Calculation and Expression of the Urban Heat Island Indices Based on GeoSOT Grid
Abstract
:1. Introduction
2. Study Area and Data Preprocessing
2.1. Study Area
2.2. Land Surface Temperature (LST) Data Preprocessing
3. The UHI Information Model Based on GeoSOT Grid
3.1. The Determination of LST for Grid Cell
3.2. The Integration Model of UHI Information Based on GeoSOT Grid
4. Calculation and Expression of the UHI Indices Based on GeoSOT Grid
4.1. Calculation of the UHI Intensity
4.2. Calculation of the UHI Footprint
4.3. Calculation of the UHI Capacity
4.4. Expression of the UHI Spatial for Distribution Based on GeoSOT Grid
5. Experiments Results and Analysis
5.1. Calculation of the Background Temperature
5.2. Calculation and Expression of the UHI Indices
6. Comparison and Discussion
6.1. The Comparison of Calculation Efficiency
6.2. The Comparison of the UHI Spatial Distribution Expression
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Field Name | Field Description | Constraint | Data Type |
---|---|---|---|
GeoCode-2D | the GeoSOT-2D grid codes | Primary Key | Varchar(30) |
Field Name | Field Description | Constraint | Data Type |
---|---|---|---|
GeoCode-2D | the GeoSOT-2D grid codes | Primary Key | Varchar(30) |
Land Surface Temperature | The land surface temperature for grid center point | Double(8,6) | |
Date | Image date | DATE | |
Time | Image time | DATE | |
Data Source | Satellite ID | Varchar(10) |
Field Name | Field Description | Constraint | Data Type |
---|---|---|---|
GeoCode-2D | the GeoSOT-2D grid codes | Primary Key | Varchar(30) |
Date | Image date | DATE | |
Time | Image time | DATE | |
UHI Intensity | The urban heat island intensity for grid center point | Double(8,6) | |
UHI Footprint | The urban heat island footprint for grid center point | Double(8,6) | |
UHI capacity | The urban heat island capacity for grid center point | Double(10,6) |
UHI Intensity Zone | Division | UHI Intensity Levels |
---|---|---|
Non-UHI area | 0 | |
Sub-low intensity UHI area | 1 | |
Medium intensity UHI area | 2 | |
Sub-high intensity UHI area | 3 | |
High intensity UHI area | 4 | |
Extra-high intensity UHI area | 5 |
Data | The Background Temperature |
---|---|
Summer of 2014 | 33.66 °C |
Summer of 2015 | 34.37 °C |
Summer of 2016 | 30.24 °C |
Summer of 2017 | 34.35 °C |
Summer of 2018 | 34.28 °C |
Summer of 2019 | 35.04 °C |
Uhi Index | UHI Footprint (km2) | UHI Capacity (km2·°C) | The Growth Rate of UHI Footprint FPGR (km2/Year) | The Growth Rate of UHI Capacity CGR (km2·°C/Year) | |
---|---|---|---|---|---|
Year | |||||
2014 | 86.13 | 323.21 | - | - | |
2015 | 89.86 | 553.62 | 3.73 | 230.41 | |
2016 | 89.53 | 483.77 | −0.33 | −69.85 | |
2017 | 91.35 | 784.94 | 1.82 | 301.17 | |
2018 | 91.86 | 980.85 | 0.51 | 195.91 | |
2019 | 87.95 | 430.31 | −3.91 | −550.54 |
UHI Index | UHI Footprint (km2) | UHI Capacity (km2·°C) | UHI Index | UHI Footprint (km2) | UHI Capacity (km2·°C) | ||
---|---|---|---|---|---|---|---|
Street | Street | ||||||
West Chang’an Street | 3.58 | 21.49 | Tianqiao Street | 2.11 | 14.70 | ||
Xinjiekou Street | 3.62 | 26.41 | Chunshu Street | 1.02 | 6.69 | ||
Yuetan Street | 4.02 | 21.17 | Taoranting Street | 1.78 | 9.61 | ||
Zhanlanlu Street | 5.53 | 34.22 | Guang’anmennei Street | 2.46 | 16.13 | ||
Desheng Street | 3.97 | 23.84 | Niujie Street | 1.43 | 8.65 | ||
Jinrongjie Street | 3.99 | 22.76 | Baizhifang Street | 3.10 | 18.34 | ||
Shichahai Street | 5.17 | 35.85 | Guang’anmenwai Street | 5.37 | 29.39 | ||
Dashilan Street | 1.28 | 12.78 |
UHI Footprint (km2) | The GeoSOT Grid Method | The Gaussian Surface Fitting Method | The Point-by-Point Method | |
---|---|---|---|---|
Year | ||||
2014 | 86.13 | 92.49 | 85.75 | |
2015 | 89.86 | 92.49 | 89.43 | |
2016 | 89.53 | 92.49 | 89.14 | |
2017 | 91.35 | 92.49 | 90.95 | |
2018 | 91.86 | 92.49 | 91.46 | |
2019 | 87.95 | 92.49 | 89.96 |
UHI Capacity (km2·°C) | The GeoSOT Grid Method | The Gaussian Surface Fitting Method | The Point-by-Point Method | |
---|---|---|---|---|
Year | ||||
2014 | 323.21 | 325.33 | 321.84 | |
2015 | 553.62 | 557.00 | 551.17 | |
2016 | 483.77 | 489.74 | 481.44 | |
2017 | 784.94 | 790.02 | 781.43 | |
2018 | 980.85 | 979.88 | 976.48 | |
2019 | 430.31 | 429.10 | 429.69 |
Method | Data | The Average Error of UHI Footprint (km2) | The Average Error of UHI Capacity (km2·°C) | Average Time Cost (ms) |
---|---|---|---|---|
the point-by-point method | The UHI footprint, capacity from 2014 to 2019 summer | - | - | 4952 |
the GeoSOT grid method | The UHI footprint, capacity from 2014 to 2019 summer | 0.67 | 2.44 | 2569 |
the Gaussian surface fitting method | The UHI footprint, capacity from 2014 to 2019 summer | 3.04 | 5.03 | 213 |
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Jiang, J.; Zhou, Y.; Guo, X.; Qu, T. Calculation and Expression of the Urban Heat Island Indices Based on GeoSOT Grid. Sustainability 2022, 14, 2588. https://doi.org/10.3390/su14052588
Jiang J, Zhou Y, Guo X, Qu T. Calculation and Expression of the Urban Heat Island Indices Based on GeoSOT Grid. Sustainability. 2022; 14(5):2588. https://doi.org/10.3390/su14052588
Chicago/Turabian StyleJiang, Jie, Yandi Zhou, Xian Guo, and Tengteng Qu. 2022. "Calculation and Expression of the Urban Heat Island Indices Based on GeoSOT Grid" Sustainability 14, no. 5: 2588. https://doi.org/10.3390/su14052588