OpenLandMap Potential FAPAR monthly

OpenLandMap/PNV/PNV_FAPAR_PROBA-V_D/v01
Dataset Availability
2001-01-01T00:00:00 - 2002-01-01T00:00:00
Dataset Provider
Earth Engine Snippet
ee.Image("OpenLandMap/PNV/PNV_FAPAR_PROBA-V_D/v01")
Tags
fapar monthly potential envirometrix openlandmap opengeohub

Description

Potential Natural Vegetation FAPAR predicted monthly median (based on PROB-V FAPAR 2014-2017). Description.

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Bands

Resolution
1000 meters

Bands

Name Units Min Max Description
jan fraction 0* 220*

Jan Potential FAPAR monthly

feb fraction 0* 220*

Feb Potential FAPAR monthly

mar fraction 0* 220*

Mar Potential FAPAR monthly

apr fraction 0* 220*

Apr Potential FAPAR monthly

may fraction 0* 220*

May Potential FAPAR monthly

jun fraction 0* 220*

Jun Potential FAPAR monthly

jul fraction 0* 220*

Jul Potential FAPAR monthly

aug fraction 0* 220*

Aug Potential FAPAR monthly

sep fraction 0* 220*

Sep Potential FAPAR monthly

oct fraction 0* 220*

Oct Potential FAPAR monthly

nov fraction 0* 220*

Nov Potential FAPAR monthly

dec fraction 0* 220*

Dec Potential FAPAR monthly

annual fraction 0* 220*

Anuual Potential FAPAR monthly

annualdiff fraction 0* 220*

Annual Difference Potential FAPAR monthly

* estimated min or max value

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

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

DOI(s)