Correlation Between Surface Temperature and Population Density In Xiong'an New Area Based on Nightlight Remote Sensing And Landsat8 Data
DOI:
https://doi.org/10.54097/hset.v59i.10045Keywords:
Xiong'an New Area; Nighttime light remote sensing; Surface temperature inversion; Grid.Abstract
Xiong'an New Area was established in 2017. With the development of the city, the urban surface temperature has also changed. Taking Xiong'an New Area as the study area, the distribution of population density in the study area was simulated based on the night light value of noctilucent remote sensing data, and the land surface temperature in the study area was retrieved by Landsat8 image. Additionally, the study area's land surface temperature and population density's temporal and spatial variation characteristics were examined. The influence before and after development was also extracted, and the correlation between them was also analyzed. According to the results, the surface temperature in the study area is rising, and it is characterized with a heat island effect. At the same time, there is a positive correlation between population density and temperature, and population density is one of the important factors that affect the urban temperature change. The development of this study is conducive to improving people's quality of life and the distribution of urbanization resources.
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Guo Hengliang, Feng Zhenzhen, He Xiaohui, Tian Zhihui, Qiao Baojin. Analysis of the influence of land cover and population density changes on urban land surface temperature-taking Zhengzhou as an example [J]. Journal of Inner Mongolia Normal University (Chinese version of natural science), 2019,48(04):298-306.
Zhang Lilong. Study on the impact of urban population density on economic growth [D]. Jinan University, 2019.
Liu Xinxin, Chen Zhuo, Liang Jiyue, Yan Jiale, Gao Zilong, Cui Zhuangjie. Study on the relationship between urban expansion and heat island effect in Taiyuan [J]. Henan Science and Technology, 2021,40(33):126-129.
Zhuo Li, Chen Jin, Shi Peijun, Gu Zhihui, Fan Yida, Yi Zhi Jun Ming. Simulation of population density in China based on night lighting data [J]. Journal of Geography, 2005,(02):266-276.
Daly C. Guidelines for assessing the suitability of spatial climate data sets [J]. International Journal of Climatology, 2010, 26(6): 707-721.
Gao Zhen, Ye Xueyi, Zhou Tianqi, et al. Underwater acoustic data visualization algorithm based on inverse distance weighted interpolation [J]. Computer Engineering, 2015, 41(9): 266-270, 275.
Fan Shengnong, Li Huadong, Wang Shuoheng, Tan Mengyi, Meng Xin, Ge Meihong, Lin Dian. Prediction of spatial distribution of soil nutrients in Huolong orchard in Hainan Province based on IDW and factor analysis [J]. Journal of Southwest Agriculture, 1-12[2023-02-02].
He Hao, Zhang Yun, Tang Zhi, Huang Jing, Ding Yue. Improvement of land surface emissivity estimation method in Landsat8 thermal infrared band [J]. Journal of Anhui Normal University (Natural Science Edition), 2020,43(05):475-482.
Zhou Siyan, Tan Yongbin, Hou Mengfei, Ai Jinquan, Zhang Zezhi, Zhu Shangjun. Correlation analysis between population density and surface temperature in Changsha-Zhuzhou-Xiangtan area based on luminous remote sensing data [J]. Jiangxi Science, 2021,39(01):105-110.
A method of population density inversion based on night lighting data [P]. China patent: cn104809572a.2015.4.27.
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