Spatial Analysis of Urban Residential Sensitivity to Heatwave Events: Case Studies in Five Megacities in China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data
2.2.1. Meteorological Datasets
2.2.2. Remote Sensing Data
2.2.3. Social Media Weibo Data
2.2.4. Other Auxiliary Datasets
2.3. Methods
2.3.1. Quantifying HWEs in Geographical Space
2.3.2. Extracting the Sensitivity to the HWEs in the Social Media
2.3.3. Matching of LST and Sensitivity to HWEs
3. Results
3.1. Temporal Correlation of HWEs and the Residential Sensitivity to HWEs
3.2. Spatial Patterns of the LST and Residential Sensitivity to HWEs
3.3. Spatial Patterns of the LST and Residential Sensitivity to HWEs
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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_id | Content | PubTime | Latitude | Longitude |
---|---|---|---|---|
6202527610-M_F72PRtRlO | It’s extra hot in Beijing today, and the hot wind is blowing in the face. #Beijing# | 2017/6/9 18:12 | 39.90554 | 116.45202 |
5045403075-M_F71Edysm4 | On the way to work, hot,hot,hot. | 2017/6/9 15:11 | 39.90844 | 116.6659 |
5381580106-M_FfOPwAaCa | Too hot to breathe. | 2017/8/6 11:06 | 39.913162 | 116.397163 |
City | Number of HWE Days | Weibo Data Points Related to HWEs | Number of Weibo Data Points |
---|---|---|---|
Beijing | 19 | 14,563 | 34,419 |
Guangzhou | 19 | 3753 | 9390 |
Nanjing | 23 | 4312 | 8801 |
Wuhan | 21 | 5080 | 11,340 |
Xi’an | 42 | 13,446 | 27,545 |
R | Low (<0.5 std. Dev) | High (≥0.5 std. Dev) | |
---|---|---|---|
LST | |||
Low (<37 °C) | Low–Low | High–Low | |
High (≥37 °C) | Low–High | High–High |
City | Classify of LST Patterns and Sensitivities on Weibo | |||
---|---|---|---|---|
Beijing | R | Low | High | |
LST | ||||
Low | 94 | 428 | ||
High | 228 | 964 | ||
Guangzhou | R | Low | High | |
LST | ||||
Low | 288 | 171 | ||
High | 475 | 354 | ||
Nanjing | R | Low | High | |
LST | ||||
Low | 245 | 102 | ||
High | 430 | 301 | ||
Wuhan | R | Low | High | |
LST | ||||
Low | 227 | 126 | ||
High | 469 | 325 | ||
Xi’an | R | Low | High | |
LST | ||||
Low | 389 | 133 | ||
High | 769 | 504 |
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Zhi, G.; Meng, B.; Wang, J.; Chen, S.; Tian, B.; Ji, H.; Yang, T.; Wang, B.; Liu, J. Spatial Analysis of Urban Residential Sensitivity to Heatwave Events: Case Studies in Five Megacities in China. Remote Sens. 2021, 13, 4086. https://doi.org/10.3390/rs13204086
Zhi G, Meng B, Wang J, Chen S, Tian B, Ji H, Yang T, Wang B, Liu J. Spatial Analysis of Urban Residential Sensitivity to Heatwave Events: Case Studies in Five Megacities in China. Remote Sensing. 2021; 13(20):4086. https://doi.org/10.3390/rs13204086
Chicago/Turabian StyleZhi, Guoqing, Bin Meng, Juan Wang, Siyu Chen, Bin Tian, Huimin Ji, Tong Yang, Bingqing Wang, and Jian Liu. 2021. "Spatial Analysis of Urban Residential Sensitivity to Heatwave Events: Case Studies in Five Megacities in China" Remote Sensing 13, no. 20: 4086. https://doi.org/10.3390/rs13204086