Spatio−Temporal Changes and Key Driving Factors of Urban Green Space Configuration on Land Surface Temperature

Junda Huang; Xinghao Lu; Yuncai Wang

doi:10.3390/f15050812

journal article Open Access May 04, 2024

Spatio−Temporal Changes and Key Driving Factors of Urban Green Space Configuration on Land Surface Temperature

Junda Huang Xinghao Lu

Yuncai Wang

Forests Vol. 15 No. 5 pp. 812 · MDPI AG

View at Publisher Save 10.3390/f15050812

Abstract

Changes in land cover by rapid urbanization have diminished the cooling effect of urban green spaces (UGS), exacerbating the upward trend of land surface temperature (LST). A thorough and precise understanding of the spatio-temporal characteristics of UGS and LST is essential for mitigating localized high temperatures in cities. This study identified the spatio-temporal changes in UGS configuration and LST in Shanghai from 2003 to 2022. The correlation between UGS configuration and LST was explored using spatial autocorrelation analysis and causal inference. The results show that (1) the high-temperature space had grown from 721 km2 in 2003 to 3059 km2 in 2022; (2) in suburbs, the largest area of UGS tended to decrease, while the number of patches tended to increase, indicating a distinct feature of suburbanization; (3) changes in the largest area of UGS had more significant spatial correlation, indicating that urban sprawl primarily impacts large UGSs; and (4) compared to the number and shape of UGS, changes in the largest area are the key factor influencing regional LST. These findings enrich the knowledge of the spatio−temporal relationship between the UGS configuration and its cooling effect in urbanization, offering valuable insights for building cooler cities.

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References

89

[1]

Luqman "On the Impact of Urbanisation on CO2 Emissions" npj Urban. Sustain. (2023) 10.1038/s42949-023-00084-2

[2]

Global Consequences of Land Use

Jonathan A. Foley, Ruth DeFries, Gregory P. Asner et al.

Science 2005 10.1126/science.1111772

[3]

A review on the generation, determination and mitigation of Urban Heat Island

Ahmed Memon RIZWAN, Leung Y.C. DENNIS, Chunho LIU

Journal of Environmental Sciences 2008 10.1016/s1001-0742(08)60019-4

[4]

Cai "The Surface Urban Heat Island Effect Decreases Bird Diversity in Chinese Cities" Sci. Total Environ. (2023) 10.1016/j.scitotenv.2023.166200

[5]

Bertil "Heat Wave Impact on Morbidity and Mortality in the Elderly Population: A Review of Recent Studies" Maturitas (2011) 10.1016/j.maturitas.2011.03.008

[6]

Tsekeri "On the Association of Ambient Temperature and Elderly Mortality in a Mediterranean Island—Crete" Sci. Total Environ. (2020) 10.1016/j.scitotenv.2020.139843

[7]

Calice "Urban Heat Island Effect on the Energy Consumption of Institutional Buildings in Rome" IOP Conf. Ser. Mater. Sci. Eng. (2017) 10.1088/1757-899x/245/8/082015

[8]

Yang "The Assessment of Cooling Capacity of Blue-Green Spaces in Rapidly Developing Cities: A Case Study of Tianjin’s Central Urban Area" Sustain. Cities Soc. (2023) 10.1016/j.scs.2023.104918

[9]

Improving City Vitality through Urban Heat Reduction with Green Infrastructure and Design Solutions: A Systematic Literature Review

Helen Elliott, Christine Eon, Jessica Breadsell

Buildings 10.3390/buildings10120219

[10]

Global covariation of carbon turnover times with climate in terrestrial ecosystems

Nuno Carvalhais, Matthias Forkel, Myroslava Khomik et al.

Nature 2014 10.1038/nature13731

[11]

Borna, R., Roshan, G., Moghbel, M., Szabó, G., Ata, B., and Attia, S. (2023). Mitigation of Climate Change Impact on Bioclimatic Conditions Using Different Green Space Scenarios: The Case of a Hospital in Gorgan Subtropical Climates. Forests, 14. 10.3390/f14101978

[12]

Lehnert "The Role of Blue and Green Infrastructure in Thermal Sensation in Public Urban Areas: A Case Study of Summer Days in Four Czech Cities" Sustain. Cities Soc. (2021) 10.1016/j.scs.2020.102683

[13]

Bridging landscape ecology and urban science to respond to the rising threat of mosquito-borne diseases

Pallavi A. Kache, Mauricio Santos-Vega, Anna M. Stewart-Ibarra et al.

Nature Ecology & Evolution 2022 10.1038/s41559-022-01876-y

[14]

Soler "Combined Effects of Tree Canopy Composition, Landscape Location, and Growing Season on Nothofagus Forest Seeding Patterns in Southern Patagonia" For. Ecol. Manag. (2023) 10.1016/j.foreco.2022.120708

[15]

Alonzo "Spatial Configuration and Time of Day Impact the Magnitude of Urban Tree Canopy Cooling" Environ. Res. Lett. (2021) 10.1088/1748-9326/ac12f2

[16]

Paschalis "Urban Forests as Main Regulator of the Evaporative Cooling Effect in Cities" AGU Adv. (2021) 10.1029/2020av000303

[17]

Yang "Influence of Urban Morphological Characteristics on Thermal Environment" Sustain. Cities Soc. (2021) 10.1016/j.scs.2021.103045

[18]

Yu "Variations in Land Surface Temperature and Cooling Efficiency of Green Space in Rapid Urbanization: The Case of Fuzhou City, China" Urban For. Urban Green. (2018) 10.1016/j.ufug.2017.11.008

[19]

Peng "Urban Thermal Environment Dynamics and Associated Landscape Pattern Factors: A Case Study in the Beijing Metropolitan Region" Remote Sens. Environ. (2016) 10.1016/j.rse.2015.11.027

[20]

Jaworek-Jakubska, J., Filipiak, M., Michalski, A., and Napierała-Filipiak, A. (2020). Spatio-Temporal Changes of Urban Forests and Planning Evolution in a Highly Dynamical Urban Area: The Case Study of Wrocław, Poland. Forests, 11. 10.3390/f11010017

[21]

Wang "Spatial-Temporal Patterns of Urban Expansion by Land Use/Land Cover Transfer in China" Ecol. Indic. (2023) 10.1016/j.ecolind.2023.111009

[22]

Herold "The Role of Spatial Metrics in the Analysis and Modeling of Urban Land Use Change" Comput. Environ. Urban Syst. (2005) 10.1016/j.compenvurbsys.2003.12.001

[23]

Wang "Quantifying and Characterizing the Dynamics of Urban Greenspace at the Patch Level: A New Approach Using Object-Based Image Analysis" Remote Sens. Environ. (2018) 10.1016/j.rse.2017.10.039

[24]

Li "Landscape Metrics in Assessing How the Configuration of Urban Green Spaces Affects Their Cooling Effect: A Systematic Review of Empirical Studies" Landsc. Urban Plan. (2023) 10.1016/j.landurbplan.2023.104842

[25]

Yi "Quantitative Analysis and Prediction of Urban Heat Island Intensity on Urban-Rural Gradient: A Case Study of Shanghai" Sci. Total Environ. (2022) 10.1016/j.scitotenv.2022.154264

[26]

Li "Discrepant Impacts of Land Use and Land Cover on Urban Heat Islands: A Case Study of Shanghai, China" Ecol. Indic. (2014) 10.1016/j.ecolind.2014.08.015

[27]

Chen "Surface Heat Island in Shanghai and Its Relationship with Urban Development from 1989 to 2013" Adv. Meteorol. (2015)

[28]

(2024, February 27). Climate Change: Global Temperature|NOAA Climate.Gov, Available online: http://www.climate.gov/news-features/understanding-climate/climate-change-global-temperature.

[29]

Chu, W., Qiu, S., and Xu, J. (2016). Temperature Change of Shanghai and Its Response to Global Warming and Urbanization. Atmosphere, 7. 10.3390/atmos7090114

[30]

Liang "The 2022 Extreme Heatwave in Shanghai, Lower Reaches of the Yangtze River Valley: Combined Influences of Multiscale Variabilities" Adv. Atmos. Sci. (2024) 10.1007/s00376-023-3007-8

[31]

Lee, P.S.-H., and Park, J. (2020). An Effect of Urban Forest on Urban Thermal Environment in Seoul, South Korea, Based on Landsat Imagery Analysis. Forests, 11. 10.3390/f11060630

[32]

McGarigal, K. (1995). FRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structure, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. USDA Forest Service General Technical Report PNW-351. 10.2737/pnw-gtr-351

[33]

Dadashpoor "Land Use Change, Urbanization, and Change in Landscape Pattern in a Metropolitan Area" Sci. Total Environ. (2019) 10.1016/j.scitotenv.2018.11.267

[34]

Cheung "Landscape Structure and Dynamics on the Qinghai-Tibetan Plateau" Ecol. Model. (2016) 10.1016/j.ecolmodel.2016.07.015

[35]

Tannier "Defining and Characterizing Urban Boundaries: A Fractal Analysis of Theoretical Cities and Belgian Cities" Comput. Environ. Urban Syst. (2013) 10.1016/j.compenvurbsys.2013.07.003

[36]

A land use change model: Integrating landscape pattern indexes and Markov-CA

Xin Yang, Xin-Qi Zheng, Rui Chen

Ecological Modelling 2014 10.1016/j.ecolmodel.2014.03.011

[37]

Zhang, Y., Wang, S., and Han, X. (2023). Spatial–Temporal Dynamics of Forest Extent Change in Southwest China in the Recent 20 Years. Forests, 14. 10.3390/f14071378

[38]

Shohan "Spatiotemporal Assessment of the Nexus between Urban Sprawl and Land Surface Temperature as Microclimatic Effect: Implications for Urban Planning" Environ. Sci. Pollut. Res. (2024) 10.1007/s11356-024-33091-6

[39]

Gonzalez "Relative Contribution of Edge and Interior Zones to Patch Size Effect on Species Richness: An Example for Woody Plants" For. Ecol. Manag. (2010) 10.1016/j.foreco.2009.10.010

[40]

Das "Measuring Moran’s I in a Cost-Efficient Manner to Describe a Land-Cover Change Pattern in Large-Scale Remote Sensing Imagery" IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. (2017) 10.1109/jstars.2017.2660766

[41]

Read "Spatial Methods for Characterising Land Cover and Detecting Land-Cover Changes for the Tropics" Int. J. Remote Sens. (2002) 10.1080/01431160110106140

[42]

Anselin, L., and Syabri, I. (2002, January 22). Visualizing Multivariate Spatial Correlation with Dynamically Linked Windows. Proceedings of the Specialist Meeting on New Tools for Spatial Data Analysis, Santa Barbara, CA, USA.

[43]

Bivand "Comparing Implementations of Global and Local Indicators of Spatial Association" Test (2018) 10.1007/s11749-018-0599-x

[44]

Song "Unlocking the Spatial Heterogeneous Relationship between Per Capita GDP and Nearby Air Quality Using Bivariate Local Indicator of Spatial Association" Resour. Conserv. Recycl. (2020) 10.1016/j.resconrec.2020.104880

[45]

Peters, J., Janzing, D., and Schlkopf, B. (2017). Elements of Causal Inference: Foundations and Learning Algorithms, The MIT Press.

[46]

Ma "Data-Based Prediction and Causality Inference of Nonlinear Dynamics" Sci. China Math. (2018) 10.1007/s11425-017-9177-0

[47]

Gao "Causal Inference from Cross-Sectional Earth System Data with Geographical Convergent Cross Mapping" Nat. Commun. (2023) 10.1038/s41467-023-41619-6

[48]

Team, R. (2024, April 09). R: A Language and Environment for Statistical Computing. MSOR Connections [Internet], Available online: https://www.semanticscholar.org/paper/R%3A-A-language-and-environment-for-statistical-Team/659408b243cec55de8d0a3bc51b81173007aa89b.

[49]

Awasthi "Retrospection of Heatwave and Heat Index" Theor. Appl. Clim. (2022) 10.1007/s00704-021-03854-z

[50]

You "Are New Towns Prone to Urban Heat Island Effect? Implications for Planning Form and Function" Sustain. Cities Soc. (2023) 10.1016/j.scs.2023.104939

Showing 50 of 89 references

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Details

Published: May 04, 2024
Vol/Issue: 15(5)
Pages: 812
License: View

Authors

J

Junda Huang

Department of Landscape Architecture, College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China

X

Xinghao Lu

Department of Landscape Architecture, College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China

Y

Yuncai Wang

Center of Ecological Planning and Environment Effects Research, Joint Laboratory of Ecological Urban Design, Shanghai 200092, China

Funding

the National Natural Science Foundation of China Award: 52238003

Cite This Article

Junda Huang, Xinghao Lu, Yuncai Wang (2024). Spatio−Temporal Changes and Key Driving Factors of Urban Green Space Configuration on Land Surface Temperature. Forests, 15(5), 812. https://doi.org/10.3390/f15050812

Spatio−Temporal Changes and Key Driving Factors of Urban Green Space Configuration on Land Surface Temperature

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