China's Gridded Manufacturing Dataset

The growth of the manufacturing industry is the engine of rapid economic growth in developing regions. Characterizing the geographical distribution of manufacturing firms is critically important for scientists and policymakers. However, data on the manufacturing industry used in previous studies either have a low spatial resolution (or fuzzy classification) or high-resolution information is lacking. Here, we propose a map point-of-interest classification method based on machine learning technology and build a dataset of the distribution of Chinese manufacturing firms called the Gridded Manufacturing Dataset. This dataset includes the number and type of manufacturing firms at a 0.01° latitude by 0.01° longitude scale. It includes all manufacturing firms (classified into seven categories) in China in 2015 (4.40 million) and 2019 (6.01 million). This dataset can be used to characterize temporal and spatial patterns in the distribution of manufacturing firms as well as reveal the mechanisms underlying the development of the manufacturing industry and changes in regional economic policies.制造业发展是驱动发展中区域经济快速增长的核心引擎。精准刻画制造企业的地理分布特征，对科研人员与政策制定者而言均具有至关重要的意义。然而，既往研究中所使用的制造业相关数据，要么空间分辨率较低（或分类模糊），要么缺乏高精度空间信息。本研究提出一种基于机器学习技术的地图兴趣点（Point-of-Interest，POI）分类方法，并构建了中国制造企业分布数据集，命名为网格化制造企业数据集（Gridded Manufacturing Dataset）。该数据集包含经纬度0.01°×0.01°网格尺度下的制造企业数量与类型信息，覆盖中国2015年（440万家）与2019年（601万家）全部7大类制造企业。该数据集可用于刻画制造企业分布的时空格局，同时能够揭示制造业发展与区域经济政策调整背后的内在机制。