Microscale Temperature-Humidity Index (THI) Distribution Estimated at the City Scale: A Case Study in Maebashi City, Gunma Prefecture, Japan
Abstract
:1. Introduction
2. Equipment and Datasets
2.1. Unmanned Aerial System (UAS) and Camera Specification
2.2. GNSS and Thermohygrometer
2.3. Satellite and Aircraft Data
2.4. Flight Design for UAS
2.5. Ground Truth Collection of the Reference THI
2.5.1. Ground Truth at Site 1
2.5.2. Ground Truth Within the City
2.6. Mobility and Building Floor Data
3. Methodology
3.1. Study Area
3.2. Spatial Data and Variable Construction
3.2.1. Aerial Image and Digital Surface Model
3.2.2. Solar Radiation and Wind Exposure
3.2.3. Satellite Indices
3.2.4. Mobility Data and Building Floor Area
3.3. Random Forest Modeling and Validation of THI
4. Results
4.1. Ortho, Thermal Mosaics, and DSM
4.2. Explanatory Variables
4.3. THI Modeling and Validation
5. Discussion
5.1. Improving THI Modeling through Multiplatform Data Integration
5.2. Urban Geometry and Its Impact on Thermal Discomfort
5.3. Microscale Urban Climate Analysis
5.4. Methodological Considerations
6. Conclusions and Future Work
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Iizuka, K.; Akiyama, Y.; Takase, M.; Fukuba, T.; Yachida, O. Microscale Temperature-Humidity Index (THI) Distribution Estimated at the City Scale: A Case Study in Maebashi City, Gunma Prefecture, Japan. Remote Sens. 2024, 16, 3164. https://doi.org/10.3390/rs16173164
Iizuka K, Akiyama Y, Takase M, Fukuba T, Yachida O. Microscale Temperature-Humidity Index (THI) Distribution Estimated at the City Scale: A Case Study in Maebashi City, Gunma Prefecture, Japan. Remote Sensing. 2024; 16(17):3164. https://doi.org/10.3390/rs16173164
Chicago/Turabian StyleIizuka, Kotaro, Yuki Akiyama, Minaho Takase, Toshikazu Fukuba, and Osamu Yachida. 2024. "Microscale Temperature-Humidity Index (THI) Distribution Estimated at the City Scale: A Case Study in Maebashi City, Gunma Prefecture, Japan" Remote Sensing 16, no. 17: 3164. https://doi.org/10.3390/rs16173164