Hugo Perilleux Sanchez;
Nicole Van Lipzig;
Daniel C Casey
This datatset contains a land use classification of Ouagadougou (Burkina Faso) at the street block level. It was created following the methodology presented in .
Description of the files:
"Ouagadougou_landuse.gpkg" : GeoPackage with two layers: (1) layer of the street blocks extracted from OpenStreetMap using  with classification results in the attribute table. (2) layer with manual correction made by GEORGANOS Stefanos (firstname.lastname@example.org).
"Ouagadougou_landuse_style_QGIS.zip" : Files for style for rendering in QGIS.
Attribute table content:
"CAT", "GID" : ID of the street block
"PROB_ACS" : Probability to belong to class ACS
"PROB_BARE" : Probability to belong to class BARE
"PROB_PLAN" : Probability to belong to class PLAN
"PROB_UNPLA" : Probability to belong to class UNPLAN
"PROB_VEG" : Probability to belong to class VEG
"FIRST_LABE" : Class with the highest classification probability
"SEC_LABEL" : Class with the second highest classification probability
"FIRST_PROB" : Value of the highest classification probability
"SEC_PROB" : Value of the second highest classification probability
"UNCERTAIN" : Difference between "FIRST_PROB" and "SEC_PROB"
"BUILT_PERC" : Percentage of the street blocks covered by built-up (from land cover map)
"MAP_LABEL" : Final classification label with uncertainty and different density classes. Depending on the layer, the label is with or without manual corrections
"PLAN_LD" : Planned residential low density built-up
"UNPLAN" : Unplanned residential built-up
"UNPLAN_LD" : Unplanned residential low density built-up
"UNCERT" : Uncertain classification
"WET" : Wetlands
"AGRI" : Agricultural land
 Grippa, Tais, 2018, "Mapping urban land use at street block level using OpenStreetMap, remote sensing data and spatial metrics", ISPRS Int. J. Geo-Inf.2018, 7(7), 246. https://doi.org/10.3390/ijgi7070246
The production of this dataset was founded by BELSPO (Belgian Federal Science Policy Office) in the frame of the
STEREO III program, as part of the MAUPP (SR/00/304) and REACT (SR/00/337) project (http://maupp.ulb.ac.be