Analysis of the spatiotemporally varying effects of urban spatial patterns on land surface temperatures
Urban heat islands (UHIs) are a worldwide phenomenon that have many ecological and social consequences. It has become increasingly important to examine the relationships between land surface temperatures (LSTs) and all related factors. This study analyses Landsat data, spatial metrics, and a geograp...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Vilnius Gediminas Technical University
2018-10-01
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| Series: | Journal of Environmental Engineering and Landscape Management |
| Subjects: | |
| Online Access: | https://journals.vgtu.lt/index.php/JEELM/article/view/5378 |
| _version_ | 1818563275483250688 |
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| author | Cheng Li Jie Zhao Nguyen Xuan Thinh Wenfu Yang Zhen Li |
| author_facet | Cheng Li Jie Zhao Nguyen Xuan Thinh Wenfu Yang Zhen Li |
| author_sort | Cheng Li |
| collection | DOAJ |
| description | Urban heat islands (UHIs) are a worldwide phenomenon that have many ecological and social consequences. It has become increasingly important to examine the relationships between land surface temperatures (LSTs) and all related factors. This study analyses Landsat data, spatial metrics, and a geographically weighted regression (GWR) model for a case study of Hangzhou, China, to explore the correlation between LST and urban spatial patterns. The LST data were retrieved from Landsat images. Spatial metrics were used to quantify the urban spatial patterns. The effects of the urban spatial patterns on LSTs were further investigated using Pearson correlation analysis and a GWR model, both at three spatial scales. The results show that the LST patterns have changed significantly, which can be explained by the concurrent changes in urban spatial patterns. The correlation coefficients between the spatial metrics and LSTs decrease as the spatial scale increases. The GWR model performs better than an ordinary least squares analysis in exploring the relationship of LSTs and urban spatial patterns, which is indicated by the higher adjusted R2 values, lower corrected Akaike information criterion and reduced spatial autocorrelations. The GWR model results indicate that the effects of urban spatial patterns on LSTs are spatiotemporally variable. Moreover, their effects vary spatially with the use of different spatial scales. The findings of this study can aid in sustainable urban planning and the mitigation the UHI effect. |
| first_indexed | 2024-12-14T01:14:33Z |
| format | Article |
| id | doaj.art-45b7ace1174442ef9e4fa4f93fcd80b0 |
| institution | Directory Open Access Journal |
| issn | 1648-6897 1822-4199 |
| language | English |
| last_indexed | 2024-12-14T01:14:33Z |
| publishDate | 2018-10-01 |
| publisher | Vilnius Gediminas Technical University |
| record_format | Article |
| series | Journal of Environmental Engineering and Landscape Management |
| spelling | doaj.art-45b7ace1174442ef9e4fa4f93fcd80b02022-12-21T23:22:37ZengVilnius Gediminas Technical UniversityJournal of Environmental Engineering and Landscape Management1648-68971822-41992018-10-0126310.3846/jeelm.2018.5378Analysis of the spatiotemporally varying effects of urban spatial patterns on land surface temperaturesCheng Li0Jie Zhao1Nguyen Xuan Thinh2Wenfu Yang3Zhen Li4Department of Geo-Information Science, School of Resources and Geosciences, China University of Mining and Technology, Daxue Road 1, 221116 Xuzhou, Jiangsu, ChinaHuaihai Inistitute of Development, Jiangsu Normal University, Heping road 57, 221009 Xuzhou, Jiangsu, ChinaDepartment of Spatial Information Management and Modeling, Spatial Planning Faculty, TU Dortmund University, August-Schmidt-Str 10, 44227, Dortmund, GermanyShanxi Coal Geology Geophysical Surveying Exploration Institute, Yingbinxijie 380, 030600 Jinzhong, Shanxi, ChinaShanxi Coal Geology Geophysical Surveying Exploration Institute, Yingbinxijie 380, 030600 Jinzhong, Shanxi, ChinaUrban heat islands (UHIs) are a worldwide phenomenon that have many ecological and social consequences. It has become increasingly important to examine the relationships between land surface temperatures (LSTs) and all related factors. This study analyses Landsat data, spatial metrics, and a geographically weighted regression (GWR) model for a case study of Hangzhou, China, to explore the correlation between LST and urban spatial patterns. The LST data were retrieved from Landsat images. Spatial metrics were used to quantify the urban spatial patterns. The effects of the urban spatial patterns on LSTs were further investigated using Pearson correlation analysis and a GWR model, both at three spatial scales. The results show that the LST patterns have changed significantly, which can be explained by the concurrent changes in urban spatial patterns. The correlation coefficients between the spatial metrics and LSTs decrease as the spatial scale increases. The GWR model performs better than an ordinary least squares analysis in exploring the relationship of LSTs and urban spatial patterns, which is indicated by the higher adjusted R2 values, lower corrected Akaike information criterion and reduced spatial autocorrelations. The GWR model results indicate that the effects of urban spatial patterns on LSTs are spatiotemporally variable. Moreover, their effects vary spatially with the use of different spatial scales. The findings of this study can aid in sustainable urban planning and the mitigation the UHI effect.https://journals.vgtu.lt/index.php/JEELM/article/view/5378land surface temperatureurban spatial patterngeographically weighted regressionspatiotemporally heterogeneityscale effect |
| spellingShingle | Cheng Li Jie Zhao Nguyen Xuan Thinh Wenfu Yang Zhen Li Analysis of the spatiotemporally varying effects of urban spatial patterns on land surface temperatures Journal of Environmental Engineering and Landscape Management land surface temperature urban spatial pattern geographically weighted regression spatiotemporally heterogeneity scale effect |
| title | Analysis of the spatiotemporally varying effects of urban spatial patterns on land surface temperatures |
| title_full | Analysis of the spatiotemporally varying effects of urban spatial patterns on land surface temperatures |
| title_fullStr | Analysis of the spatiotemporally varying effects of urban spatial patterns on land surface temperatures |
| title_full_unstemmed | Analysis of the spatiotemporally varying effects of urban spatial patterns on land surface temperatures |
| title_short | Analysis of the spatiotemporally varying effects of urban spatial patterns on land surface temperatures |
| title_sort | analysis of the spatiotemporally varying effects of urban spatial patterns on land surface temperatures |
| topic | land surface temperature urban spatial pattern geographically weighted regression spatiotemporally heterogeneity scale effect |
| url | https://journals.vgtu.lt/index.php/JEELM/article/view/5378 |
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