Published January 1, 2025
| Version v2
Dataset
Open
ALCC: Temporally consistent annual land cover maps over China from 1985 to 2022 based on an ensemble change detection method
Authors/Creators
-
1.
Sun Yat-sen University
Description
We develope a consistent annual land cover product for China (ALCC) from 1985 to 2022. First, change areas for each year was detected baesd on an ensemble change detection method combing CCDC, BFASTm, and Chow Test. Then, stable training samples were derived from both CLCD and CLUDs. The Random Forest classifier was locally trained and used to classify change areas year by year. Finally, ALCC was generated by updating land cover classification results for change areas and remaining class label the same as the base map forthe unchanged areas. ALCC achieved a mean overall accuracy of 81.11±0.67% nationwide and exceeded 72.00% across seven geographical regions.
Files
Files
(29.1 GB)
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