Data · dataset · 2024
Land use land cover very high resolution map (1.5-m) for the area of Diébougou, Burkina Faso, 2018
Listed in DataSuds
This dataset is a very-high spatial resolution Land Use / Land Cover (LULC) map of the region of Diébougou, located in southwestern Burkina Faso.
Description
Its spatial resolution is 1.5 m. It was produced in 2018 and made available for a wide range of uses.
It contains 12 land cover classes: ligneous savanna, crop, grassland, marsh, riparian forest, woodland, rice, settlements, bare soil, main roads, permanent water bodies and running waters. The method used to generate the map involved a supervised object-based image classification using multisource satellite products (SPOT 7, Sentinel-2, a Digital Elevation Model), a ground-truth dataset acquired by fieldwork and photo-interpretation, and a random forest classifier.
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The classification accuracy is 84 %. In addition to the LULC georeferenced raster data, we propose the following files in this release: the raster attribute table, including definitions of the land cover classes in english and french ; a layer style (*.qml) to visualize the raster in QGIS ; the map as a .jpeg image (for visualization purposes only) ; representative pictures of the land cover classes ; the detailed methodology used to generate the data, with the resulting confusion matrix (in English and French) ; the ground-truth georeferenced dataset used for training and test in the classification ; the R script used to create the product, based exclusively on Free and Open Source software.
Links
Where it is published
- Dataverse dataset page dataverse.ird.fr/dataset.xhtml?persistentId=doi%3A10.23708%2FARSJNB ↗
landing page · from dataverse ird fr
- DOI doi.org/10.23708/arsjnb ↗
DOI / persistent id · from dataverse ird fr
Catalogue records · 1
- Dataverse API dataverse.ird.fr/api/datasets/:persistentId/?persistentId=doi%3A10.23708%2FARSJ… ↗
metadata API · from dataverse ird fr
Topics
- Stated by source
- Computer and Information Science · Earth and Environmental Sciences
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataSuds | doi:10.23708/ARSJNB | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:field:401304 | mapping · dataverse ird fr | vocabulary-mapper@1.0.0 | keywords['remote sensing'] |
| concepts[field].dataverse_subject:computer-and-information-science | source · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | /subjects |
| concepts[field].dataverse_subject:earth-and-environmental-sciences | source · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | /subjects |
| concepts[field].local:field:earth-environmental | mapping · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | /subjects |
| concepts[modality].local:modality:image | enrichment · dataverse ird fr | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:remote-sensing | mapping · dataverse ird fr | vocabulary-mapper@1.0.0 | keywords['remote sensing'] |
| concepts[modality].local:modality:tabular | enrichment · dataverse ird fr | keyword-concept-rules@1.0.0 | title+description (65%) |
| created_date | source · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | |
| description | source · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | /description |
| publication_date | source · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | |
| title | source · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | /name |
| updated_date | source · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 | |
| version_label | source · dataverse ird fr | connector:dataverse_ird_fr@1.0.0 |