Google Earth Engine ——数据全解析专辑（COPERNICUS/CORINE/V18_5_1/100m）欧洲土地利用数据1986-2012

此星光明

发布于 2024-05-24 08:53:28

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发布于 2024-05-24 08:53:28

The CORINE (coordination of information on the environment) Land Cover (CLC) inventory was initiated in 1985 to standardize data collection on land in Europe to support environmental policy development. The project is coordinated by the European Environment Agency (EEA) in the frame of the EU Copernicus programme and implemented by national teams. The number of participating countries has increased over time currently including 33 (EEA) member countries and six cooperating countries (EEA39) with a total area of over 5.8 Mkm2.

The reference year of the first CLC inventory was 1990 and the first update created in 2000. Later, the update cycle has become 6 years. Satellite imagery provides the geometrical and thematic basis for mapping with in-situ data as essential ancillary information. The basic technical parameters of CLC (i.e. 44 classes in nomenclature, 25 hectares minimum mapping unit (MMU), and 100 meters minimum mapping width) have not changed since the beginning, therefore the results of the different inventories are comparable.

CORINE（环境信息协调）土地覆盖 (CLC) 清单于 1985 年启动，旨在标准化欧洲土地数据收集，以支持环境政策制定。该项目由欧洲环境署 (EEA) 在欧盟哥白尼计划的框架内协调，并由国家团队实施。随着时间的推移，参与国的数量不断增加，目前包括 33 个（欧洲经济区）成员国和六个合作国家（EEA39），总面积超过 5.8 平方公里。

第一次 CLC 清单的参考年份是 1990 年，第一次更新创建于 2000 年。后来，更新周期变成了 6 年。卫星图像为以实地数据作为基本辅助信息的制图提供了几何和专题基础。 CLC的基本技术参数（即44类命名、25公顷最小制图单位（MMU）、100米最小制图宽度）自开始以来没有变化，因此不同清单的结果具有可比性。

Dataset Availability

1986-01-01T00:00:00 - 2012-12-31T00:00:00

Dataset Provider

EEA/Copernicus

Collection Snippet

ee.ImageCollection("COPERNICUS/CORINE/V18_5_1/100m")

Resolution

100 meters

Bands Table

Name	Description
landcover	Land cover

Class Table: landcover

Value	Color Value	Description
1	#E6004D	Artificial surfaces > Urban fabric > Continuous urban fabric
2	#FF0000	Artificial surfaces > Urban fabric > Discontinuous urban fabric
3	#CC4DF2	Artificial surfaces > Industrial, commercial, and transport units > Industrial or commercial units
4	#CC0000	Artificial surfaces > Industrial, commercial, and transport units > Road and rail networks and associated land
5	#E6CCCC	Artificial surfaces > Industrial, commercial, and transport units > Port areas
6	#E6CCE6	Artificial surfaces > Industrial, commercial, and transport units > Airports
7	#A600CC	Artificial surfaces > Mine, dump, and construction sites > Mineral extraction sites
8	#A64DCC	Artificial surfaces > Mine, dump, and construction sites > Dump sites
9	#FF4DFF	Artificial surfaces > Mine, dump, and construction sites > Construction sites
10	#FFA6FF	Artificial surfaces > Artificial, non-agricultural vegetated areas > Green urban areas
11	#FFE6FF	Artificial surfaces > Artificial, non-agricultural vegetated areas > Sport and leisure facilities
12	#FFFFA8	Agricultural areas > Arable land > Non-irrigated arable land
13	#FFFF00	Agricultural areas > Arable land > Permanently irrigated land
14	#E6E600	Agricultural areas > Arable land > Rice fields
15	#E68000	Agricultural areas > Permanent crops > Vineyards
16	#F2A64D	Agricultural areas > Permanent crops > Fruit trees and berry plantations
17	#E6A600	Agricultural areas > Permanent crops > Olive groves
18	#E6E64D	Agricultural areas > Pastures > Pastures
19	#FFE6A6	Agricultural areas > Heterogeneous agricultural areas > Annual crops associated with permanent crops
20	#FFE64D	Agricultural areas > Heterogeneous agricultural areas > Complex cultivation patterns
21	#E6CC4D	Agricultural areas > Heterogeneous agricultural areas > Land principally occupied by agriculture, with significant areas of natural vegetation
22	#F2CCA6	Agricultural areas > Heterogeneous agricultural areas > Agro-forestry areas
23	#80FF00	Forest and semi natural areas > Forests > Broad-leaved forest
24	#00A600	Forest and semi natural areas > Forests > Coniferous forest
25	#4DFF00	Forest and semi natural areas > Forests > Mixed forest
26	#CCF24D	Forest and semi natural areas > Scrub and/or herbaceous vegetation associations > Natural grasslands
27	#A6FF80	Forest and semi natural areas > Scrub and/or herbaceous vegetation associations > Moors and heathland
28	#A6E64D	Forest and semi natural areas > Scrub and/or herbaceous vegetation associations > Sclerophyllous vegetation
29	#A6F200	Forest and semi natural areas > Scrub and/or herbaceous vegetation associations > Transitional woodland-shrub
30	#E6E6E6	Forest and semi natural areas > Open spaces with little or no vegetation > Beaches, dunes, sands
31	#CCCCCC	Forest and semi natural areas > Open spaces with little or no vegetation > Bare rocks
32	#CCFFCC	Forest and semi natural areas > Open spaces with little or no vegetation > Sparsely vegetated areas
33	#000000	Forest and semi natural areas > Open spaces with little or no vegetation > Burnt areas
34	#A6E6CC	Forest and semi natural areas > Open spaces with little or no vegetation > Glaciers and perpetual snow
35	#A6A6FF	Wetlands > Inland wetlands > Inland marshes
36	#4D4DFF	Wetlands > Inland wetlands > Peat bogs
37	#CCCCFF	Wetlands > Maritime wetlands > Salt marshes
38	#E6E6FF	Wetlands > Maritime wetlands > Salines
39	#A6A6E6	Wetlands > Maritime wetlands > Intertidal flats
40	#00CCF2	Water bodies > Inland waters > Water courses
41	#80F2E6	Water bodies > Inland waters > Water bodies
42	#00FFA6	Water bodies > Marine waters > Coastal lagoons
43	#A6FFE6	Water bodies > Marine waters > Estuaries
44	#E6F2FF	Water bodies > Marine waters > Sea and ocean

影像属性：

Name	Type	Description
landcover_class_names	List of Strings	Land cover class names
landcover_class_palette	List of Strings	Land cover class palette
landcover_class_values	List of Ints	Value of the land cover classification.

影像来源：

Access to data is based on a principle of full, open, and free access as established by the Copernicus data and information policy Regulation (EU) No 1159/2013 of 12 July 2013. For more information visit: https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012?tab=metadata.

示例代码：

var dataset = ee.Image('COPERNICUS/CORINE/V18_5_1/100m/2012');
var landCover = dataset.select('landcover');
Map.setCenter(16.436, 39.825, 6);
Map.addLayer(landCover, {}, 'Land Cover');

影像：