Forest Map of New Caledonia
Description
Description
This dataset contains the shapefile of the Caledonian forest produced by digitization at a scale of 1:3,000 from a mosaic of satellite images (Sentinel 2, Quickbird, Pléiades) and aerial photographs provided by the department of infrastructure, topography and land transport (DITTT) of the government of New Caledonia and available on the georep map server (georep.nc). Satellite images and aerial photographs were taken between 2009 and 2021 with a maximum spatial resolution of 0.5 m. We classified the vegetation as a forest when the plants (which must be over 5 meters tall) formed a continuous canopy, obscuring the ground surface over an area of at least 0.5 hectares (FAO 2020). Finally, we consider a polygon as an isolated forest fragment if it is more than 10 meters away from another polygon. When the distance is less than 10 meters, the polygons are merged.
Each of the 12,058 digitized polygons was extensively cross-checked with the Tropical Rainforest Cover Change (TMF) dataset using 41 years of Landsat time series (Vancutsem et al., 2021) and the ETH model providing 10 m resolution of global canopy height (Lang et al., 2023). This consistency analysis between photo-interpretation and radiometric detection was conducted on a 2 km² grid, with verification of each polygon when the divergence exceeded 15%. In total, 1564 polygons, either barely discernible in the images or exhibiting a homogeneous canopy texture, were visually verified by helicopter overflight. At least, forest polygons were verified through databases of plant occurrences collected in the forest, in particular the Herbarium of New Caledonia database (NOU) and the New Caledonian Plant Inventories and Permanent Plots Network (NC-PIPPN).
Content
This dataset was generated, analyzed, and validated using a suite of open-source software tools, including QGIS, PostgreSQL, PostGIS, Python, and the GDAL library, operating on a Linux platform. The compressed file includes six essential files formatted for an ESRI GIS system, utilizing the WGS84 international coordinate system. It is compatible for upload into spatial databases such as PostgreSQL/PostGIS..
Each entry in the attribute table represents a forest fragment (a polygon) with associated fields (restricted to 10 characters) :
Field | Type | Description |
id | INTEGER | Unique identifier |
pn | BOOLEAN | True or False, indicating if the polygon overlaps with the Northern province |
ps | BOOLEAN | True or False, indicating if the polygon overlaps with the Southern province |
pil | BOOLEAN | True or False, indicating if the polygon overlaps with the Islands province (Loyalty Islands) |
area_ha | NUMERIC (2 DECIMALS) | Area of the polygon in hectares |
dry_ha | NUMERIC (2 DECIMALS) | Area of the polygon in hectares within the dry life zone according to Holdridge |
moist_ha | NUMERIC (2 DECIMALS) | Area of the polygon in hectares within the moist life zone according to Holdridge |
rain_ha | NUMERIC (2 DECIMALS) | Area of the polygon in hectares within the rain life zone according to Holdridge |
created_by | TEXT | Creator of the polygon |
date_creat | DATE | Date when the polygon was first created |
date_updat | DATE | Date when the polygon was updated |
Limitations
Currently, only the North and South provinces are available, an area of 16,395 km² out of a total of 18,345 km². Digitization of the Loyaulties Islands will be available soon. This dataset is periodically updated with corrections made by field observations and the addition of new expert interpretations, especially on smaller islands that have not been digitized before. We plan to produce the whole map step by step.
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Additional details
Related works
- Is derived from
- Dataset: 10.5281/zenodo.12731521 (DOI)
Dates
- Updated
-
2024-07-15
References
- Lang, N., Jetz, W., Schindler, K., & Wegner, J. D. (2023). A high-resolution canopy height model of the Earth. Nature Ecology & Evolution, 7(11), 1778–1789. https://doi.org/10.1038/s41559-023-02206-6
- Vancutsem, C., Achard, F., Pekel, J.-F., Vieilledent, G., Carboni, S., Simonetti, D., Gallego, J., Aragao, L., & Nasi, R. (2020). Long-term (1990-2019) monitoring of tropical moist forests dynamics. bioRxiv, 2020.09.17.295774. https://doi.org/10.1101/2020.09.17.295774