| 引用本文: | 侯春华,李富平,何宝杰,马朋坤,宋文,赵菁菁.地表反照率和植被覆盖度对矿区热环境的影响[J].哈尔滨工业大学学报,2022,54(12):117.DOI:10.11918/202007003 |
| HOU Chunhua,LI Fuping,HE Baojie,MA Pengkun,SONG Wen,ZHAO Jingjing.Influence of surface albedo and vegetation fractional coverage on thermal environment of mining area[J].Journal of Harbin Institute of Technology,2022,54(12):117.DOI:10.11918/202007003 |
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| 地表反照率和植被覆盖度对矿区热环境的影响 |
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侯春华，李富平，何宝杰，马朋坤，宋文，赵菁菁
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1.华北理工大学 矿业工程学院, 河北 唐山 063210;2.唐山师范学院 计算机科学系, 河北 唐山 063000;3.重庆大学 建筑城规学院, 重庆 400405;4.澳大利亚新南威尔士大学 建筑环境学院, 澳大利亚 悉尼 2052;5.北京城市气象研究院城市边界层与大气环境研究所, 北京 100089;6.中国科学院地理科学与资源研究所, 北京 100101
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| 摘要: |
| 为分析由于矿产资源的高强度开采导致地表原有植被遭到破坏，使得地表反照率发生改变进而对矿区地表热环境造成的影响。以河北省迁安市马兰庄铁矿为例，利用Landsat遥感影像可见光波段基于统计模型法反演地表反照率，基于NDVI-DFI的像元三分模型反演植被覆盖度，对热红外波段基于辐射传输方程法反演地表温度，借助叠加分析法、相关分析法和回归分析法，定量化和可视化探究了地表热环境时空异质性对光合植被覆盖度和地表反照率变化的响应规律。结果表明：研究区地表热环境空间分布呈现明显的异质性和规律性，高温区主要分布于北部沙河山采场、中部柳河峪排土场和南部未复垦的白马山排土场，中温区主要位于高温区边缘以及其他裸露地表，低温区主要位于北部已复垦尾矿库和已复垦排土场以及境内绿地和水体；光合植被覆盖度和地表反照率的时空变化，导致研究区夏季午间地表热环境异质性较大，3期影像下垫面地表温度均值排序为：矿区采场裸岩>排土场矿渣>复垦植被>水体；光合植被覆盖度和地表温度的回归分析结果表明二者在0.01水平(双侧)呈线性负相关关系(p < 0.01)，说明光合植被覆盖度的增加对地表热环境具有降温效应，决定系数R2分别为0.63、0.55、0.65，由回归系数可知，2000年、2008年和2018年，光合植被覆盖度每增加10%，会使地表温度相应下降0.66、0.74、1.09 ℃；地表反照率和地表温度的回归分析结果表明二者在0.01水平(双侧)呈线性正相关关系(p < 0.01)，说明地表反照率的增加对地表热环境具有增温效应，决定系数R2分别为0.35、0.40、0.48，由回归系数可知，2000年、2008年和2018年，地表反照率每增加10%，会使地表温度相应上升1.09、1.36、1.76 ℃。研究结果将对矿区地表热环境异质性的评估和优化提供定量参考依据。 |
| 关键词: 遥感 地表反照率 光合植被覆盖度 地表温度 矿区 |
| DOI：10.11918/202007003 |
| 分类号:X87 |
| 文献标识码:A |
| 基金项目:河北省重点研发计划(19224204D); 河北省高等学校青年拔尖人才计划(BJ2014029);唐山市科学技术研究与发展计划重点项目(19150247E); 唐山市科技创新团队培养计划(19130206C); 唐山市科技研发平台培养计划(2020TS003b) |
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| Influence of surface albedo and vegetation fractional coverage on thermal environment of mining area |
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Chunhua HOU1,2, Fuping LI1, Baojie HE3,4, Pengkun MA5, Wen SONG1,6, Jingjing ZHAO1
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1.College of Mining Engineering, North China University of Science and Technology, Tangshan 063210, Hebei, China;2.Department of Computer Science, Tangshan Normal University, Tangshan 063000, Hebei, China;3.Faculty of Architecture and Urban Planning, Chongqing University, Chongqing 400405, China;4.Faculty of Built Environment, University of New South Wales, Sydney 2052, Australia;5.Institute of Urban Boundary Layer and Atmospheric Environment, Institute of Urban Meteorology, CMA, Beijing 100089, China;6.Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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| Abstract: |
| The influence of the changes in surface albedo on the thermal environment of the mining area due to the destruction of the original vegetation caused by the high-intensity mining of mineral resources was analyzed. Taking Malanzhuang Iron Mine in Qian'an city of Hebei province as an example, the statistical model method was adopted to retrieve the surface albedo based on the visible light band of Landsat remote sensing image, and the pixel trisection model was used to retrieve the vegetation fractional coverage based on NDVI-DFI. By means of radiative transfer equation method, the land surface temperature (LST) was retrieved based on the thermal infrared band of Landsat remote sensing image. With the aid of superposition analysis method, correlation analysis method, and regression analysis method, the response of spatiotemporal heterogeneity of surface thermal environment to the changes in photosynthetic vegetation coverage (fPV) and surface albedo was quantitatively and visually explored. Results showed that the spatial distribution of surface thermal environment in the study area showed obvious heterogeneity and regularity. The high temperature zone was mainly distributed in the northern Shaheshan stope, central Liuheyu dump, and the unreclaimed Baimashan dump in the south. The moderate temperature zone was mainly located at the edge of the high temperature zone and other bare surfaces. The low temperature zone was mainly located in the northern reclaimed tailings pond and reclaimed waste dump, as well as the green land and water bodies in the area. The spatiotemporal variation of photosynthetic vegetation coverage and surface albedo resulted in a large heterogeneity of the surface thermal environment during the summer midday in the study area. The mean surface temperature of underlying surface in the third phase of the image was ranked as follows: mining area bare rock > dump slag > reclamation vegetation > water body. The regression analysis results showed that fPV at 0.01 level (double sides) had a negative linear correlation with LST (p < 0.01), indicating that the increase in fPV has a cooling effect on surface thermal environment, and the determination coefficients (R2)were 0.63, 0.55, and 0.65, respectively. According to the regression coefficient, in 2000, 2008, and 2018, for every 10% increase in fPV, LST decreased by 0.66, 0.74, and 1.09 ℃. The regression analysis results showed that albedo at 0.01 level (double sides) had a positive linear correlation with LST (p < 0.01), indicating that the increase in albedo has a warming effect on surface thermal environment, and the determination coefficients (R2)were 0.35, 0.40, and 0.48, respectively. According to the regression coefficient, in 2000, 2008, and 2018, every 10% increase in albedo led to the increase in LST by 1.09, 1.36, and 1.76 ℃. The research results will provide a quantitative reference for the evaluation and optimization of the surface thermal environment heterogeneity in mining area. |
| Key words: remote sensing surface albedo fractional cover of photosynthetic vegetation land surface temperature mining area |
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