Global Built-up Reference Layer (BUREF 2010)

The developed approach outputs a global raster layer representing both the spatial distribution and density of built-up areas, for the year 2010. The information about the presence of built-up is expressed as the percentage of built-up area respect to the total surface of the cell. Values are expressed in the range [0 to 100]. The layer is made available as a grid having a spatial resolution of 30-arc seconds (approximately 1 km at the equator), in the WGS84 coordinate system. Being available as a quantitative, continuous raster dataset significantly increases its value by facilitating integration with other spatial datasets for analysis or modeling The method uses machine learning techniques to understand the best population thresholds translating population densities to built-up densities. In the proposed methodology the MODIS Urban Land Cover (ULC) 500 m (C5) made by satellite data of the year circa 2001-2002 is used as training set for classification of the LandScan 2010 Global Population Database (LS). Similar techniques are described in Pesaresi et al. (2013) and Gueguen (2014) for the purpose of finding best rescaling parameters translating remote sensing image-derived features to a high-level-abstraction semantic as “built-up areas”.