Ouagadougou land use map at street block level (Q11801)

This datatset contains a land use classification of Ouagadougou (Burkina Faso) at the street block level. It was created following the methodology presented in[1]. Description of the files: Ouagadougou_landuse.gpkg : GeoPackage with two layers: (1) layer of the street blocks extracted from OpenStreetMap using [2] with classification results in the attribute table. (2) layer with manual correction made by GEORGANOS Stefanos (sgeorganos@ulb.ac.be). 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 classBARE 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 betweenFIRST_PROB andSEC_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 Legend classes label: VEG :Vegetation BARE:Bare soils ACS :Non-residential built-up (administrative, commercial, services, etc.) PLAN :Planned residential built-up 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 References: [1] 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 [2]Grippa, Tais. 2018. Osm Street Blocks Extraction. Zenodo. https://doi.org/10.5281/zenodo.1290637. Funding: This dataset wasproduced in the frame of two research project : MAUPP (http://maupp.ulb.ac.be)and REACT (http://react.ulb.be), funded by theBelgian Federal Science Policy Office (BELSPO).