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社区首页 >专栏 >Google Earth Engine ——全球森林/非森林地图(FNF)数据集

Google Earth Engine ——全球森林/非森林地图(FNF)数据集

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发布2024-02-02 09:24:16
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发布2024-02-02 09:24:16
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The global forest/non-forest map (FNF) is generated by classifying the SAR image (backscattering coefficient) in the global 25m resolution PALSAR-2/PALSAR SAR mosaic so that strong and low backscatter pixels are assigned as "forest" and "non-forest", respectively. Here, "forest" is defined as the natural forest with the area larger than 0.5 ha and forest cover over 10%. This definition is the same as the Food and Agriculture Organization (FAO) definition. Since the radar backscatter from the forest depends on the region (climate zone), the classification of Forest/Non-Forest is conducted by using a region-dependent threshold of backscatter. The classification accuracy is checked by using in-situ photos and high-resolution optical satellite images. Detailed information is available in the provider's Dataset Description.

Attention:

  • Backscatter values may vary significantly from path to path over high latitude forest areas. This is due to the change of backscattering intensity caused by freezing trees in winter. Please note that this may affect the classification of forest/non-forest.
代码语言:javascript
复制
全球森林/非森林地图(FNF)是通过对全球 25m 分辨率 PALSAR-2/PALSAR SAR 马赛克中的 SAR 影像(后向散射系数)进行分类,从而将强和低后向散射像素分配为“森林”和“非-森林”,分别。这里的“森林”是指面积大于0.5公顷、森林覆盖率超过10%的天然林。该定义与粮食及农业组织 (FAO) 的定义相同。由于来自森林的雷达后向散射取决于区域(气候带),因此使用与区域相关的后向散射阈值来进行森林/非森林的分类。通过使用原位照片和高分辨率光学卫星图像检查分类精度。提供者的数据集描述中提供了详细信息。

注意力:

在高纬度森林地区,不同路径的反向散射值可能会有很大差异。这是由于冬季树木结冰引起后向散射强度的变化。请注意,这可能会影响森林/非森林的分类。

Dataset Availability

2007-01-01T00:00:00 - 2018-01-01T00:00:00

Dataset Provider

JAXA EORC

Collection Snippet

ee.ImageCollection("JAXA/ALOS/PALSAR/YEARLY/FNF")

Resolution

25 meters

Bands Table

Name

Description

Min

Max

fnf

Forest/Non-Forest landcover classification

1

3

Class Table: fnf

Value

Color

Color Value

Description

1

#006400

Forest

2

#FEFF99

Non-Forest

3

#0000FF

Water

数据说明:JAXA retains ownership of the dataset and cannot guarantee any problem caused by or possibly caused by using the datasets. Anyone wishing to publish any results using the datasets should clearly acknowledge the ownership of the data in the publication.

引用:

Masanobu Shimada, Takuya Itoh, Takeshi Motooka, Manabu Watanabe, Shiraishi Tomohiro, Rajesh Thapa, and Richard Lucas, "New Global Forest/Non-forest Maps from ALOS PALSAR Data (2007-2010)", Remote Sensing of Environment, 155, pp. 13-31, December 2014. doi:10.1016/j.rse.2014.04.014.

代码:

代码语言:javascript
复制
var dataset = ee.ImageCollection('JAXA/ALOS/PALSAR/YEARLY/FNF')
                  .filterDate('2017-01-01', '2017-12-31');
var forestNonForest = dataset.select('fnf');
var forestNonForestVis = {
  min: 1.0,
  max: 3.0,
  palette: ['006400', 'FEFF99', '0000FF'],
};
Map.setCenter(136.85, 37.37, 4);
Map.addLayer(forestNonForest, forestNonForestVis, 'Forest/Non-Forest');
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