Spatiotemporal built-up patterns of 3 Romanian and 3 Polish cities

This dataset contains the derived spatial data and summary indicators used in the article “Divergent land consumption trajectories in post-socialist Romania and Poland: A spatiotemporal analysis of built-up expansion (1975–2020)”. It provides open, fine-scale evidence on built-up growth patterns in six second-tier cities in Central and Eastern Europe: Szczecin, Bydgoszcz and Lublin (Poland) and Timișoara, Cluj-Napoca and Iași (Romania). The dataset is based on the Global Human Settlements Layer (GHSL) products produced by the European Commission’s Joint Research Centre. We use the GHS-BUILT-S (built-up surface), GHS-BUILT-V (built-up volume) and GHS-POP (population) grids at 100 m resolution for the epochs 1975, 1990, 2000 and 2015, which we process to estimate total built-up area and built-up area per capita over time. The original GHSL rasters are not redistributed here and can be downloaded directly from the JRC. The main spatial unit of analysis is a regular 100 × 100 m grid covering a 20 km road-distance radius around each city centre. For each grid cell, we compute:– Total built-up area per epoch (m²), based on the combination of GHS-BUILT-S and GHS-BUILT-V and an assumed standard floor height;– Population per epoch (persons), from GHS-POP;– Built-up area per capita per epoch (m²/person);– A categorical cluster ID representing one of ten recurrent space–time development patterns identified via time-series clustering of total built-up area trajectories;– City identifier and basic locational attributes. The dataset is organised in the following files:– Two vector files (Shapefile) containing the 100 m grid cells for all six cities, with attributes for city ID, cluster ID, cluster colour, total built-up area by epoch, population by epoch and built-up area per capita by epoch;– Two Excel files summarising cluster-level statistics (e.g. total area, average built-up area per capita, population) by country;– A codebook / README describing variables, units, and processing steps. The purpose of this dataset is to allow users to: (i) replicate the main quantitative results and figures reported in the article; (ii) explore the space–time patterns of built-up expansion across the six case-study cities; and (iii) reuse the classification of development clusters in comparative research on post-socialist urbanisation, land consumption and sprawl. Users should note that all derived indicators are subject to the spatial and temporal uncertainties inherent in GHSL products and the methodological assumptions described in the article (e.g. uniform floor height). The data are provided for research and teaching purposes and should be interpreted in conjunction with the methodological description in the associated paper.本数据集包含发表于论文《后社会主义罗马尼亚与波兰的土地消耗轨迹差异：1975–2020年建成区扩张时空分析》中所用的衍生空间数据与汇总统计指标。它为中东欧6座二线城市的建成区增长模式提供了开放获取的精细尺度实证证据，这6座城市分别为波兰的什切青（Szczecin）、比得哥什（Bydgoszcz）与卢布林（Lublin），以及罗马尼亚的蒂米什瓦拉（Timișoara）、克卢日-纳波卡（Cluj-Napoca）与雅西（Iași）。 本数据集基于欧盟委员会联合研究中心（Joint Research Centre, JRC）生产的全球人类住区图层（Global Human Settlements Layer, GHSL）产品。我们采用了分辨率为100米的GHS-BUILT-S（建成地表面积）、GHS-BUILT-V（建成体体积）与GHS-POP（人口）栅格数据，对应1975、1990、2000与2015四个时间节点，并对其进行处理以估算随时间变化的总建成区面积与人均建成区面积。此处未重新分发原始GHSL栅格数据，用户可直接从JRC下载获取。 本分析的核心空间单元为覆盖各城市中心周边20公里道路距离范围的规则100×100米栅格。针对每个栅格单元，我们计算了以下指标： - 各时间节点的总建成区面积（单位：平方米）：基于GHS-BUILT-S与GHS-BUILT-V的组合，并结合假定的标准楼层高度计算得出； - 各时间节点的人口数量（单位：人）：源自GHS-POP数据； - 各时间节点的人均建成区面积（单位：平方米/人）； - 分类聚类ID：代表通过对总建成区面积变化轨迹进行时间序列聚类所识别出的10种重复出现的时空发展模式之一； - 城市标识符与基本区位属性。 本数据集由以下文件构成： - 两份矢量文件（Shapefile格式）：包含全部6座城市的100米栅格单元，附带的属性字段包括城市ID、聚类ID、聚类配色、各时间节点总建成区面积、各时间节点人口数量以及各时间节点人均建成区面积； - 两份Excel文件：按国家汇总了聚类层面的统计指标（如总占地面积、人均建成区面积平均值、人口总量等）； - 一份代码簿/自述文件（codebook/README）：对变量、单位与处理步骤进行详细说明。 本数据集的设计目标为支持用户实现以下三类工作：(i) 复现论文中报告的主要定量结果与可视化图表；(ii) 探索6座案例城市的建成区扩张时空模式；(iii) 将发展模式聚类的分类结果复用至后社会主义城市化、土地消耗与城市蔓延的比较研究中。 用户需注意，所有衍生指标均受GHSL产品固有空间与时间不确定性，以及论文中所述方法学假设（如统一楼层高度）的影响。本数据仅用于研究与教学目的，解读时需结合相关论文中的方法学描述。