This spatial tract lookup table provides essential geolocation data for the BuildingsBench performance benchmark dataset. The BuildingsBench Spatial Index serves as a critical mapping resource derived from the comprehensive Buildings-900K simulated building stock. It organizes complex spatial information into a structured lookup table, enabling researchers and engineers to cross-reference geographical tracts with energy performance metrics. The data is formatted for high-compatibility integration, ensuring that large-scale building simulations remain consistent across different analytical platforms. By providing a standardized spatial framework, this index simplifies the correlation between physical building characteristics and regional environmental variables, facilitating more accurate load forecasting and energy consumption modeling for diverse building archetypes.

The download is a 37.3 MB file containing .CSV files.

Professionals integrate this CSV-based index into their data pipelines to map building performance outputs to specific spatial coordinates. Users typically load the dataset into Python or R environments, using it as a relational key to join energy simulation results with census tract identifiers. It is designed for seamless merging with larger performance databases, allowing for efficient filtering and subsetting of building data during the preprocessing stage of machine learning workflows for short-term load forecasting applications.

This dataset is primarily utilized by energy analysts, sustainability consultants, and researchers working on urban-scale energy modeling and grid load forecasting. It is invaluable during the research and development stages of high-performance building projects, where accurate regional benchmarking is required. Engineers often pair this index with other BuildingsBench components to validate energy efficiency strategies across various climate zones and building types. It is a standard tool for those conducting large-scale building stock analysis, optimization studies, and policy-driven energy research within the AEC industry.