Earth Observation-Based Dwelling Detection Approaches in a Highly Complex Refugee Camp Environment - A Comparative Study

For effective management of refugee camps or camps for internally displaced persons (IDPs) relief organizations need up-to-date information on the camp situation, that can be provided by Earth observation (EO). In this study, different approaches were tested using the example of a highly complex camp site in Somalia.Si loogu sameeyo maareen rasmi ah xereyinka qaxootiga iyo barakacayaasha gudaha dalka, ururada samafalku waxay u baahanyihiin xog ama warar cusub oo ku saabsan xaaladaha xerooyinka. Haddaba daraasaadkan wuxuu si gaar ah u baarayaa xero ku taalla Soomaaliya.Per una gestione efficace dei campi profughi o campi per sfollati interni (IDPs), le organizzazioni umanitarie hanno bisogno di informazioni aggiornate sulla situazione del campo, che possono essere fornite con osservazioni della Terra dallo spazio (EO). In questo studio, diversi approcci sono stati testati partendo dal caso di un campo molto complesso in Somalia

Earth Observation-Based Dwelling Detection Approaches in a Highly Complex Refugee Camp Environment — A Comparative Study

For effective management of refugee camps or camps for internally displaced persons (IDPs) relief organizations need up-to-date information on the camp situation. In cases where detailed field assessments are not available, Earth observation (EO) data can provide important information to get a better overview about the general situation on the ground. In this study, different approaches for dwelling detection were tested using the example of a highly complex camp site in Somalia. On the basis of GeoEye-1 imagery, semi-automatic object-based and manual image analysis approaches were applied, compared and evaluated regarding their analysis results (absolute numbers, population estimation, spatial pattern), statistical correlations and production time. Although even the results of the visual image interpretation vary considerably between the interpreters, there is a similar pattern resulting from all methods, which shows same tendencies for dense and sparse populated areas. The statistical analyses revealed that all approaches have problems in the more complex areas, whereas there is a higher variance in manual interpretations with increasing complexity. The application of advanced rule sets in an object-based environment allowed a more consistent feature extraction in the area under investigation that can be obtained at a fraction of the time compared to visual image interpretation if large areas have to be observed