University of Kansas, Department of Geography & Atmospheric Science, Lawrence, KS, USA.
Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA.
Sci Data. 2024 Mar 7;11(1):275. doi: 10.1038/s41597-024-03081-x.
Understanding changes in the built environment is vital for sustainable urban development and disaster preparedness. Recent years have seen the emergence of a variety of global, continent-level, and nation-wide datasets related to the current state and the evolution of the built environment, human settlements or building stocks. However, such datasets may face limitations like incomplete coverage, sparse building information, coarse resolution, and limited timeframes. This study addresses these challenges by integrating three spatial datasets to create an extensive, attribute-rich sequence of settlement layers spanning 200 years for the contiguous U.S. This integration process involves complex data processing, merging property-level real estate, parcel, and remote sensing-based building footprint data, and creating gridded multi-temporal settlement layers. This effort unveils the latest edition (Version 2) of the Historical Settlement Data Compilation for the U.S. (HISDAC-US), which includes the latest land use and structural information as of the year 2021. It enables detailed research on urban form and structure, helps assess and map the built environment's risk to natural hazards, assists in population modeling, supports land use analysis, and aids health studies.
了解建成环境的变化对于可持续城市发展和备灾至关重要。近年来,出现了各种与建成环境、人类住区或建筑物存量的现状和演变相关的全球、大陆级和国家级数据集。然而,这些数据集可能存在覆盖不完整、建筑物信息稀疏、分辨率粗糙和时间范围有限等局限性。本研究通过整合三个空间数据集,为美国大陆创建了一个广泛的、具有丰富属性的 200 年时间跨度的居住层序列,从而解决了这些挑战。这个整合过程涉及复杂的数据处理,包括将房地产、包裹和基于遥感的建筑物足迹数据进行合并,并创建网格化多时相居住层。这一努力揭示了美国历史居住数据编纂的最新版本(版本 2)(HISDAC-US),其中包括截至 2021 年的最新土地利用和结构信息。它可以支持对城市形态和结构的详细研究,有助于评估和绘制建成环境对自然灾害的风险图,辅助人口建模,支持土地利用分析,并有助于健康研究。