Joint Super-Resolution and Segmentation for 1-m Impervious Surface Area Mapping in China’s Yangtze River Economic Belt

<b><i>High-resolution impervious surface area (ISA) mapping is critical for a wide range of applications, including sustainable urban planning, flood risk assessment, and land use monitoring. However, the production of meter ISA products has long relied on commercial very high-resolution (VHR) satellite imagery, which is cost-prohibitive and geographically limited. To this end, we propose a novel joint framework by integrating super-resolution and segmentation, called JointSeg, which enables the generation of 1-meter ISA maps directly from freely available Sentinel-2 imagery (10m resolution). JointSeg was trained on multimodal cross-resolution inputs, offering a scalable and affordable alternative to traditional approaches. This synergistic design enables gradual resolution enhancement from 10m to 1m while preserving fine-grained spatial textures, and ensures high classification fidelity through effective cross-scale feature fusion. This method has been successfully applied to the Yangtze River Economic Belt (YREB), a region characterized by complex urban–rural patterns and diverse topography. As a result, a comprehensive ISA mapping product for 2021, referred to as ISA-1, was generated, covering an area of over 2.2 million square kilometers. Quantitative comparisons against the 10m ESA WorldCover and other benchmark products reveal that ISA-1 achieves an F1-score of 85.71%, outperforming bilinear-interpolation-based segmentation by 9.5%, and surpassing other ISA datasets by 21.43%-61.07%. In densely urbanized areas (e.g., Suzhou, Nanjing), ISA-1 reduces ISA overestimation through improved discrimination of green spaces and water bodies. Conversely, in mountainous regions (e.g., Ganzi, Zhaotong), it identifies significantly more ISA due to its enhanced ability to detect fragmented anthropogenic features such as rural roads and sparse settlements, demonstrating its robustness across diverse landscapes. Moreover, we present biennial ISA maps from 2017 to 2023, capturing spatiotemporal urbanization dynamics across representative cities. The results highlight distinct regional growth patterns: rapid expansion in upstream cities, moderate growth in midstream regions, and saturation in downstream metropolitan areas. These findings underscore the framework’s utility for continuous, high-resolution urban monitoring using only open-access data. In summary, our method establishes a transformative approach to ISA mapping by overcoming the resolution limitations of medium-resolution imagery. This technique opens new possibilities for large-scale, fine-resolution ISA monitoring without the dependency on expensive VHR data, thus supporting global efforts in sustainable development and urban resilience planning.</i></b>

高分辨率不透水面面积（High-resolution impervious surface area，ISA）制图广泛应用于可持续城市规划、洪水风险评估与土地利用监测等诸多领域。长期以来，米级分辨率不透水面产品的生产依赖商用超高分辨率（very high-resolution，VHR）卫星影像，不仅成本高昂，且地理覆盖范围有限。为此，本文提出一种融合超分辨率与语义分割的新型联合框架JointSeg，可直接从免费获取的10米分辨率Sentinel-2影像生成1米分辨率不透水面制图产品。

JointSeg基于多模态跨分辨率输入数据进行训练，为传统方法提供了一种可扩展且经济实惠的替代方案。该协同设计可实现从10米到1米的渐进式分辨率提升，同时保留精细空间纹理细节，并通过高效的跨尺度特征融合保障高分类精度。本方法已成功应用于长江经济带（Yangtze River Economic Belt，YREB）——这一区域兼具复杂城乡空间格局与多样地形地貌。最终，研究生成了2021年的综合不透水面制图产品ISA-1，覆盖面积超过220万平方千米。

通过与10米分辨率欧空局WorldCover（ESA WorldCover）产品及其他基准数据集的定量对比，ISA-1的F1分数达到85.71%，较基于双线性插值的分割方法提升9.5%，较其他不透水面数据集提升21.43%~61.07%。在苏州、南京等人口密集的城市化区域，ISA-1通过增强对绿地与水体的区分能力，有效减少了不透水面面积的高估现象；而在甘孜、昭通等山区，得益于对乡村道路、零散聚落等零散人为活动地物的检测能力提升，该方法识别出的不透水面面积显著更多，展现出在多样景观下的鲁棒性。

此外，本研究还发布了2017至2023年的两年期不透水面制图产品，捕捉了典型城市的时空城市化动态特征。结果显示出鲜明的区域增长模式：上游城市扩张迅速，中游区域增长平缓，下游大都市圈则已进入饱和状态。这些结果凸显了本框架仅使用开放获取数据即可实现连续高分辨率城市监测的实用价值。

综上，本研究提出的方法突破了中分辨率影像的分辨率限制，为不透水面制图建立了一种变革性路径。该技术无需依赖昂贵的超高分辨率数据，即可为大规模精细分辨率不透水面监测开辟新可能，从而为全球可持续发展与城市韧性规划工作提供有力支撑。

搜集汇总

背景与挑战

背景概述

该数据集提供了中国长江经济带2017-2023年的1米分辨率不透水地表面积(ISA)地图，采用创新的联合超分辨率和分割方法(JointSeg)从10米Sentinel-2影像生成，覆盖面积达220万平方公里，精度达85.71%，适用于可持续城市规划和土地监测等应用。