The spatiotemporal heterogeneity and driving forces of surfacial thermal environment over an intensive mining region

被引:0
|
作者
Hou, Chun-Hua [1 ,2 ]
Li, Fu-Ping [1 ,2 ,3 ,4 ]
Gu, Hai-Hong [1 ,2 ,3 ,4 ]
He, Bao-Jie [5 ,6 ,7 ]
Ma, Peng-Kun [8 ]
Song, Wen [1 ,9 ]
机构
[1] College of Mining Engineering, North China University of Science and Technology, Tangshan,063210, China
[2] Tangshan Key Laboratory of Resources and Environmental Remote Sensing, Tangshan,063210, China
[3] Hebei Key Laboratory of Mining Development and Security Technology, Tangshan,063210, China
[4] Hebei Industrial Technology Institute of Mine Ecological Remediation, Tangshan,063210, China
[5] School of Architecture and Urban Planning, Chongqing University, Chongqing,400405, China
[6] Key Laboratory of New Technology for Construction of Cities in Mountain Area, Ministry of Education, Chongqing University, Chongqing,400405, China
[7] Faculty of Built Environment, University of New South Wales, Sydney,2052, Australia
[8] Institute of Urban Meteorology, Beijing,100089, China
[9] Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing,100101, China
关键词
Multivariant analysis - Regression analysis - Moisture control - Surface properties - Vegetation - Atmospheric temperature - Soil moisture - Surface measurement;
D O I
暂无
中图分类号
学科分类号
摘要
Based on the Landsat thermal imagery, land surface temperature (LST) of the mining-intensive areas in Manlanzhuang, Qian'an, Hebei Province, China, was retrieved using atmospheric correction method. Meanwhile, the land surface disturbance type and four surface biophysical parameters including Fraction of Photosynthetic Vegetation (fPV), Soil Moisture Monitoring Index (SMMI), Enhanced Bare Soil Index (EBSI) and Normalized Difference Impervious Surface Index (NDISI) were analysed from the perspective of biogeophysical effects. Afterwards, the spatiotemporal heterogeneity of surface thermal environment was quantified and visualised by overlay analysis. To uncover the driving mechanism behind such spatiotemporal heterogeneities, the relationship between the four biophysical parameters and LST was assessed by correlation and regression analysis. The results show that the mining land had the highest LST, characterised as the severest heat island cluster. Surface disturbance types and four surface biophysical parameters drove the spatiotemporal heterogeneity of surface thermal environment, where the LST followed the order of mining land> residential land> cultivated land> forest land> water area. The single factor regression analysis indicates that fPV and SMMI had a significant negative linear relationship with the normalised LST (NLST), while EBSI and NDISI had a significant positive linear relationship with NLST. The multivariate regression analysis indicates that using the four biophysical parameters could holistically characterize spatiotemporal heterogeneity of surface thermal environment and better present the actual relationships between biophysical parameters and NLST. The regression coefficient of SMMI was larger than that of fPV, indicating surface moisture content had a stronger effect on surface temperature reduction. The regression coefficient of EBSI was larger than that of NDISI, indicating bare soil contributed more to surface warming. The findings of this study will provide a quantitative reference for the assessment and optimisation of surface thermal environment in mining-intensive regions. © 2021, Editorial Board of China Environmental Science. All right reserved.
引用
下载
收藏
页码:872 / 882
相关论文
共 31 条
  • [21] Spatiotemporal Changes in and Forces Driving Ozone Concentration in the Beijing-Tianjin-Hebei (Jing-Jin-Ji) Region from 2015 to 2022
    Xiong, Guang-Sen
    Liu, Xue-Zheng
    Li, Yong
    Ren, Yi-Zhuo
    Tang, Quan-Zhong
    Tang, Xi-Wang
    ATMOSPHERE, 2024, 15 (04)
  • [22] Assessing the spatiotemporal variation in anthropogenic heat and its impact on the surface thermal environment over global land areas
    Jin, Kai
    Wang, Fei
    Wang, Shaoxia
    SUSTAINABLE CITIES AND SOCIETY, 2020, 63 (63)
  • [23] Spatial Heterogeneity of Driving Forces in Response to Carbon Emissions from Land Use at County-Level in Beijing-Tianjin-Hebei Region
    Tian, Chao
    Cheng, Linlin
    Yin, Tingting
    POLISH JOURNAL OF ENVIRONMENTAL STUDIES, 2023, 32 (01): : 267 - 279
  • [24] Land cover changes in the Lachuá region, Guatemala: patterns, proximate causes, and underlying driving forces over the last 50 years
    Maura L. Quezada
    Víctor Arroyo-Rodríguez
    Evangelina Pérez-Silva
    T. Mitchell Aide
    Regional Environmental Change, 2014, 14 : 1139 - 1149
  • [25] Land cover changes in the Lachua region, Guatemala: patterns, proximate causes, and underlying driving forces over the last 50 years
    Quezada, Maura L.
    Arroyo-Rodriguez, Victor
    Perez-Silva, Evangelina
    Aide, T. Mitchell
    REGIONAL ENVIRONMENTAL CHANGE, 2014, 14 (03) : 1139 - 1149
  • [26] Study on surface thermal environment differentiation effect in mining intensive area through developing remote sensing assessment model
    Hou Chun-Hua
    Li Fu-Ping
    He Bao-Jie
    Gu Hai-Hong
    Song Wen
    JOURNAL OF INFRARED AND MILLIMETER WAVES, 2020, 39 (05) : 635 - 649
  • [27] Spatiotemporal pattern of Neolithic-Bronze Age settlements and its driving mechanisms in Northern Haidai Region, China: Natural environment, social organization, and subsistence strategies
    Zou, Chunhui
    Mao, Longjiang
    Shan, Siwei
    Mo, Duowen
    QUATERNARY INTERNATIONAL, 2023, 658 : 48 - 59
  • [28] Spatial heterogeneity analysis and driving forces exploring of built-up land development intensity in Chinese prefecture-level cities and implications for future Urban Land intensive use
    Zhang, Pengyan
    Yang, Dan
    Qin, Mingzhou
    Jing, Wenlong
    LAND USE POLICY, 2020, 99
  • [29] Contribution of Spatial Heterogeneity and Temporal-Spatial Change of Ecosystems to the Thermal Environment of Tourist Destinations: A Case Study of Sichuan-Chongqing Region, China
    Chen, Dechao
    Xu, Xinliang
    Jiang, Huailong
    Sun, Zongyao
    Luo, Liu
    Qiao, Zhi
    ADVANCES IN METEOROLOGY, 2020, 2020
  • [30] Changes in Forest Vegetation Carbon Storage and Its Driving Forces in Subtropical Red Soil Hilly Region over the Past 34 Years: A Case Study of Taihe County, China
    Yan, Lingyuan
    Meng, Shengwang
    Yang, Fengting
    Dai, Xiaoqin
    Wang, Huimin
    FORESTS, 2023, 14 (03):