| 城市空间格局与热环境响应关系:以合肥市区为例 |
| 摘要点击 1451 全文点击 1053 投稿时间：2022-07-04 修订日期：2022-09-06 |
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| 中文关键词 城市空间格局 热环境 相关性分析 合肥市区 多元线性回归 |
| 英文关键词 urban spatial pattern thermal environment correlation analysis Hefei City multiple linear regression |
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| 中文摘要 |
| 随着城市不断扩张,区域的地表覆盖类型发生转变,大量自然景观被人造景观所替代,环境温度随之上升.研究城市空间格局与热环境之间的响应关系,对于改善生态环境、优化城市空间布局有一定的指导意义.基于合肥市区2020年的Landsat 8系列遥感影像数据及ENVI和ARCGIS等分析平台,采用皮尔逊相关性与剖面线反映两者之间的关联性,再选取关联性最大的3个空间格局组成要素构建多元回归函数,以探究城市空间格局对城市热环境的影响及其作用机制.结果表明:① 2013~2020年间,随着时间推进,合肥市高温区明显增加.对于不同的季节,热岛效应呈现出夏季>秋季>春季>冬季.②中心城区内,建筑占比、建筑高度、不透水占比和人口密度明显高于郊区,而植被覆盖度呈现出郊区高于城区,且在城区主要呈现出点状分布,水体呈不规则分布.③城市高温区主要分布在城区各类开发区内,而城区内其他地方则以中高温及以上温度分区为主,郊区以中低温为主.④各要素的空间格局与热环境之间的皮尔逊系数为正相关的有建筑占比(0.395)、不透水面占比(0.333)、人口密度(0.481)和建筑高度(0.188),负相关的为植被覆盖度(-0.577)和水体占比(-0.384).构建的夏季热环境多元回归函数,包括建筑占比、人口密度和植被覆盖度的系数分别为8.372、0.295和-5.639,常数为38.555.研究结果能够为优化城市空间布局和提高城市居住品质提供参考依据. |
| 英文摘要 |
| With the continuous expansion of cities, the land cover type of the region is transformed, a large number of natural landscapes are replaced by man-made landscapes, and the environmental temperature rises. The study of the response relationship between urban spatial pattern and thermal environment provides some guidance for improving the ecological environment and optimizing the urban spatial layout. Based on the Landsat 8 series remote sensing image data of Hefei City in 2020 and analysis platforms such as ENVI and ARCGIS, Pearson correlation and profile lines were used to reflect the correlation between the two. Then, the three spatial pattern components with the greatest correlation were selected to construct multiple regression functions to investigate the influence of urban spatial pattern on urban thermal environment and its mechanism of action. The results showed that:① the high temperature area of Hefei City increased significantly with the advance of time during 2013-2020. For different seasons, the urban heat island effect showed that summer>autumn>spring>winter. ② In the central urban area, the building occupancy, building height, imperviousness occupancy, and population density were significantly higher than those in the suburbs, whereas fractional vegetation coverage presented a higher suburban than urban area and mainly showed a point distribution in the urban area and an irregular distribution of water bodies. ③ The urban high-temperature zone was mainly distributed in various development zones in urban areas, whereas other places in urban areas were dominated by medium-high temperature and above-temperature zoning, and suburban areas were dominated by medium-low temperature. ④ The Pearson coefficients between the spatial pattern of each element and the thermal environment were positively correlated with the building occupancy (0.395), impervious surface occupancy (0.333), population density (0.481), and building height (0.188) and negatively correlated with fractional vegetation coverage (-0.577) and water occupancy (-0.384). The coefficients of the constructed multiple regression functions, including building occupancy, population density, and fractional vegetation coverage, were 8.372, 0.295, and -5.639 respectively, with a constant of 38.555. The results of this study can provide a reference basis for optimizing urban spatial layouts and improving urban living quality. |
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