The data set provides maps describing the land surface, divided into 22 categories, which have been defined by the Land Cover Classification System (LCCS) of the Food and Agriculture Organization of the United Nations (FAO). In addition to the Land Cover (LC) map, four quality markers were produced to record the reliability of classification and change detection.
In order to ensure continuity, these land cover maps are consistent with the global annual LC map series from the 1990s to 2015 produced by the European Space Agency (ESA) Climate Change Initiative (CCI), and can also be obtained on the ESA CCI LC Viewer. To generate this dataset, the full resolution and low resolution archives of the entire Medium Resolution Imaging Spectrometer (MERIS) from 2003 to 2012 were first classified into a unique 10-year baseline LC map. Then use (i) the Advanced Very High Resolution Radiometer (AVHRR) time series from 1992 to 1999, (ii) the SPOT vegetation (SPOT-VGT) time series from 1998 to 2012, and (iii) the changes of PROBA vegetation (PROBA-V) and Sentinel-3 OLCI (S3OLCI) time series in 2013 to retrieve and update.
In addition to the climate modeling community, the long-term consistency, annual update and high thematic details of the dataset on a global scale make it attractive in many applications such as land accounting, forest monitoring and desertification, as well as scientific research.
File name: the land use data is stored in tiff format. For example, the file name is "ESACCI_year. tif", where ESACCI stands for project abbreviation; year from 1992 to 2020
Data reading mode: can be opened and displayed with Arcgis/ENVI software.
欧空局, 欧. (2022). ESA land cover data 300m upstream of the Yangtze River in China (1992-2020). Upper Yangtze River Scientific Data Center, DOI: https://doi.org/10.24381/cds.006f2c9a. (Download the reference：
Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.
To respect the intellectual property rights, protect the rights of data authors, expand services of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.
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Attribution 4.0 International (CC BY 4.0)
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| East: 112.50 | West: 89.00 |
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| South: 20.50 | North: 36.50 |
