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Ouagadougou very-high resolution land cover map

Tais Grippa; Stefanos Georganos


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{
  "description": "<p>This land cover map of Ouagadougou (Burkina Faso) was created from a WorldView3 very-high resolution imagery with a spatial resolution of 0.5 meter. The methodology followed a open-source semi-automated framework [1] that rely on <a href=\"https://grass.osgeo.org/\">GRASS GIS</a>&nbsp;using a local unsupervised optimization approach for the segmentation part&nbsp;[2-3].</p>\n\n<p>Description of the files:</p>\n\n<ul>\n\t<li>&quot;Landcover.zip&quot; :&nbsp;The direct output from the supervised classification using the Random Forest classifier.</li>\n\t<li>&quot;Landcover_Postclassif_Level5_Splitbuildings.zip&quot; : Post-processed version of the previous map (&quot;Landcover&quot;), with reduced misclassifications from the original classification (rule-based used to reclassify&nbsp;the errors, with a focus on built-up classes).</li>\n\t<li>&quot;Landcover_Postclassif_Level5_modalfilter3.zip&quot; : Smoothed version of the previous product (modal filter with window 3x3 applied on the &quot;Landcover_Postclassif_Level5_Splitbuildings&quot;).&nbsp;</li>\n\t<li>&quot;Landcover_Postclassif_Level6_Shadowsback.zip&quot; : Corresponds to the &quot;level5_Splitbuildings&quot; with shadows coming&nbsp;from the original classification.</li>\n\t<li>&quot;Ouaga_legend_colors.txt&quot; : Text file providing the&nbsp;correspondance between the value of the pixels and the legend labels and a proposition of color to be used.</li>\n</ul>\n\n<p>&nbsp;</p>\n\n<p>References:</p>\n\n<p>[1]&nbsp;Grippa, Ta&iuml;s, Moritz Lennert, Benjamin Beaumont, Sabine Vanhuysse, Nathalie Stephenne, and El&eacute;onore Wolff. 2017. &ldquo;An Open-Source Semi-Automated Processing Chain for Urban Object-Based Classification.&rdquo; <em>Remote Sensing</em> 9 (4): 358. <a href=\"https://doi.org/10.3390/rs9040358\">https://doi.org/10.3390/rs9040358</a>.</p>\n\n<p>[2]&nbsp;Grippa, Tais, Stefanos Georganos, Sabine G. Vanhuysse, Moritz Lennert, and El&eacute;onore Wolff. 2017. &ldquo;A Local Segmentation Parameter Optimization Approach for Mapping Heterogeneous Urban Environments Using VHR Imagery.&rdquo; In <em>Proceedings Volume 10431, Remote Sensing Technologies and Applications in Urban Environments II.</em>, edited by Wieke Heldens, Nektarios Chrysoulakis, Thilo Erbertseder, and Ying Zhang, 20. SPIE. <a href=\"https://doi.org/10.1117/12.2278422\">https://doi.org/10.1117/12.2278422</a>.</p>\n\n<p>[3]&nbsp;Georganos, Stefanos, Ta&iuml;s Grippa, Moritz Lennert, Sabine Vanhuysse, and Eleonore Wolff. 2017. &ldquo;SPUSPO: Spatially Partitioned Unsupervised Segmentation Parameter Optimization for Efficiently Segmenting Large Heterogeneous Areas.&rdquo; In <em>Proceedings of the 2017 Conference on Big Data from Space (BiDS&rsquo;17)</em>.</p>\n\n<p>&nbsp;</p>\n\n<p>Founding:&nbsp;</p>\n\n<p>This dataset was&nbsp;produced in the frame of two research project : MAUPP (<a href=\"http://maupp.ulb.ac.be\">http://maupp.ulb.ac.be</a>)&nbsp;and REACT (<a href=\"http://react.ulb.be\">http://react.ulb.be</a>), funded by the&nbsp;Belgian Federal Science Policy Office (<a href=\"http://eo.belspo.be/About/Stereo3.aspx\">BELSPO</a>).</p>", 
  "license": "https://opensource.org/licenses/MIT", 
  "creator": [
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      "@id": "https://orcid.org/0000-0002-9837-1832", 
      "@type": "Person", 
      "name": "Tais Grippa"
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    {
      "@id": "https://orcid.org/0000-0002-0001-2058", 
      "@type": "Person", 
      "name": "Stefanos Georganos"
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  "url": "https://zenodo.org/record/1290654", 
  "datePublished": "2018-06-15", 
  "keywords": [
    "Ouagadougou", 
    "Land cover", 
    "Map", 
    "Very-high resolution"
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  "version": "V1.0", 
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  "identifier": "https://doi.org/10.5281/zenodo.1290654", 
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  "@type": "Dataset", 
  "name": "Ouagadougou very-high resolution land cover map"
}
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