Shranjeno v:
| Main Authors: | , , , , , , , , |
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| Format: | Recurso digital |
| Jezik: | angleščina |
| Izdano: |
Zenodo
2026
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| Teme: | |
| Online dostop: | https://doi.org/10.5281/zenodo.19696524 |
| Oznake: |
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- <p>HK-BFETD is a building-level bilingual (English_Chinese) dataset for Hong Kong, developed to support urban building energy modeling (UBEM) and related spatial energy analyses. It provides EMSD-aligned functional typologies, mixed-use proportional vectors, and geospatial building units that enable consistent linkage between official sectoral energy statistics and building-level spatial records.</p> <p>This release (v1.0.0) includes:<br>1) HK_UBEM_Buildings_Public_v1.csv<br>2) HK_UBEM_Buildings_Public_v1.geojson<br>3) Validation materials (audit tables and supporting files)</p> <p>The tabular product contains 341,153 building records and 30 fields, including footprint/floor attributes, UBEM main and sub classes, mixed-use proportions, classification provenance, and probabilistic outputs for uncertainty-aware allocation.</p> <p>Main-class counts in this release are:<br>- Residential_住宅类别: 251,901<br>- Commercial_商业类别: 49,129<br>- Mixed-use_混合用途: 31,395<br>- Non-assessed_非评估类别: 5,373<br>- Industrial_工业类别: 3,355</p> <p>Usage scope:<br>HK-BFETD is designed as a spatial typology and allocation dataset for benchmark-informed urban energy applications. It is suitable for city-scale stock characterization, mixed-use allocation, sectoral aggregation, scenario construction, and policy-oriented comparative analysis. For mixed-use buildings, UBEM_Mixed_Proportions can be used as initial allocation weights when distributing area- or emission-related quantities across functional sectors.</p> <p>Interpretation note:<br>Probability vectors represent epistemic uncertainty and should be interpreted as probabilistic allocation weights rather than direct measurements. The dataset does not provide building-specific measured energy consumption, conditioned floor area, HVAC system characteristics, or detailed operational schedules; therefore, detailed building-by-building simulation requires additional project-specific assumptions and external data.</p> <p>Traceability:<br>Classification_Source and related provenance fields support source-aware filtering and uncertainty management. Deterministic preprocessing and rule-based stages are script-traceable, while AI-assisted stages are documented through prompts, thresholds, logs, and workflow metadata. Exact byte-identical replay of API-mediated outputs may depend on external model availability and service state.</p> <p>Data provenance note:<br>Some raw source datasets used in preprocessing (e.g., official or third-party source layers) are governed by their own licenses and are therefore not redistributed in this Zenodo record. This record publishes the release-ready derived products and accompanying documentation for reuse and citation.</p>