LULC-1m: High-resolution land use/land cover data of 33 major Chinese cities based on remote sensing imagery

With the rapid advancement of urbanization, detailed land use/land cover data are of great significance for urban management, ecological assessment, and sustainable development research. This paper proposes and constructs a high-precision LULC dataset—LULC-1m—covering 33 major Chinese cities with a spatial resolution of 1 meter. Based on multi-source high-resolution remote sensing imagery, this dataset utilizes an automated processing workflow and deep learning semantic segmentation algorithms to achieve fine-grained identification of seven typical LULC types on the urban surface (overall accuracy reaching 88.90%). This study systematically designed the data processing workflow, semantic consistency control, and cross-regional generalization capabilities, significantly improving the consistency, accuracy, and applicability of the data. LULC-1m provides crucial fundamental data support for land spatial monitoring, carbon emission accounting, and environmental modeling at the scale of Chinese urban agglomerations, and has broad prospects for scientific research and policy applications.