- Dataset Availability
- 2001-01-01T00:00:00Z–2002-01-01T00:00:00
- Dataset Provider
- EnvirometriX Ltd
- Earth Engine Snippet
-
ee.Image("OpenLandMap/PNV/PNV_FAPAR_PROBA-V_D/v01")Sign up for Earth Engine
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- Tags
Description
Potential Natural Vegetation FAPAR predicted monthly median (based on PROB-V FAPAR 2014-2017). Description.
To access and visualize maps outside of Earth Engine, use this page.
If you discover a bug, artifact or inconsistency in the LandGIS maps or if you have a question please use the following channels:
Bands
Resolution
1000 meters
Bands
| Name | Units | Min | Max | Description |
|---|---|---|---|---|
jan |
1 (unspecified fraction) | 0* | 220* | Jan Potential FAPAR monthly |
feb |
1 (unspecified fraction) | 0* | 220* | Feb Potential FAPAR monthly |
mar |
1 (unspecified fraction) | 0* | 220* | Mar Potential FAPAR monthly |
apr |
1 (unspecified fraction) | 0* | 220* | Apr Potential FAPAR monthly |
may |
1 (unspecified fraction) | 0* | 220* | May Potential FAPAR monthly |
jun |
1 (unspecified fraction) | 0* | 220* | Jun Potential FAPAR monthly |
jul |
1 (unspecified fraction) | 0* | 220* | Jul Potential FAPAR monthly |
aug |
1 (unspecified fraction) | 0* | 220* | Aug Potential FAPAR monthly |
sep |
1 (unspecified fraction) | 0* | 220* | Sep Potential FAPAR monthly |
oct |
1 (unspecified fraction) | 0* | 220* | Oct Potential FAPAR monthly |
nov |
1 (unspecified fraction) | 0* | 220* | Nov Potential FAPAR monthly |
dec |
1 (unspecified fraction) | 0* | 220* | Dec Potential FAPAR monthly |
annual |
1 (unspecified fraction) | 0* | 220* | Anuual Potential FAPAR monthly |
annualdiff |
1 (unspecified fraction) | 0* | 220* | Annual Difference Potential FAPAR monthly |
Terms of Use
Terms of Use
This is a human-readable summary of (and not a substitute for) the license.
You are free to - Share - copy and redistribute the material in any medium or format Adapt - remix, transform, and build upon the material for any purpose, even commercially.
This license is acceptable for Free Cultural Works. The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms - Attribution - You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
ShareAlike - If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Citations
Hengl T, Walsh MG, Sanderman J, Wheeler I, Harrison SP, Prentice IC. (2018) Global Mapping of Potential Natural Vegetation: An Assessment of Machine Learning Algorithms for Estimating Land Potential. PeerJ Preprints. 10.7287/peerj.preprints.26811v5
DOIs
Explore in Earth Engine
var dataset = ee.Image('OpenLandMap/PNV/PNV_FAPAR_PROBA-V_D/v01');
var visualization = {
bands: ['jan'],
min: 0.0,
max: 220.0,
palette: ['0000ff', '00ffff', 'ffff00', 'ff0000']
};
Map.centerObject(dataset);
Map.addLayer(dataset, visualization, 'Potential FAPAR monthly');