| 793 | 9 | 119 |
| 下载次数 | 被引频次 | 阅读次数 |
建设强度的变化会对城市热岛效应产生不同方向或强度的影响。选用Landsat-8遥感影像,以地表温度热岛强度(简称为热岛强度)作为城市热岛效应的量化标准,以片区和连续序列空间尺度作为基本分析单元,使用空间自相关方法和空间自回归模型代替经典统计学方法,对热岛强度空间分布特性进行研究,探究热岛强度与建设强度的空间响应机制;并基于分析结果对研究区域进行分区,探究合理的城市热岛效应缓解措施。结果表明:(1)研究区域热岛强度具有显著的空间自相关性,且随着分析尺度的精确自相关性愈发明显;“热点”区域主要分布在西南部的工厂密集区和中部的城市中心区,“冷点”区域则以五象岭和青秀山风景保护区为主。(2)建设强度直接或间接影响了城市热岛效应的形成和演化;100 m规则格网尺度的空间特性表现最显著,可作为常用分析尺度;作为回归模型的解释变量,各建设强度指标的显著性在不同尺度呈现较大差异。(3)空间误差模型的拟合效果优于普通最小二乘法模型,空间尺度越精确、模型的拟合效果越好。(4)基于热岛强度“热点”和“冷点”区域进行进一步研究,得出基于不同分区的缓解思路和连接破碎化“冷点”区域,打造城市“冷廊”等热岛缓解措施。
Abstract:The change of construction intensity can have impact on urban heat island effect direction or intensity. This paper selected Landsat 8remote sensing images, took the surface urban heat island intensity(referred to as heat island intensity) as urban heat island effect quantitative standard, and area and continuous sequence scale as basic analysis unit. This paper used spatial autocorrelation methods and spatial autoregressive models instead of classical statistical methods to study the spatial distribution characteristics of urban heat island intensity, explored the spatial response mechanism of urban heat island intensity and construction intensity, and partitioned the study area based on the analysis results to explore reasonable measures to mitigate urban heat island effect. The results show that:(1) the surface urban heat island intensity of the study area has significant spatial autocorrelation. With more precise autocorrelation analysis scale, the autocorrelation becomes more obvious. The "hot spots" areas are mainly distributed in the factory-intensive areas in the southeast and the central urban center district, and the "cold spot" areas are mainly in Wuxiangling and Qingxiu Mountain Scenic Reserve.(2) The construction intensity directly or indirectly affects the urban heat island effect formation and function. As the regression model explanatory variables, the construction intensity indicator significance and correlation vary greatly at different scales.(3) The fitting effect of the spatial error model is better than that of the ordinary least squares model. The more accurate the spatial scale, the better the model fitting effect.(4) Based on further research based on the urban heat island intensity in the "hot spots" and "cold spots" areas, the mitigation ideas based on different city districts, construction of urban "cold corridors" by connecting fragmented "cold spots" areas and other heat island mitigation measures were proposed.
[1] Gallo K P,Mcnab A L,Karl T R,et al. The Use of a Vegetation Index for Assessment of the Urban Heat Island Effect[J]. International Journal of Remote Sensing,1993,14(11):2 223-2 230
[2]张光智,徐祥德,王继志,等.北京及周边地区城市尺度热岛特征及其演变[J].应用气象学报,2002(增刊):43-50
[3]覃盟琳,宋文博,宋苑震,等.北部湾城市群热岛空间特征及演变趋势研究[J].安全与环境学报,2020,20(4):1 557-1 566
[4]王植,董斌,陈炟君.基于Landsat的沈阳城市热岛效应与地表参数变化分析[J].测绘与空间地理信息,2018,41(10):4-7
[5] Hart M A,Sailor D J. Quantifying the Influence of Land-Use and Surface Characteristics on Spatial Variability in the Urban Heat island[J]. Theoretical and Applied Climatology,2009,95(3-4):397-406
[6]韩贵锋,蔡智,谢雨丝,等.城市建设强度与热岛的相关性:以重庆市开州区为例[J].土木建筑与环境工程,2016,38(5):138-147
[7]江颖慧,焦利民,张博恩.城市地表温度与NDVI空间相关性的尺度效应[J].地理科学进展,2018,37(10):1 362-1 370
[8]王雪,于德永,曹茜,等.城市景观格局与地表温度的定量关系分析[J].北京师范大学学报(自然科学版),2017,53(3):329-336
[9] Tobler W R. A Computer Movie Simulating Urban Growth in the Detroit Region[J]. Economic Geography,1970,46(1):234-240
[10] QI Y,WU J. Effects of Changing Spatial Resolution on the Results of Landscape Pattern Analysis Using Spatial Autocorrelation Indices[J]. Landscape Ecology,1996,11(1):39-49
[11]叶骏菲,文秀,林奕桐,等.基于遥感的南宁城市热岛效应时空演变分析[J].气象研究与应用,2018,39(1):55-58
[12]蔡智,韩贵锋.山地城市空间形态的地表热环境效应:基于LCZ的视角[J].山地学报,2018,36(4):617-627
[13]江颖慧,焦利民,张博恩.城市地表温度与NDVI空间相关性的尺度效应[J].地理科学进展,2018,37(10):1 362-1 370
[14]王勇,李发斌,李何超,等. RS与GIS支持下城市热岛效应与绿地空间相关性研究[J].环境科学研究,2008(4):81-87
[15] Voogt J A,Oke T R. Thermal Remote Sensing of Urban Climates[J]. Remote Sensing of Environment,2003,86(3):370-384
[16]宋挺,段峥,刘军志,等. Landsat-8数据地表温度反演算法对比[J].遥感学报,2015,19(3):451-464
[17]叶彩华,刘勇洪,刘伟东,等.城市地表热环境遥感监测指标研究及应用[J].气象科技,2011,39(1):95-101
[18]林锦耀,黎夏.基于空间自相关的东莞市主体功能区划分[J].地理研究,2014,33(2):349-357
[19]胡家昱,刘丙军.基于空间自回归和地理加权回归模型的佛山市中心城区河网水系演变驱动分析[J].水文,2019,39(2):7-13
[20]胡毅佳,廖永生,陆菊月.广西沿海区域填海及其城市热岛效应研究[J].地理空间信息,2019,17(6):26-28
基本信息:
中图分类号:X87;X16
引用信息:
[1]朱梓铭,宋苑震,覃盟琳.城市热岛效应与建设强度空间关系研究[J].地理空间信息,2022,20(04):37-43.
基金信息:
国家自然科学基金资助项目(51768001); 广西自然科学基金资助项目(2017JJA150076,2017GXNSFAA198357)
2022-04-25
2022-04-25