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社区首页 >专栏 >Google Earth Engine ——数据全解析专辑(Copernicus Global Land Cover Layers: CGLS-LC100 Collec)2015 年全球土地分类数据集

Google Earth Engine ——数据全解析专辑(Copernicus Global Land Cover Layers: CGLS-LC100 Collec)2015 年全球土地分类数据集

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发布2024-02-02 11:12:53
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发布2024-02-02 11:12:53
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Copernicus Global Land Cover Layers: CGLS-LC100 Collection 2

The Copernicus Global Land Service (CGLS) is earmarked as a component of the Land service to operate a multi-purpose service component that provides a series of bio-geophysical products on the status and evolution of land surface at global scale.

The Dynamic Land Cover map at 100 m resolution (CGLS-LC100) is a new product in the portfolio of the CGLS and delivers a global land cover map at 100 m spatial resolution. The CGLS Land Cover product provides a primary land cover scheme. Next to these discrete classes, the product also includes continuous field layers for all basic land cover classes that provide proportional estimates for vegetation/ground cover for the land cover types. This continuous classification scheme may depict areas of heterogeneous land cover better than the standard classification scheme and, as such, can be tailored for application use (e.g. forest monitoring, crop monitoring, biodiversity and conservation, monitoring environment and security in Africa, climate modelling, etc.).

This Land Cover map is provided for the 2015 reference year over the entire Globe, derived from the PROBA-V 100 m time-series, a database of high quality land cover training sites and several ancillary datasets, reaching an accuracy of 80 % at Level1

哥白尼全球陆地服务 (CGLS) 被指定为陆地服务的一个组成部分,以运营一个多功能服务组件,提供一系列关于全球范围地表状况和演变的生物地球物理产品。

100 m 分辨率的动态土地覆盖图 (CGLS-LC100) 是 CGLS 产品组合中的新产品,可提供 100 m 空间分辨率的全球土地覆盖图。 CGLS Land Cover 产品提供了主要的土地覆盖方案。除了这些离散类别之外,该产品还包括所有基本土地覆盖类别的连续字段图层,为土地覆盖类型的植被/地面覆盖提供比例估计。这种连续分类方案可能比标准分类方案更好地描述异质土地覆盖区域,因此,可以针对应用用途(例如森林监测、作物监测、生物多样性和保护、非洲环境和安全监测、气候建模、等等。)。

该土地覆盖图是为 2015 年全球参考年提供的,源自 PROBA-V 100 m 时间序列、高质量土地覆盖训练站点的数据库和几个辅助数据集,在 Level1 上达到 80% 的准确率

Dataset Availability

2015-01-01T00:00:00 - 2015-01-01T00:00:00

Dataset Provider

Copernicus

Collection Snippet

ee.ImageCollection("COPERNICUS/Landcover/100m/Proba-V/Global")

Resolution

100 meters

Bands Table

Name

Description

Min

Max

Units

discrete_classification

Land cover classification

0

200

discrete_classification-proba

Quality indicator (classification probability) of the discrete classification

0

100

%

forest_type

Forest type for all pixels with tree percentage vegetation cover bigger than 1 %

0

5

bare-coverfraction

Percent vegetation cover for bare-sparse-vegetation land cover class

0

100

%

crops-coverfraction

Percent vegetation cover for cropland land cover class

0

100

%

grass-coverfraction

Percent vegetation cover for herbaceous vegetation land cover class

0

100

%

moss-coverfraction

Percent vegetation cover for moss and lichen land cover class

0

100

%

shrub-coverfraction

Percent vegetation cover for shrubland land cover class

0

100

%

tree-coverfraction

Percent vegetation cover for forest land cover class

0

100

%

snow-coverfraction

Percent ground cover for snow and ice land cover class

0

100

%

urban-coverfraction

Percent ground cover for built-up land cover class

0

100

%

water-permanent-coverfraction

Percent ground cover for permanent water land cover class

0

100

%

water-seasonal-coverfraction

Percent ground cover for seasonal water land cover class

0

100

%

data-density-indicator

Data density indicator for algorithm input data

0

100

bare-coverfraction-stddev

Quality indicator (std. dev.) of the bare-sparse-vegetation regression

0

100

%

crops-coverfraction-stddev

Quality indicator (std. dev.) of the cropland regression

0

100

%

grass-coverfraction-stddev

Quality indicator (std. dev.) of the herbaceous vegetation regression

0

100

%

moss-coverfraction-stddev

Quality indicator (std. dev.) of the moss and lichen regression

0

100

%

shrub-coverfraction-stddev

Quality indicator (std. dev.) of the shrubland regression

0

100

%

tree-coverfraction-stddev

Quality indicator (std. dev.) of the forest regression

0

100

%

Class Table: discrete_classification

Value

Color

Color Value

Description

0

#282828

Unknown. No or not enough satellite data available.

20

#FFBB22

Shrubs. Woody perennial plants with persistent and woody stems and without any defined main stem being less than 5 m tall. The shrub foliage can be either evergreen or deciduous.

30

#FFFF4C

Herbaceous vegetation. Plants without persistent stem or shoots above ground and lacking definite firm structure. Tree and shrub cover is less than 10 %.

40

#F096FF

Cultivated and managed vegetation / agriculture. Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type.

50

#FA0000

Urban / built up. Land covered by buildings and other man-made structures.

60

#B4B4B4

Bare / sparse vegetation. Lands with exposed soil, sand, or rocks and never has more than 10 % vegetated cover during any time of the year.

70

#F0F0F0

Snow and ice. Lands under snow or ice cover throughout the year.

80

#0032C8

Permanent water bodies. Lakes, reservoirs, and rivers. Can be either fresh or salt-water bodies.

90

#0096A0

Herbaceous wetland. Lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water.

100

#FAE6A0

Moss and lichen.

111

#58481F

Closed forest, evergreen needle leaf. Tree canopy >70 %, almost all needle leaf trees remain green all year. Canopy is never without green foliage.

112

#009900

Closed forest, evergreen broad leaf. Tree canopy >70 %, almost all broadleaf trees remain green year round. Canopy is never without green foliage.

113

#70663E

Closed forest, deciduous needle leaf. Tree canopy >70 %, consists of seasonal needle leaf tree communities with an annual cycle of leaf-on and leaf-off periods.

114

#00CC00

Closed forest, deciduous broad leaf. Tree canopy >70 %, consists of seasonal broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods.

115

#4E751F

Closed forest, mixed.

116

#007800

Closed forest, not matching any of the other definitions.

121

#666000

Open forest, evergreen needle leaf. Top layer- trees 15-70 % and second layer- mixed of shrubs and grassland, almost all needle leaf trees remain green all year. Canopy is never without green foliage.

122

#8DB400

Open forest, evergreen broad leaf. Top layer- trees 15-70 % and second layer- mixed of shrubs and grassland, almost all broadleaf trees remain green year round. Canopy is never without green foliage.

123

#8D7400

Open forest, deciduous needle leaf. Top layer- trees 15-70 % and second layer- mixed of shrubs and grassland, consists of seasonal needle leaf tree communities with an annual cycle of leaf-on and leaf-off periods.

124

#A0DC00

Open forest, deciduous broad leaf. Top layer- trees 15-70 % and second layer- mixed of shrubs and grassland, consists of seasonal broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods.

125

#929900

Open forest, mixed.

126

#648C00

Open forest, not matching any of the other definitions.

200

#000080

Oceans, seas. Can be either fresh or salt-water bodies.

Class Table: forest_type

Value

Color

Color Value

Description

0

#282828

Unknown

1

#666000

Evergreen needle leaf

2

#009900

Evergreen broad leaf

3

#70663E

Deciduous needle leaf

4

#A0DC00

Deciduous broad leaf

5

#929900

Mix of forest types

影像信息:

Name

Type

Description

discrete_classification_class_names

List of Strings

Land cover class names

discrete_classification_class_palette

List of Strings

Land cover class palette

discrete_classification_class_values

List of Ints

Value of the land cover classification.

forest_type_class_names

List of Strings

forest cover class names

forest_type_class_palette

List of Strings

forest cover class palette

forest_type_class_values

List of Ints

forest cover class values

代码:

代码语言:javascript
复制
var dataset = ee.ImageCollection("COPERNICUS/Landcover/100m/Proba-V/Global");

var visualization = {
  bands: ['discrete_classification']
};

Map.setCenter(-88.6, 26.4, 1);

Map.addLayer(dataset, visualization, "Land Cover");

影像:

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