Harris Census Block Group - Building Instance Population

This dataset contains building-level records for Harris County where each building instance is linked to a Census Block Group (GEOID) and assigned an estimated population label derived from demographic ratios and occupancy assumptions. It combines geometric/location attributes (building polygons or centroids), structural/context features (building type, estimated units, parcel-informed classification), and CBG-level demographic context (ppu_*, occupancy_rate) to create ML-ready supervision targets. The core table for modeling is ml_dataset/labels.csv, which ties each building_uid to image crop/mask paths and a numeric estimated_population target. Companion outputs include building-level estimate files (harris_county_building_population_estimates.csv, harris_county_buildings_with_population.geojson) and a CBG-level reference/validation table (harris_county_cbg_validation.csv) keyed by GEOID. Conceptually, it is a spatially joined, feature-engineered population estimation dataset where many buildings map to the same CBG, enabling both geospatial analysis and supervised learning.本数据集收录哈里斯县（Harris County）的建筑级记录，每条建筑实例均关联至一个普查街区组（Census Block Group，CBG），并基于人口统计比率与居住占用假设，为其分配估计人口标签。数据集整合了几何/位置属性（建筑多边形或质心）、结构与上下文特征（建筑类型、估计单元数、基于地块的分类）以及CBG级人口统计上下文（ppu_*、occupancy_rate），以生成可直接用于机器学习的监督学习目标。用于建模的核心数据表为ml_dataset/labels.csv，该表将每个building_uid与图像裁剪/掩码路径及数值型estimated_population目标进行关联。配套输出文件包括建筑级估计文件（harris_county_building_population_estimates.csv、harris_county_buildings_with_population.geojson），以及以GEOID为键的CBG级参考验证表（harris_county_cbg_validation.csv）。从概念层面而言，本数据集属于经空间连接与特征工程处理的人口估计数据集，多个建筑可映射至同一CBG，可同时支撑空间地理分析与监督学习任务。