Data · dataset · 2023
SPOT6 satellite imagery, land cover and land use classification of 5 areas in the South Province of New Caledonia
Listed in DataSuds
5 areas of New Caledonia covered by the SPOT6 satellite are available at 1.5 meters resolution (RGB + PIR), totaling 128,4 km².
Description
These 5 areas have been manually segmented and then classified by photo-interpretation according to two types of classification: (i) classification of the bio-geophysical land cover, containing 6 different classes (buildings, bare soil, forest, low-density vegetation; water bodies, Shadows and Clouds); (ii) classification of the land use divided into 15 distinct classes.
Two levels of hierarchy have been established. The first level separates four classes: the urban fabric, the natural formation, the wetlands and the shadows and clouds. The second level is described in the file "NC_NomLU.png".
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The SPOT6 data, recorded in the course of 2013-2014, have been radiometrically corrected and assembled into a mosaic. The data were provided as ortho-rectified tiles based on the local authorities' 10-meter DTM and projected according to the reference coordinate system RGCN91-93 / Lambert New Caledonia (EPSG:3163). Results are provided as a GeoTIFF file for each area.
The goal of this dataset, is to prepare the set-up of an operational system for land use and land cover monitoring for the South Province territory of New Caledonia.
Links
Where it is published
- Dataverse dataset page dataverse.ird.fr/dataset.xhtml?persistentId=doi%3A10.23708%2FPHVOJD ↗
landing page · from dataverse ird fr
- DOI doi.org/10.23708/phvojd ↗
DOI / persistent id · from dataverse ird fr
Catalogue records · 1
- Dataverse API dataverse.ird.fr/api/datasets/:persistentId/?persistentId=doi%3A10.23708%2FPHVO… ↗
metadata API · from dataverse ird fr
Topics
- Stated by source
- Computer and Information Science · Earth and Environmental Sciences
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataSuds | doi:10.23708/PHVOJD | 13 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:remote-sensing | mapping · dataverse ird fr | vocabulary-mapper@1.0.0 | keywords['Remote Sensing'] |
| 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 |