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Cytaty
Cytowania:
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
Potencjalna naturalna roślinność FAPAR przewidywana jako miesięczna mediana (na podstawie PROB-V FAPAR 2014–2017). Opis. Aby uzyskać dostęp do map i wyświetlać je poza Earth Engine, skorzystaj z tej strony. Jeśli zauważysz błąd, artefakt lub niespójność na mapach LandGIS albo masz pytanie, skorzystaj z tych kanałów: Problemy techniczne …
[null,null,[],[[["\u003cp\u003eThis dataset provides monthly and annual potential natural vegetation FAPAR (Fraction of Absorbed Photosynthetically Active Radiation) data.\u003c/p\u003e\n"],["\u003cp\u003eThe data is based on PROB-V FAPAR observations from 2014-2017 and covers the period from 2001 to 2002.\u003c/p\u003e\n"],["\u003cp\u003eThe spatial resolution of the dataset is 1000 meters, with values ranging from 0 to 220.\u003c/p\u003e\n"],["\u003cp\u003eUsers can access and visualize the dataset through Google Earth Engine or the OpenGeoHub platform.\u003c/p\u003e\n"],["\u003cp\u003eIt's licensed under Creative Commons Attribution-ShareAlike 4.0 International License, allowing for sharing and adaptation, even for commercial purposes, with proper attribution.\u003c/p\u003e\n"]]],["The dataset provides monthly median predictions of Potential Natural Vegetation FAPAR, derived from PROB-V FAPAR data from 2014-2017, available from 2001-01-01 to 2002-01-01. It includes 14 bands: 12 monthly FAPAR values (Jan-Dec), an annual value, and an annual difference. Data can be accessed via the provided Earth Engine snippet or externally through OpenGeoHub. Users can report issues via technical and general forums, and the dataset is openly licensed under CC BY-SA 4.0.\n"],null,["# OpenLandMap Potential FAPAR Monthly\n\nDataset Availability\n: 2001-01-01T00:00:00Z--2002-01-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [EnvirometriX Ltd](https://doi.org/10.7910/DVN/QQHCIK)\n\nTags\n:\n[envirometrix](/earth-engine/datasets/tags/envirometrix) [fapar](/earth-engine/datasets/tags/fapar) [monthly](/earth-engine/datasets/tags/monthly) [opengeohub](/earth-engine/datasets/tags/opengeohub) [openlandmap](/earth-engine/datasets/tags/openlandmap) [plant-productivity](/earth-engine/datasets/tags/plant-productivity) [potential](/earth-engine/datasets/tags/potential) \n\n#### Description\n\nPotential Natural Vegetation FAPAR predicted monthly median (based on PROB-V FAPAR 2014-2017).\n[Description](https://gitlab.com/openlandmap/global-layers/#potential-natural-vegetation).\n\nTo access and visualize maps outside of Earth Engine, use [this page](https://opengeohub.org/about-openlandmap).\n\nIf you discover a bug, artifact or inconsistency in the LandGIS maps\nor if you have a question please use the following channels:\n\n- [Technical issues and questions about the code](https://gitlab.com/openlandmap/global-layers/issues)\n- [General questions and comments](https://disqus.com/home/forums/landgis/)\n\n### Bands\n\n\n**Pixel Size**\n\n1000 meters\n\n**Bands**\n\n| Name | Units | Min | Max | Pixel Size | Description |\n|--------------|----------|-----|-------|------------|-------------------------------------------|\n| `jan` | Fraction | 0\\* | 220\\* | meters | Jan Potential FAPAR monthly |\n| `feb` | Fraction | 0\\* | 220\\* | meters | Feb Potential FAPAR monthly |\n| `mar` | Fraction | 0\\* | 220\\* | meters | Mar Potential FAPAR monthly |\n| `apr` | Fraction | 0\\* | 220\\* | meters | Apr Potential FAPAR monthly |\n| `may` | Fraction | 0\\* | 220\\* | meters | May Potential FAPAR monthly |\n| `jun` | Fraction | 0\\* | 220\\* | meters | Jun Potential FAPAR monthly |\n| `jul` | Fraction | 0\\* | 220\\* | meters | Jul Potential FAPAR monthly |\n| `aug` | Fraction | 0\\* | 220\\* | meters | Aug Potential FAPAR monthly |\n| `sep` | Fraction | 0\\* | 220\\* | meters | Sep Potential FAPAR monthly |\n| `oct` | Fraction | 0\\* | 220\\* | meters | Oct Potential FAPAR monthly |\n| `nov` | Fraction | 0\\* | 220\\* | meters | Nov Potential FAPAR monthly |\n| `dec` | Fraction | 0\\* | 220\\* | meters | Dec Potential FAPAR monthly |\n| `annual` | Fraction | 0\\* | 220\\* | meters | Anuual Potential FAPAR monthly |\n| `annualdiff` | Fraction | 0\\* | 220\\* | meters | Annual Difference Potential FAPAR monthly |\n\n\\* estimated min or max value\n\n### Terms of Use\n\n**Terms of Use**\n\nThis is a human-readable summary of (and not a substitute for) the [license](https://creativecommons.org/licenses/by-sa/4.0/).\n\nYou are free to -\nShare - copy and redistribute the material in any medium or format\nAdapt - remix, transform, and build upon the material for any purpose, even commercially.\n\nThis license is acceptable for Free Cultural Works.\nThe licensor cannot revoke these freedoms as long as you follow the license terms.\n\nUnder the following terms -\nAttribution - You must give appropriate credit, provide a link to the license, and indicate if\nchanges were made. You may do so in any reasonable manner, but not in any way that suggests the\nlicensor endorses you or your use.\n\nShareAlike - If you remix, transform, or build upon the material, you must distribute your\ncontributions under the same license as the original.\n\nNo additional restrictions - You may not apply legal terms or technological measures that\nlegally restrict others from doing anything the license permits.\n\n### Citations\n\nCitations:\n\n- 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.\n [10.7287/peerj.preprints.26811v5](https://doi.org/10.7910/DVN/QQHCIK)\n\n### DOIs\n\n- \u003chttps://doi.org/10.7910/DVN/QQHCIK\u003e\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.Image('OpenLandMap/PNV/PNV_FAPAR_PROBA-V_D/v01');\n\nvar visualization = {\n bands: ['jan'],\n min: 0.0,\n max: 220.0,\n palette: ['0000ff', '00ffff', 'ffff00', 'ff0000']\n};\n\nMap.centerObject(dataset);\n\nMap.addLayer(dataset, visualization, 'Potential FAPAR monthly');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/OpenLandMap/OpenLandMap_PNV_PNV_FAPAR_PROBA-V_D_v01) \n[OpenLandMap Potential FAPAR Monthly](/earth-engine/datasets/catalog/OpenLandMap_PNV_PNV_FAPAR_PROBA-V_D_v01) \nPotential 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: Technical issues ... \nOpenLandMap/PNV/PNV_FAPAR_PROBA-V_D/v01, envirometrix,fapar,monthly,opengeohub,openlandmap,plant-productivity,potential \n2001-01-01T00:00:00Z/2002-01-01T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [https://doi.org/10.7910/DVN/QQHCIK](https://doi.org/https://doi.org/10.7910/DVN/QQHCIK)\n- [https://doi.org/10.7910/DVN/QQHCIK](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_PNV_PNV_FAPAR_PROBA-V_D_v01)"]]