Data · dataset · 2024
Land use land cover very high resolution map (1.5-m) for the area of Korhogo, Côte d'Ivoire, 2018
Listed in DataSuds
This dataset is a very-high spatial resolution Land Use / Land Cover (LULC) map of the region of Korhogo, located in northern Côte d’Ivoire (Ivory Coast).
Description
Its spatial resolution is 1.5 m. It was produced in 2018 and made available for a wide range of uses.
It contains 16 land cover classes: ligneous savanna, crop, marsh, riparian forest, dense forest, open forest, rice, cotton, fallows, cashew plantation, mango plantation, built-up, 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 6, 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 83%. 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%2FMTF4S8 ↗
landing page · from dataverse ird fr
- DOI doi.org/10.23708/mtf4s8 ↗
DOI / persistent id · from dataverse ird fr
Catalogue records · 1
- Dataverse API dataverse.ird.fr/api/datasets/:persistentId/?persistentId=doi%3A10.23708%2FMTF4… ↗
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/MTF4S8 | 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 |