基于光谱指数的地表温度与土地利用/土地覆盖关系分析——以昌迪加尔为例

Q4 Computer Science
Yamini Agrawal, None Hina Pandey, None Poonam S. Tiwari
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引用次数: 0

摘要

快速城市化是全球土地利用和土地覆盖变化的主要原因。城市化改变了地表动态,影响地表温度,从而产生城市热岛效应。本文对昌迪加尔市地表温度(LST)与土地利用和土地覆盖(LULC)进行了空间相关分析。利用单窗算法从Landsat-8热波段反演地表温度,显示2016 - 2022年气温上升2.5℃。利用最大似然分类器(MLC)得到的LULC结果表明,建成度增加7.56%,森林覆盖率减少32%。利用Sentinel-2光学波段导出了主要露地温度类别的光谱指数,并利用线性回归分析得到了与地表温度的空间相关性。结果表明,建成度与地表温度呈显著正相关(r=0.988),城市植被覆盖与地表温度呈显著负相关(r=-0.625)。植被和森林覆盖的LST-NDVI、水体的LST-NDWI、建成区的LST-NDBI和裸地的LST-NBLI的平均相关系数分别为-0.3、0.116、0.51和0.392。结果表明,植被和水体对地表温度的上升有减缓作用,而建成区和裸地对地表温度的上升有维持作用。统计分析将有助于决策者和城市规划者预防城市环境和地表动态的进一步退化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analytical study of relation between Land surface temperature and Land Use/Land Cover using spectral indices: A case study of Chandigarh
Rapid urbanization is the major cause for Land Use and Land Cover changes globally. The urbanization alters the land surface dynamics and affects the surface temperature, which gives rise to urban heat island effect. In the present study, spatial correlation analysis has been done between Land Surface Temperature (LST) and Land Use and Land Cover (LULC) for the city of Chandigarh. The LST is retrieved from Landsat-8 thermal band using Mono-Window algorithm and shows 2.5°C increase of temperature from 2016 to 2022. The LULC has been derived using Maximum Likelihood Classifier (MLC) which shows an increase in built-up of 7.56% and decrease in forest cover by 32%. Spectral indices belonging to major LULC classes have been derived using Sentinel-2 optical bands and spatially correlated with LST using linear regression analysis. The results show a strong positive correlation (r=0.988) between built-up and LST and a negative correlation (r=-0.625) between urban vegetation cover and LST. The mean correlation coefficient for LST-NDVI for vegetation and forest cover, LST-NDWI for water bodies, LST-NDBI for built-up and LST-NBLI for bare land is -0.3, 0.116, 0.51 and 0.392 respectively. The results indicate that vegetation and water bodies mitigate the rise of LST, whereas built-up areas and bare lands sustain in the rise of LST. The statistical analysis will be helpful for policy makers and urban planners for prevention of further degradation of urban environment and surface dynamics.
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来源期刊
测绘地理信息
测绘地理信息 Earth and Planetary Sciences-Earth-Surface Processes
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4458
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