Metadata last updated on Oct 21, 2021

This raster dataset contains land cover classification in Brazzaville in 2005 and 2010 derived from SPOT5 imagery.

Land cover classes in the attribute table are as follows:

Class 1 - Regular Residential (small planned buildings)
Class 2- Regular Residential (small unplanned buildings)
Class 3 - Commercial/Industrial (large buildings)
Class 4 - Natural (Vegetation/Soil/non built-up

This dataset is part of a paper which illustrates how the capabilities of GIS and satellite imagery can be harnessed to explore and better understand the urban form of several large African cities (Addis Ababa, Nairobi, Kigali, Dar es Salaam, and Dakar). To allow for comparability across very diverse cities, this work looks at the above mentioned cities through the lens of several spatial indicators and relies heavily on data derived from satellite imagery. First, it focuses on understanding the distribution of population across the city, and more specifically how the variations in population density could be linked to transportation. Second, it takes a closer look at the land cover in each city using a semi-automated texture based land cover classification that identifies neighborhoods that appear more regular or irregularly planned. Lastly, for the higher resolution images, this work studies the changes in the land cover classes as one moves from the city core to the periphery. This work also explored the classification of slightly coarser resolution imagery which allowed analysis of a broader number of cities, sixteen, provided the lower cost.

When using this dataset keep in mind: Accuracy is higher in closer to the City center, and the distinction between class 1 and class 2 has not been validated, so use with caution. To learn more about the methodology please refer to https://ssrn.com/abstract=2883394

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Classification: Public
This dataset is classified as Public under the Access to Information Classification Policy. Users inside and outside the Bank can access this dataset.
License: Creative Commons Attribution 4.0
This dataset is licensed under Creative Commons Attribution 4.0
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