Relationship between Urban Tree Canopy Cover on Thermal Environment in Yongping County
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Abstract
Based on the remote sensing image data to decipher the land cover type, the surface temperature of the study area was obtained by surface temperature inversion, and the sample method was used to obtain the information of community characteristics, and the area, perimeter, and shape indices of extra-large and giant forest canopy patches were used as the independent variables, and the rate of cooling was used as the dependent variable, and Pearson correlation and regression analyses were performed, so as to investigate the correlation between urban forest canopy cover and the thermal environment in Yongping County. The results showed that:the area of impervious surface> the area of forest tree canopy covers> the area of water body> the area of bare land> the area of farmland in the study area, the impervious surface accounted for 67.89% of the whole area of the study area, and the forest tree canopy cover accounted for 20.39%, and the forest tree canopy cover with larger area was mainly distributed in the subsidiary green space and protective green space, and the canopy cover area of the green space in the park was relatively small. The surface temperature varies with the characteristics of forest tree canopy cover patches, and the change of the area has a greater influence on the surface temperature, while small patches with small area but large number and high degree of connection and aggregation can also influence the surface temperature. Forest canopy cover showed low temperatures in dense buildings, and water bodies showed stable low temperatures, indicating that both forest canopy cover and water bodies has good cooling effects.The cooling effect of community characteristics is shown as tree-grass>tree-shrub-grass>tree-shrub vegetation type, evergreen>broadleaf species, and the community with uniform weighting of vegetation structure has better cooling effect. There are seasonal differences in the correlation between forest canopy cover and thermal environment, with correlation weights of fall>summer>spring>winter, and the correlation between the spot-fast characteristics of forest canopy cover and the cooling rate is area>perimeter≈shape index. In the future, priority can be given to optimizing the urban riverfront green space in the process of urban construction, increasing the area covered by the canopy of trees in the riverfront green space, replanting tall trees, and focusing on the regulation of tree species, so as to improve the urban thermal environment.
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