The Mitigation Effect of Park Landscape on Thermal Environment in Shanghai City Based on Remote Sensing Retrieval Method
Abstract
:1. Introduction
2. Materials and Methods
2.1. Description of the Study Area
2.2. Data Sources
2.3. Data Processing and Analysis Methods
2.3.1. Land Surface Temperature Retrieval Algorithm
2.3.2. Temperature Division Method
2.3.3. Features Extraction of Park Landscape and Buffer Zone Analysis
2.4. Statistical Analysis
3. Results
3.1. Land Surface Temperature Features of Shanghai and the Parks in 2015 and 2020
3.2. Correlation of Park Landscape Features with Land Surface Temperature within the Parks
3.3. Correlation between Park Cooling Effect and Landscape Metrics
3.4. One Way ANOVA of the Influence of Different Park Groups on the Cooling Effect Indicators
4. Discussion
4.1. Influence of Park Landscape Characteristics on Local Surface Temperature
4.2. Influence of Park Landscape Characteristics on the Surrounding Thermal Environment
4.3. Influence of Different Park Size Groups on the Cooling Effect Indicators
4.4. Limitations
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A
Dependent Variable | (I) Park Group | (J) Park Group | Mean Difference (I–J) | Std. Error | Sig. | 95% Confidence Interval | |
---|---|---|---|---|---|---|---|
Lower Bound | Upper Bound | ||||||
MCD in 2015 | Super large | Large | 174.0506 | 87.6299 | 0.061 | −0.8009 | 1.3652 |
Medium | 364.6714 * | 80.5126 | 0.000 | −1.7420 | 0.2482 | ||
Small | 434.1170 * | 83.5518 | 0.000 | −1.4699 | 0.5954 | ||
Large | Super large | −174.0506 | 87.6299 | 0.061 | −1.3652 | 0.8009 | |
Medium | 190.6208 * | 84.7370 | 0.036 | −2.0763 | 0.0183 | ||
Small | 260.0664 * | 87.6299 | 0.008 | −1.8025 | 0.3637 | ||
Medium | Super large | −364.6714 * | 80.5126 | 0.000 | −0.2482 | 1.7420 | |
Large | −190.6208 * | 84.7370 | 0.036 | −0.0183 | 2.0763 | ||
Small | 69.4456 | 80.5126 | 0.399 | −0.6855 | 1.3047 | ||
Small | Super large | −434.1170 * | 83.5518 | 0.000 | −0.5954 | 1.4699 | |
Large | −260.0664 * | 87.6299 | 0.008 | −0.3637 | 1.8025 | ||
Medium | −69.4456 | 80.5126 | 0.399 | −1.3047 | 0.6855 | ||
MCD in 2020 | Super large | Large | 83.0792 | 91.1201 | 0.373 | −1.6651 | 1.9103 |
Medium | 416.3050 * | 83.7193 | 0.000 | −3.1307 | 0.1542 | ||
Small | 440.9147 * | 86.8796 | 0.000 | −2.2263 | 1.1826 | ||
Large | Super large | −83.0792 | 91.1201 | 0.373 | −1.9103 | 1.6651 | |
Medium | 333.2257 * | 88.1120 | 0.001 | −3.3395 | 0.1178 | ||
Small | 357.8355 * | 91.1201 | 0.001 | −2.4321 | 1.1432 | ||
Medium | Super large | −416.3049 * | 83.7193 | 0.000 | −0.1542 | 3.1307 | |
Large | −333.2257 * | 88.1120 | 0.001 | −0.1178 | 3.3395 | ||
Small | 24.6097 | 83.7193 | 0.772 | −0.6761 | 2.6089 | ||
Small | Super large | −440.9147 * | 86.8796 | 0.000 | −1.1826 | 2.2263 | |
Large | −357.8355 * | 91.1201 | 0.001 | −1.1432 | 2.4321 | ||
Medium | −24.6097 | 83.7193 | 0.772 | −2.6089 | 0.6761 |
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Park Group | Park Name | Area Percentage (%) | Green Coverage (%) | Fuction | Predominant Tree Species and Main Biological Feature | |
---|---|---|---|---|---|---|
Super large ) | Century park | 143.1380 | 0.1156 | 78.36 | Integrated park | Ginkgo biloba L. (deciduous) |
GongQing forest park | 127.0630 | 0.1026 | 85.08 | Specialized park | Ginkgo biloba L.(deciduous + evergreen) | |
Binjiang forest park | 111.8870 | 0.0904 | 95.84 | Specialized park | Acer buergerianum (deciduous) | |
Minhang sports park | 86.1472 | 0.0696 | 86.14 | Integrated park | Ginkgo biloba L. (deciduous + evergreen) | |
Shanghai botanical garden | 77.9539 | 0.0630 | 72.43 | Specialized park | Cinnamomum camphora (evergreen + deciduous) | |
Daningyujinxiang park | 58.0379 | 0.0469 | 79.37 | Integrated park | Ginkgo biloba L. (deciduous + evergreen) | |
Large ) | Huangxing park | 39.7864 | 0.0321 | 72.67 | Integrated park | Ginkgo biloba L. (deciduous) |
Changfeng park | 35.8347 | 0.0289 | 58.86 | Integrated park | Osmanthus fragrans (evergreen) | |
Zhongshan park | 20.7742 | 0.0168 | 87.38 | Integrated park | Platycladus orientalis (evergreen) | |
Luxun park | 20.2863 | 0.0164 | 78.32 | Historic Garden | Acer palmatum (deciduous + evergreen) | |
Jinqiao park | 10.2522 | 0.0083 | 81.46 | Community park | Cedrus deodara ( evergreen + deciduous) | |
Medium ) | Guyi garden | 9.5335 | 0.0077 | 88.83 | Historic Garden | Salix babylonica L. (deciduous) |
Lujiazui central green | 9.2272 | 0.0075 | 83.47 | Integrated park | Magnolia denudata (deciduous + evergreen) | |
Xujiahui park | 9.0939 | 0.0073 | 92.24 | Integrated park | Ginkgo biloba L. (deciduous) | |
Fuxing park | 6.7610 | 0.0055 | 88.65 | Historic Garden | Platanus hispanica (deciduous) | |
Tianshan park | 5.7487 | 0.0046 | 65.83 | Integrated park | Pterocarya stenoptera (deciduous + evergreen) | |
Zuibaichi park | 4.7679 | 0.0039 | 96.81 | Historic Garden | Pseudolarix amabilis (deciduous + evergreen) | |
Gushu park | 4.2421 | 0.0034 | 88.29 | Community park | Ginkgo biloba L. (deciduous) | |
Small ) | Gucheng park | 3.7272 | 0.0030 | 89.73 | Community park | Osmanthus fragrans (evergreen) |
Xianghe park | 3.0011 | 0.0024 | 83.04 | Community park | Cinnamomum contractum (evergreen) | |
Jing’an park | 2.7355 | 0.0022 | 77.84 | Integrated park | Platanus hispanica (deciduous) | |
Shangnan park | 2.6522 | 0.0021 | 91.88 | Community park | Salix babylonica L. (deciduous + evergreen) | |
Jingnan park | 2.5440 | 0.0021 | 95.03 | Community park | Magnolia grandiflora (evergreen + deciduous) | |
Xiangyang park | 2.1324 | 0.0017 | 87.76 | Community park | Prunus serrulata (deciduous + evergreen) |
Classification | Landscape Metrics and Abbreviation | Calculation |
---|---|---|
Landscape composition | Green area (ha), GA | GA = green area of park |
Water area (ha), WA | WA = water area of park | |
Proportion of impermeable layers (%), PIL | PIL = Ai/PA × 100%; Ai = area of impermeable layers (PA-GA-WA) | |
Plaque morphology | Park area (ha), PA | PA = area of park |
Park perimeter (m), PP | PP = perimeter of park | |
Park perimeter-to-area ratio (%), PPAR | PPAR = PP/PA × 100% | |
Park fractal dimension, PFD | D = 2 × ln(PP/4)/ln(PA) [59] |
Classification | Temperature Range in 2015 (°C) | Temperature Range in 2020 (°C) |
---|---|---|
Low temperature | <28.71 | <30.03 |
Middle–low temperature | 28.71–30.60 | 30.03~32.05 |
Middle temperature | 30.60–32.25 | 32.05~34.06 |
Middle–high temperature | 32.25–34.06 | 34.06~36.24 |
High temperature | >34.06 | >36.24 |
Landscape Metrics | In 2015 | In 2020 | ||
---|---|---|---|---|
Pearson Correlation | Sig. | Pearson Correlation | Sig. | |
PA | −0.716 ** | 0.000 | −0.719 ** | 0.000 |
PP | −0.690 ** | 0.000 | −0.677 ** | 0.000 |
PPAR | 0.632 ** | 0.001 | 0.640 ** | 0.001 |
PFD | 0.182 | 0.394 | 0.192 | 0.370 |
GA | −0.722 ** | 0.000 | −0.729 ** | 0.000 |
WA | −0.498 * | 0.013 | −0.532 ** | 0.007 |
PIL | 0.312 | 0.138 | 0.536 ** | 0.007 |
Park Grade | Park Name | In 2015 | In 2020 | ||
---|---|---|---|---|---|
MCD (m) | MCI (°C) | MCD (m) | MCI (°C) | ||
Super large parks ) | Century park | 706.9506 | 1.2782 | 762.3386 | 1.7007 |
GongQing forest park | 795.7450 | 1.3335 | 570.4900 | 0.8273 | |
Binjiang forest park | 1041.7070 | 0.8286 | 1016.1858 | 0.9299 | |
Minhang sports park | 522.2678 | 0.8592 | 861.2296 | 1.4615 | |
Shanghai botanical garden | 634.6422 | 0.8223 | 539.7231 | 1.1805 | |
Daningyujinxiang park | 585.0422 | 1.7656 | 568.6326 | 2.3472 | |
Large parks ) | Huangxing park | 554.9581 | 1.0104 | 633.7859 | 1.7390 |
Changfeng park | 881.0605 | 0.1235 | 881.0605 | 0.5083 | |
Zhongshan park | 412.2149 | 0.0986 | 799.8771 | 0.7355 | |
Luxun park | 381.2560 | 1.5903 | 365.7999 | 2.3829 | |
Jinqiao park | 472.2197 | 1.5060 | 502.9135 | 1.0606 | |
Medium parks ) | Guyi garden | 252.9480 | 1.1000 | 217.5562 | 0.7764 |
Lujiazui central green | 510.3497 | 0.1572 | 527.7217 | 0.3621 | |
Xujiahui park | 393.4313 | 2.1042 | 328.3025 | 2.6251 | |
Fuxing park | 304.8691 | 2.2150 | 283.3706 | 2.9778 | |
Tianshan park | 441.1852 | 2.8666 | 273.8877 | 4.0943 | |
Zuibaichi park | 260.5534 | 3.0442 | 291.7883 | 3.4186 | |
Gushu park | 284.7108 | 1.7763 | 201.6045 | 6.0184 | |
Small parks ) | Gucheng park | 353.0546 | 0.7561 | 338.6038 | 0.4656 |
Xianghe park | 347.0739 | 0.4785 | 339.1409 | 1.0331 | |
Jing’an park | 316.6093 | 0.7609 | 316.6093 | 0.0988 | |
Shangnan park | 197.3022 | 1.9122 | 203.9789 | 3.0141 | |
Jingnan park | 218.6293 | 3.0756 | 225.7952 | 4.3050 | |
Xiangyang park | 248.9833 | 2.5277 | 248.9833 | 2.6617 |
Landscape Metrics | In 2015 | In 2020 | ||||||
---|---|---|---|---|---|---|---|---|
MCD | MCI | MCD | MCI | |||||
Pearson Correlation | Sig. | Pearson Correlation | Sig. | Pearson Correlation | Sig. | Pearson Correlation | Sig. | |
PA | 0.792 ** | 0.000 | −0.267 | 0.207 | 0.715 ** | 0.000 | −0.292 | 0.166 |
PP | 0.805 ** | 0.000 | −0.335 | 0.109 | 0.769 ** | 0.000 | −0.330 | 0.116 |
PPAR | −0.757 ** | 0.000 | 0.392 | 0.059 | −0.733 ** | 0.000 | 0.330 | 0.115 |
PFD | −0.220 | 0.303 | 0.094 | 0.663 | −0.128 | 0.551 | 0.053 | 0.807 |
GA | 0.790 ** | 0.000 | −0.254 | 0.232 | 0.715 ** | 0.000 | −0.287 | 0.173 |
WA | 0.575 ** | 0.003 | −0.215 | 0.313 | 0.549 ** | 0.006 | −0.203 | 0.341 |
PIL | −0.148 | 0.490 | −0.298 | 0.157 | −0.234 | 0.272 | −0.194 | 0.365 |
Sum of Squares | Mean Square | F | Sig. | ||
---|---|---|---|---|---|
MCI in 2015 | Between Groups | 3.721 | 1.240 | 1.687 | 0.202 |
Within Groups | 14.705 | 0.735 | |||
Total | 18.426 | ||||
MCI in 2020 | Between Groups | 10.241 | 3.414 | 1.704 | 0.198 |
Within Groups | 40.061 | 2.003 | |||
Total | 50.301 | ||||
MCD in 2015 | Between Groups | 699,250.864 | 233,083.621 | 11.130 | 0.000 |
Within Groups | 418,854.943 | 20,942.747 | |||
Total | 1,118,105.807 | ||||
MCD in 2020 | Between Groups | 926,578.689 | 308,859.563 | 13.640 | 0.000 |
Within Groups | 452,884.738 | 22,644.237 | |||
Total | 1,379,463.427 |
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Wang, T.; Tu, H.; Min, B.; Li, Z.; Li, X.; You, Q. The Mitigation Effect of Park Landscape on Thermal Environment in Shanghai City Based on Remote Sensing Retrieval Method. Int. J. Environ. Res. Public Health 2022, 19, 2949. https://doi.org/10.3390/ijerph19052949
Wang T, Tu H, Min B, Li Z, Li X, You Q. The Mitigation Effect of Park Landscape on Thermal Environment in Shanghai City Based on Remote Sensing Retrieval Method. International Journal of Environmental Research and Public Health. 2022; 19(5):2949. https://doi.org/10.3390/ijerph19052949
Chicago/Turabian StyleWang, Tian, Hui Tu, Bo Min, Zuzheng Li, Xiaofang Li, and Qingxiang You. 2022. "The Mitigation Effect of Park Landscape on Thermal Environment in Shanghai City Based on Remote Sensing Retrieval Method" International Journal of Environmental Research and Public Health 19, no. 5: 2949. https://doi.org/10.3390/ijerph19052949