基于普查数据的中国人口空间分布遥感监测数据集

人口数据是重要的国情要素之一，其空间分布也是社会、经济、资源以及环境相互作用的综合体现。基于普查数据的中国人口空间分布遥感监测数据集综合统计数据、土地利用/覆盖数据、遥感监测等数据，运用地理加权回归等空间分析模型，精细刻画了在标准千米格网上的人口空间分布，反映了同地区、同类型土地资源上的人口差异。
基于普查数据的中国人口空间分布遥感监测数据集可供民政、自然资源、发展规划、应急管理等部门和科研人员应用在全球气候变化、区域发展规划、陆表生态系统、应急管理、空间规划等领域，尤其是在基于自然单元上的人口空间分析中。例如，在突发灾害时，快速地分析灾害影响区域内的受灾人口，开展快速灾害损失评估。
基于普查数据的中国人口空间分布遥感监测数据集能够解决基于统计的人口分布数据难以反映行政区划内部差异、时间尺度可比性差等问题，是人地关系研究的重要基础性数据。基于普查数据的中国人口空间分布遥感监测数据集可以满足我国在城乡发展、资源环境、应急管理等公共服务方面精细化管理的需求，在人地耦合、气候变化等研究领域也具有广泛的应用前景。

Population data is one of the core components of a country's national conditions, and its spatial distribution serves as a comprehensive manifestation of the interactions among society, economy, resources and the environment. The Remote Sensing Monitoring Dataset of China's Population Spatial Distribution Based on Census Data integrates statistical data, land use/cover data, remote sensing monitoring data and other related datasets, and adopts spatial analysis models such as Geographically Weighted Regression (GWR) to finely characterize the population spatial distribution on standard 1km grids, reflecting population differences among land resources of the same type within the same region.

This dataset is available for use by departments including civil affairs, natural resources, development planning, emergency management, as well as researchers, in fields such as global climate change, regional development planning, terrestrial ecosystems, emergency management and spatial planning, particularly in population spatial analysis based on natural units. For instance, in the event of sudden disasters, it can rapidly analyze the affected population within disaster-impacted areas and conduct rapid disaster loss assessments.

The Remote Sensing Monitoring Dataset of China's Population Spatial Distribution Based on Census Data addresses the limitations of traditional statistical population distribution data, such as failing to reflect internal differences within administrative divisions and poor temporal scale comparability, making it an important foundational dataset for human-land relationship research. It can meet China's demand for refined public service management in areas like urban-rural development, resources and environment, and emergency management, and boasts broad application prospects in research fields including human-land coupling and climate change.