by remote sensing data can be created. Thus, the application of satellite data information (such as accurate information on land use extent and other measures of surface or environmental characteristics) along with socio-economic data may well facilitate complex modelling to estimate population trends.

In terms of remote sensing technology contribution it is necessary to continue to develop new techniques for complex densely packed urban environments such as informal settlements. Emphasis on spectral properties should be considered but also emphasis on the characteristics of the shape, texture, context, and relationship with neighbouring pixels (and/or objects) information needs to be enhanced; as well as integration of the knowledge on corresponding socio-economic drivers should not be neglected.
