Classifying urban poor with satellite imagery

German Aerospace Center is using Very High Resolution (VHR) satellite imagery combined with auxiliary surveys to develop a base model classification system for the shape and structure of urban poor areas around the world

Classifying urban poor  with satellite imagery
Classifying urban poor with satellite imagery

Classifying urban poor areas with satellite imagery

Hannes Taubenböck and his team at DLR (German Aerospace Center) are using Very High Resolution (VHR) satellite imagery, supplied by European Space Imaging, combined with auxiliary surveys to develop a base model classification system for the shape and structure of urban poor areas around the world.

Slum, favela, tenement… whatever you call it, nearly every country in the world has some form of urban poor areas.  Taubenböck, Kraff and Wurm identify these locations as “Arrival Cities”, defined as a place offering relatively affordable housing serving as an access to the city, its society and its functions (a concept based on Doug Saunders’ Book “Arrival Cities”). These urban poor areas are often perceived to be densely populated clusters of dilapidated and make-shift structures.

This perception, however, fails to accurately define the morphology of these “Arrival Cities” in a meaningful way for researchers and urban planners. There are information gaps regarding these blighted neighborhoods across the globe, and without proper classification systems, policymakers cannot have the full view to make informed decisions regarding their local poor urban areas. Through the use of WorldView VHR optical satellite imagery, Arrival Cities can be modeled, measured and categorized for a better understanding by researchers.

Data Gaps

Estimates from the UN-Habitat state that nearly 1 billion people live in slums across the world and that informal structures contribute significantly to global housing construction.  Despite the statistics, these areas are often the most neglected in any city.  There are very few consistent empirical methods for researching and documenting urban poverty.

Furthermore, huge gaps in the spatial identification of these Arrival Cities still exist in many parts of the world. In a sense, Arrival Cities are missing from the maps, and because there are no agreed upon parameters for studying these areas using remote sensing, the spatial data that does exist is inconsistent and incomparable across data sets.