数据介绍Fig. 1. Study areas for time-series urban land use mapping in China. Spatial distribution of urban area density (defined as the ratio of built-up area to the total administrative area) across China and six representative subregions: (a) Xinjiang, (b) Zhengzhou, (c) Chongqing, (d) Beijing, (e) the Yangtze River Delta, and (f) the Pearl River Delta.Fig. 2. The proposed framework of our study. It includes three major steps: (a) cross-resolution reconstruction, (b) iterative self-enhancing semi-supervised network, (c) time-series Segmentation Optimization with Road Constraints.Fig. 3. Accuracy assessment of land use classification in China from 1984 to 2024. Panels (a)–(i) show the temporal evolution of overall accuracy (OA) and F1-score (F-score) for nine representative land use categories at approximately five-year intervals. The solid blue lines and blue-shaded areas denote the mean OA and its 95% confidence intervals (CIs), respectively; the dashed red lines and red-shaded areas represent the mean F-score and its 95% CIs.Fig. 4. Land use changes over the past 40 years in five representative cities: Beijing, Shanghai, Wuhan, Shenzhen, and Changchun. (a) Ronghua Street in Beijing, (b) Pujiang Town in Shanghai, and (c) Longhua Street in Shenzhen.Fig. 5. Comparison of impervious surface classification across GAIA, GLC_FCS30D, and TCULU in the North China Plain (Note: GAIA and GLC_FCS30D use 1984 and 2022, while TCULU uses 1985 and 2024). Panels (a–c) show a comparison of three datasets near Tongzhou Airport, Beijing, while panels (d–f) illustrate the comparison near Songzhuang, Beijing.Fig. 6. Temporal evolution and inter-period transitions of urban land use in China (1985–2024). (a–i) Proportional changes of different urban land-use categories over time. (j) inter-period land-use conversion flows数据截图由于科研较忙没有将数据完全展示处理【下载→方式一推荐主页 *个人* 简介城数派-CSDN博客方式二数据下载方式汇总-CSDN博客