Analysis on Spatiotemporal Pattern of Land Surface Temperature in Kunming City, China

Authors: Jinrui Ren, Li Wu

Abstract:

Anthropogenic activities and changes of underlying surface affect the temporal and spatial distribution of surface temperature in Kunming. Taking Kunming city as the research area, the surface temperature in 2000, 2010 and 2020 as the research object, using ENVI 5.3 and ArcGIS 10.8 as auxiliary tools, and based on the spatial autocorrelation method, this paper devoted to exploring the interactions among the changes of surface temperature, urban heat island effect and land use type, so as to provide theoretical basis and scientific basis for mitigating climate change. The results showed that: (1) The heat island effect was obvious in Kunming City, the high temperature area increased from 604 km2 in 2000 to 1269 km2 in 2020, and the sub-high temperature area reached 1099 km2 in 2020; (2) In terms of space, the spatial distribution of LST was significantly different with the change of underlying surface. The high temperature zone extended in three directions: south, north and east. The overall spatial distribution pattern of LST was high in the east and low in the west. (3) The inter-annual fluctuation of land surface temperature (LST) was large, and the growth rate was faster, from 2000 to 2010. The lowest temperature in 2000 was 13.45 ℃, which raised to 19.71 ℃ in 2010, and the temperature difference in 10 years was 6.26 ℃. (4) The land use/land cover type has a strong effect on the change of LST: the man-made land made a great contribution to the increase of LST, followed by grassland and farmland, while forest and water have a significant cooling effect on LST. To sum up, the variation of surface temperature in Kunming is the result of the interactions of human activities and climate change.

Keywords: Surface temperature, urban heat island effect, land use cover type, spatiotemporal variation.

References:

[1] Y. N. Li, "Discussion on land surface temperature inversion based on Landsat 8 imagery," Journal of Earth Environment, vol. 32, no. 5, pp. 238-239, 2020.
[2] H. F. Guo, C. Zhang, and S. Cao, "Research status of urban heat island effect," Agriculture and Technology, vol. 42, no. 10, pp. 113-115, 2022.
[3] C. B. Chen, J. Peng, and G. Y. Li, "Evaluating ecosystem health in the grasslands of Xinjiang," Arid Zone Research, vol. 39, no. 1, pp. 270-281, 2022.
[4] X. Ren, Z. G. Shi, "Response of global temperature extremes in mid-Holocene: results from MPI-ESM-P experiments," Journal of Earth Environment, vol. 10, no. 5, pp. 465-478, 2019.
[5] Z. Sun, "The Temporal-Spatial Distribution and Driving Mechanism of Changes of Vegetation Carbon Source/Sink in the Three Gorges Reservoir Area," Chongqing University, 2021.
[6] "Key Data Bulletin of the Sixth National Population Census 2010 (No. 1)," Chinese Journal of Family Planning, vol. 19, no. 08, pp. 511-512, 2011.
[7] C. Y. Yin, Y. S. Shi, and H. F. Wang, et al. "Impacts of urban landscape form on thermal environment at multi-spatial levels," Resources and Environment in the Yangtze Basin, vol. 24, no. 1, pp. 97-105, 2015.
[8] W. H. Kuang, "Advance and Future Prospects of Urban Land Use/Cover Change and Ecological Regulation of Thermal Environment," Scientia Geographica Sinica, vol. 38, no. 10, pp. 1643-1652, 2018.
[9] H. W. Liang, Alimujiang Kasmu, H. M. Zhao, and Y. Y. Zhao, "The surface temperature and its influencing factors in Urumqi City based on the geodetector," Journal of Lanzhou University (Natural Sciences), vol. 58, no. 3, pp. 356-363, 2022.
[10] R. Luo, "Towards the Retrieval Methods for Land Surface Temperature in Urban Areas," University of Electronic Science and Technology of China, 2020.
[11] N. Wang, J. Y. Chen, T. He, X. L. Wu, L. Liu, Z. Y. Sun, Z. Qiao, D. R. Han, “Understanding the differences in the effect of urbanization on land surface temperature and air temperature in China: insights from heatwave and non-heatwave conditions,” Environmental Research Letters, vol. 18, no. 10, pp. 4038, 2023.
[12] M. Kim, D. Kim, G. Kim, “Examining the Relationship between Land Use/Land Cover (LULC) and Land Surface Temperature (LST) Using Explainable Artificial Intelligence (XAI) Models: A Case Study of Seoul, South Korea,” International Journal of Environmental Research and Public Health, vol. 19, no. 23, pp. 15926-15926, 2022.
[13] M. He, Y. M. Xu, Y. P. Mo, S. Y. Zhu, “Assessment of heat wave risk in Beijing using multi-source remote sensing data,” Scientia Geographica Sinica, vol. 43, no. 7, pp. 1270-1280, 2023.
[14] Y. Y. Que, X. Y. Hu, S. L. Wang, S. Y. Lin, D. F. Lu, “The spatio-temporal difference between underlying surface parameters and surface temperature: a case study of Poyang Lake basin,” Journal of Hunan City University (Natural Science), vol. 31, no. 4, pp. 36-43, 2022.
[15] H. J. Chen, L. Liu, Z. Y. Zhang, et al. “Spatiotemporal correlation between human activity intensity and surface temperature on the north slope of Tianshan Mountains,” Acta Geographic Sinica, vol. 77, no. 5, pp. 1244-1259, 2022.
[16] S. Buya, C. C. Potjamas, A. O. Benjamin, “Analysis of land surface temperature with land use and land cover and elevation from NASA MODIS satellite data: a case study of Bali, Indonesia,” Environmental Monitoring Assessment, vol. 194, no. 8, pp. 566, 2022.
[17] T. L. Guan, R. H. Wang, C. Li, J. Yao, M. Zhang, J. P. Zhao, "Spatial-temporal characteristics of land surface temperature in Tianshan Mountains area based on MODIS data," Chinese Journal of Applied Ecology, vol. 26, no. 3, pp. 681-688, 2015.
[18] F. F. Zhang, K. Peng, F. Zhang, “Spatial distribution characteristics of land surface temperature and its “source-sink” effect in Yanqi Basin, Xinjiang,” Transactions of the Chinese Society of Agricultural Engineering, vol. 38, no. 16, pp. 153-161, 2022.
[19] E. L. Zhao, F. Deng, Z. Y. Li, P. X. Zheng, F. Qian, Y. Han, “Study on the thermal environment of Wuhan City based on local climate zones,” Resources and Environment in the Yangtze Basin, vol. 32, no. 5, pp. 1030-1041, 2023.
[20] L. G. Kang, S. K. Cao, G. C. Cao, L. Yan, L. X. Chen, W. B. Li, H. R. Zhao, “Spatiotemporal variation of land surface temperature in Qinghai Lake Basin,” Arid Land Geography, vol. 46, no. 7, pp. 1084-1097, 2023.
[21] Y. Luo, W. F. Peng, Y. B. Dong, Y. M. Luo, D. M. Zhang, “Geographical exploration of the spatial pattern of the surface temperature and its influencing factors in western Sichuan Plateau: A case of Xichang City,” Arid Land Geography, vol. 43, no. 3, pp. 738-749, 2020.
[22] J. Shi, X. Y. Lu, X. Chen, “Study on the impact of urbanization and urban heat island effect on net primary productivity in Kunming,” Pratacultural Science, vol. 39, no. 12, pp. 2589-2603, 2022.
[23] Edited by Office of Kunming Local Chronicles Compilation Committee. Kunming Yearbook. 2021, Nationalities Publishing House of Yunnan, 2021.
[24] K. G. Ying, "Kelvin-a versatile and prolific scientist," Physics Teaching, no. 2, 1984.
[25] X. H. Zhang, "Integrate Global Land Cover Products to Refine the Forest Type of Globe Land 30," Beijing University of Civil Engineering and Architecture, 2018.
[26] X. F. Wei, J. P. Wu, "Development and Research of Spatial Autocorrelation Based on ArcGIS," Geomatics & Spatial Information Technology, pp. 672-680, 2004.
[27] W. Zhang, J. G. Jiang, Y. B. Zhu, "Spatial-temporal evolution of urban thermal based on spatial statistical features," Chinese Journal of Applied Ecology, vol. 26, no. 6, pp. 1840-1846, 2015.
[28] P. L. Wang, J. M. Zhang, R. F. Lv "Urban thermal environment pattern with spatial autocorrelation in Lanzhou," Chinese Journal of Ecology, vol. 33, no. 4, pp. 1089-1095, 2014.
[29] X. Y. Chen, P. Lin, "Spatial Autocorrelation Analysis on the Distribution of Mangrove in China," Journal of East China Normal University (Natural Science), no. 3, pp. 104-109, 2000.
[30] B. Meng, J. F. Wang, W. Z. Zhang, X. H. Liu, "Evaluation of Regional Disparity in China Based on Spatial Analysis," Scientia Geographica Sinica, vol. 25, no. 4, pp. 393-400, 2005.
[31] Z. G. Li, M. Y. Wang, J. Q. Niu, et al. "Analysis of the Spatial Pattern Evolution of Cultivated Land in Municipalities Based on Spatial Autocorrelation Analysis—Luoyang City as an Example," Journal of Xinyang Normal University (Natural Science Edition), vol. 34, no. 3, pp. 415-421, 2021.
[32] H. M. Zhou, F. Dong, "Research on Response of Land Use and Surface Temperature in Nan’an District of Chongqing City," Journal of Anhui Agricultural Sciences, vol. 49, no. 15, pp. 79-84, 2021.
[33] J. H. Ye, Y. W. Han, "Spatiotemporal dynamic analysis of surface temperature in Xiongan New Area from 2000 to 2019," Environmental Ecology, vol. 5, no. 2, pp. 5-12, 2023.