**7. Conclusion**

Effective methods of monitoring informal settlements are required to generate appropriate data fast enough to assist to local policies and their controlling actions. Remote sensing data are especially powerful in that respect since, apart they are up‐to date, they assist to link the geographic location with the accurate socio-economic data.

The results of change detection confirmed that VHR imagery is very promising for immediate monitoring of dense informal residences in the areas where much information is lacking. The results of object-based (contextual) classification of the land use in informal settlements of Kibera were highly accurate, especially if taking into consideration that informal settlements are difficult to be interpreted with automatic or semi-automatic routines. On the other side, the results indicate the problem of the ratio between spectral and spatial heterogeneity of objects in slum-like areas when viewed only from the above (satellite) perspective. Overall, the use of the object-based image analysis holds great promise for dense urban environments and was proved useful for studies of urban change structure and corresponding population estimation.

Satellite derived information can greatly complement the information that is traditionally collected by field observations (UNHCR, 2000). Quantitative information that can be derived from it should not be underestimated. The production of maps with geometrical shapes of settlements can contribute to recover the management of informal settlements, especially when interfaced with database that has information collected on the field. Although several challenges have not been yet solved adequately, e.g. delimitation of individual objects in slum-like areas, we can notice that applications are being developed. Thus (automatic) analysis of objects enables tremendous opportunities for population estimation in informal settlements.
