ArticleScientific data2025
Dynamic land-cover maps in the Guangdong-Hong Kong-Macao Greater Bay Area at 30 m spatial resolution, 2000-2022.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Urban land use of national economic sectors in Guangdong-Hong Kong-Macao Greater Bay Area from 2015-2022.Scientific data · 2026Article
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8 authors.
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Abstract
As a world-class urban agglomeration, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has experienced substantial land-cover restructuring driven by urbanization, necessitating high temporal resolution monitoring to capture dynamic surface processes. However, traditional land-cover products cannot capture intra-annual dynamics effectively due to their limited update cycles. Therefore, this study generates a publicly accessible dynamic land-cover dataset for the GBA spanning 2000-2022, with a 30-meter spatial resolution and a 15-day temporal resolution. This dataset achieves an overall accuracy of 97.46%, an average accuracy of 94.5%, an F1 score of 95.19%, and a kappa coefficient of 96.78%. The validation results indicated that this dataset significantly enhances the detection of short-term land cover transitions and facilitates the characterization of critical environmental patterns. We anticipate it will serve as a baseline for monitoring agricultural growing cycles, tracking vegetation phenological shifts, and identifying disturbances in forests and croplands caused by natural hazards or anthropogenic activities.
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