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社区首页 >专栏 >Google Earth Engine——潜在的自然植被FAPAR预测月度中值(基于PROB-V FAPAR 2014-2017)

Google Earth Engine——潜在的自然植被FAPAR预测月度中值(基于PROB-V FAPAR 2014-2017)

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发布2024-02-02 10:13:36
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发布2024-02-02 10:13:36
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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:

潜在的自然植被FAPAR预测月度中值(基于PROB-V FAPAR 2014-2017)。说明。

要在地球引擎之外访问和可视化地图,请使用此页面。

如果您发现LandGIS地图中的错误、伪装或不一致之处,或者您有问题,请使用以下渠道。

关于代码的技术问题和疑问 一般问题和评论

Dataset Availability

2001-01-01T00:00:00 - 2002-01-01T00:00:00

Dataset Provider

EnvirometriX Ltd

Collection Snippet

ee.Image("OpenLandMap/PNV/PNV_FAPAR_PROBA-V_D/v01")

Resolution

1000 meters

Bands Table

Name

Description

Min*

Max*

Units

jan

Jan Potential FAPAR monthly

0

220

fraction

feb

Feb Potential FAPAR monthly

0

220

fraction

mar

Mar Potential FAPAR monthly

0

220

fraction

apr

Apr Potential FAPAR monthly

0

220

fraction

may

May Potential FAPAR monthly

0

220

fraction

jun

Jun Potential FAPAR monthly

0

220

fraction

jul

Jul Potential FAPAR monthly

0

220

fraction

aug

Aug Potential FAPAR monthly

0

220

fraction

sep

Sep Potential FAPAR monthly

0

220

fraction

oct

Oct Potential FAPAR monthly

0

220

fraction

nov

Nov Potential FAPAR monthly

0

220

fraction

dec

Dec Potential FAPAR monthly

0

220

fraction

annual

Anuual Potential FAPAR monthly

0

220

fraction

annualdiff

Annual Difference Potential FAPAR monthly

0

220

fraction

* = Values are estimated

数据使用:

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.

这是对许可证的可读摘要(而不是替代)。

你可以自由地--分享--以任何媒介或格式复制和再传播这些材料,适应--为任何目的重新混合、改造和建立这些材料,甚至是商业性的。

此许可证可用于自由文化作品。只要你遵守许可条款,许可人就不能撤销这些自由。

在以下条款下--署名--你必须给予适当的荣誉,提供许可证的链接,并说明是否进行了修改。你可以以任何合理的方式这样做,但不能以任何方式暗示许可人认可你或你的使用。

类似共享 - 如果你重新混合、改造或建立在材料的基础上,你必须在与原始材料相同的许可下分发你的贡献。

没有额外的限制--你不得应用法律条款或技术措施,在法律上限制他人做许可证允许的任何事情。

数据引用:

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

https://doi.org/10.7910/DVN/QQHCIK

代码:

代码语言:javascript
复制
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");
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