Integrating GIS-Based Point of Interest and Community Boundary Datasets for Urban Building Energy Modeling
Abstract
:1. Introduction
2. Methods
2.1. Introduction of the Case Study Buildings
2.2. Assign POI and Community Tags to Building Footprints
2.3. Primary Building Use Determination
2.4. Sub-Type Clustering Analysis
2.5. UBEM Case Study
3. Results
3.1. GIS Data Spatial Analysis Results
3.1.1. Assign POIs to Building Footprints
3.1.2. Building Footprints within Community Boundaries
3.2. Primary Building Uses
3.3. Building Sub-Types Clustering
3.4. Validation
3.5. UBEM Case Study
4. Discussion
5. Conclusions
- Considering GIS data spatial inaccuracies, it is important to obtain the appropriate tolerance to include more outside POIs or buildings.
- Through primary use determination and sub-type clustering analysis, the building uses of 47,428 buildings were successfully identified; about 69% of the 68,966 building footprints. The validation results of 7895 sampled building footprints showed an overall accuracy of 86%, which was acceptable based on the limited information used.
- A total of 243 office buildings in the downtown area were divided into three groups for UBEM based on the office building sub-type clustering results.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Category | Sub-category | Amount | Percentage |
---|---|---|---|
Food and Beverages | Chinese Food Restaurant, Ice Cream Shop, etc. | 47,522 | 16.9% |
Enterprise | Company, Factory, etc. | 27,802 | 9.9% |
Shopping | Shopping Center, Supermarket, etc. | 84,615 | 30.0% |
Finance and Insurance Services | Bank, Insurance Company, etc. | 4227 | 1.5% |
Science/Culture and Education Services | Museum, School, etc. | 18,933 | 6.7% |
Commercial Housing | Building, Residential Building, etc. | 8501 | 3.0% |
Daily Life Services | Travel Agency, Post Office, etc. | 52,476 | 18.6% |
Sports and Recreation | Sports Stadium, Theatre and Cinema, etc. | 7141 | 2.5% |
Medical Services | Hospital, Pharmacy, etc. | 9520 | 3.4% |
Governmental Organization and Social Groups | Governmental Organization, Social Group, etc. | 8976 | 3.2% |
Accommodation Services | Hotel, Inn, etc. | 12,054 | 4.3% |
Total | 281,767 | 100% |
Categories | Number of POIs | Categories | Number of POIs |
---|---|---|---|
hotel | 0 | school | 0 |
shopping mall | 0 | hospital | 0 |
commercial office building | 1 | food and beverage | 11 |
culture and art gallery | 0 | company | 42 |
administrative agency | 0 | retail goods | 31 |
residential building | 0 | recreation | 1 |
Distance Tolerance | Number of POIs within a Distance Tolerance | Number of POIs Belonging to Buildings | Accuracy |
---|---|---|---|
1 m | 226 | 204 | 90.3% |
2 m | 386 | 351 | 90.9% |
3 m | 473 | 431 | 91.1% |
4 m | 540 | 482 | 89.3% |
5 m | 592 | 496 | 83.8% |
6 m | 631 | 510 | 80.8% |
Percentage Tolerance | Number of buildings within a Percentage Tolerance | Number of Buildings Belonging to Communities | Accuracy |
---|---|---|---|
90% | 284 | 266 | 93.7% |
80% | 321 | 294 | 91.6% |
70% | 344 | 311 | 90.4% |
60% | 363 | 319 | 87.9% |
Building Use | Number of Buildings |
---|---|
Residential building | 34,448 |
Commercial-residential mixed building | 835 |
Commercial office building | 393 |
Hotel | 960 |
Shopping mall | 91 |
School | 5363 |
Hospital | 649 |
Culture & art gallery | 62 |
Government office building | 602 |
Hotel-office mixed building | 288 |
Hotel-shopping mall mixed building | 53 |
Office-shopping mall mixed building | 10 |
Hotel-office-shopping mall mixed building | 18 |
Other mixed-use building | 114 |
Industrial | 584 |
Retail | 964 |
Tourist | 1351 |
Primary Building Use | Clusters | Number of Buildings | Building Sub-Type Description |
---|---|---|---|
Residential building | Cluster 1 | 29,873 | Residential building |
Cluster 2 | 47 | Residential–office mixed building | |
Clusters 3, 4 | 1409 | Residential building with retail stores on the first floor | |
Clusters 5, 6 | 3119 | Residential building with restaurants on the first floor | |
Commercial office building | Clusters 1, 2 | 70 | Office building for lease |
Cluster 3 | 4 | Office building with retail stores on the first floor | |
Cluster 4 | 305 | Enterprise office building | |
Cluster 5 | 14 | Office building with retail and restaurants on the first floor | |
Hotel | Clusters 1, 2 | 28 | Hotel–office mixed building |
Cluster 3 | 65 | Hotel with retail stores on the first floor | |
Cluster 4 | 717 | Hotel | |
Clusters 5, 6 | 150 | Hotel with restaurants on the first floor | |
Building with no main attributes | Clusters 1, 2 | 58 | Office building for lease |
Cluster 3 | 26 | Shopping mall | |
Cluster 4 | 147 | Retail store | |
Cluster 5 | 3646 | Unidentified | |
Clusters 6, 7 | 384 | Restaurant |
Building Use | Number of Buildings | Number of Identified Buildings | Number of Correct Buildings | Detection Rate | Accuracy |
---|---|---|---|---|---|
Residential building | 5100 | 3947 | 3594 | 77.4% | 91.1% |
Commercial–residential mixed | 94 | 101 | 55 | 100% | 54.5% |
Commercial office | 319 | 173 | 129 | 54.2% | 74.6% |
Hotel | 383 | 301 | 214 | 78.6% | 71.1% |
Shopping mall | 51 | 39 | 22 | 76.5% | 56.4% |
Government office | 312 | 153 | 114 | 49.0% | 74.5% |
School | 287 | 222 | 201 | 77.4% | 90.5% |
Hospital | 206 | 192 | 179 | 93.2% | 93.2% |
Culture and art gallery | 37 | 16 | 11 | 43.2% | 68.8% |
Mixed-use building | 300 | 223 | 146 | 74.3% | 65.5% |
Others | 425 | 223 | 129 | 52.5% | 57.8% |
Parameters | Pre-2005 | 2006–2015 | Post-2016 |
---|---|---|---|
Lighting power density (W/m2) | 25 | 11 | 9 |
Equipment power density (W/m2) | 25 | 20 | 15 |
Occupancy density (person/m2) | 0.125 | 0.125 | 0.125 |
Roof U-value (W/m2·k) | 1.5 | 0.7 | 0.45 |
Wall U-value (W/m2·k) | 2 | 1 | 0.7 |
Window U-value (W/m2·k) | 6.4 | 3 | 2.6 |
Window solar heat gain coefficient (SHGC) | 0.65 | 0.5 | 0.4 |
Chiller coefficient of performance (COP) | 4.2 | 5.1 | 5.6 |
Boiler heating efficiency | 0.55 | 0.89 | 0.9 |
Heating setpoint (℃) | 20 | 20 | 20 |
Cooling setpoint (℃) | 26 | 26 | 26 |
Building Use | Number of Buildings | Averaged Electricity EUI* (kWh/m2) | Averaged Natural Gas EUI (kWh/m2) |
---|---|---|---|
Office building | 233 | 174.2 | 75.1 |
Office building with retail stores on the first floor | 4 | 182.5 | 31.5 |
Office building with retail and restaurants on the first floor | 6 | 186.7 | 45.4 |
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Deng, Z.; Chen, Y.; Pan, X.; Peng, Z.; Yang, J. Integrating GIS-Based Point of Interest and Community Boundary Datasets for Urban Building Energy Modeling. Energies 2021, 14, 1049. https://doi.org/10.3390/en14041049
Deng Z, Chen Y, Pan X, Peng Z, Yang J. Integrating GIS-Based Point of Interest and Community Boundary Datasets for Urban Building Energy Modeling. Energies. 2021; 14(4):1049. https://doi.org/10.3390/en14041049
Chicago/Turabian StyleDeng, Zhang, Yixing Chen, Xiao Pan, Zhiwen Peng, and Jingjing Yang. 2021. "Integrating GIS-Based Point of Interest and Community Boundary Datasets for Urban Building Energy Modeling" Energies 14, no. 4: 1049. https://doi.org/10.3390/en14041049