昆明市主城区热环境及其影响因素的时空演化特征
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摘要
为了明确城市化发展所导致的城市地表变化对城市热环境时空变化的影响,基于2002年、2008年和2014年的三期遥感影像,采用辐射传输方程法和ISODATA非监督分类法对城市地表进行了地表温度反演和土地利用分类,同时利用NDVI像元二分线性模型法计算了地表的植被覆盖度,最后,通过对研究区域的土地利用、植被覆盖和热环境进行时空变化的统计分析和对比分析,得到如下结果,(1)2002—2014年,城镇用地面积共增加了295.18 km~2,相比2002年,2014年城镇用地面积增加了1.62倍,所占比重增长了10.98%;(2)大量中低植被覆盖度区域转换为中高植被覆盖度区域,植被覆盖度大于0.6的区域面积共增加了220.26km~2;(3)较高温区面积持续增加,共增加841.78km~2,与之相反的是低温区和较低温区面积持续减少,共减少701.71 km~2;(4)城市热环境虽然受到植被覆盖度等地表特征因素的影响,但是城市热环境的持续增高并非完全由于城市化导致的城市地表特征变化所致,全球变暖大环境的影响也是其均温大幅增高的主要原因之一。研究结果可作为改善城市热环境和缓解其负面效应的空间优化与规划的重要科学依据,也可为将来昆明城市发展战略提供科学参考。
In order to clarify the impact of urban surface changes on the temporal and spatial changes of urban thermal environment caused by urbanization, using the radioactive transfer equation algorithm and the ISODATA unsupervised classification method, the land surface temperatures were retrieved and land use classification were carried out, based on remote sensing images of 2002, 2008 and 2014. In addition, the vegetation coverages of the land surface were calculated by the NDVI dimidiate pixel linear model. Finally, through the statistical analysis and comparative analysis of the temporal and spatial changes of land use, vegetation cover and thermal environment in the study area, the following results were obtained:(1) In 2014, the urban land-use areas had increased by 295.18 km~2, 1.62 times more than 2002, and the proportion had increased by 10.98%.(2) A large number of medium-low vegetation coverage areas had been converted to medium-high vegetation coverage areas, and the regions of vegetation coverage greater than 0.6 had increased by 220.26 km~2.(3) The medium-high temperature areas increased continuously with a total increase of 841.78 km~2; meanwhile, the areas of low temperature and medium-low temperature were decreased by 701.71 km~2. And(4) although the urban thermal environment was affected by the surface characteristics such as vegetation coverage, the temperature of urban continuous increase was not only caused by urbanization, but also by global warming. The research results can be used as an important scientific basis for space optimization and planning, which will help to improve the urban thermal environment and relieve its negative effects. This study may also be a valuable reference for city development strategy planning of Kunming in future.
In order to clarify the impact of urban surface changes on the temporal and spatial changes of urban thermal environment caused by urbanization, using the radioactive transfer equation algorithm and the ISODATA unsupervised classification method, the land surface temperatures were retrieved and land use classification were carried out, based on remote sensing images of 2002, 2008 and 2014. In addition, the vegetation coverages of the land surface were calculated by the NDVI dimidiate pixel linear model. Finally, through the statistical analysis and comparative analysis of the temporal and spatial changes of land use, vegetation cover and thermal environment in the study area, the following results were obtained:(1) In 2014, the urban land-use areas had increased by 295.18 km~2, 1.62 times more than 2002, and the proportion had increased by 10.98%.(2) A large number of medium-low vegetation coverage areas had been converted to medium-high vegetation coverage areas, and the regions of vegetation coverage greater than 0.6 had increased by 220.26 km~2.(3) The medium-high temperature areas increased continuously with a total increase of 841.78 km~2; meanwhile, the areas of low temperature and medium-low temperature were decreased by 701.71 km~2. And(4) although the urban thermal environment was affected by the surface characteristics such as vegetation coverage, the temperature of urban continuous increase was not only caused by urbanization, but also by global warming. The research results can be used as an important scientific basis for space optimization and planning, which will help to improve the urban thermal environment and relieve its negative effects. This study may also be a valuable reference for city development strategy planning of Kunming in future.
引文
CHEN X,ZHANG Y P,2017.Impacts of urban surface characteristics on spatiotemporal pattern of land surface temperature in Kunming of China[J].Sustainable Cities and Society,32:87-99.
SHAHMOHAMADI P,CHE-ANI A I,ETESSAM I,et al.,2011.Healthy environment:the need to mitigate urban heat island effects on human health[J].Procedia Engineering,20:61-70.
WENG Q H,LU D S,SCHUBRING J,2004.Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies[J].Remote Sensing of Environment,89(4):467-483.
包月梅,孙紫英,赵鹏武,等,2015.基于遥感数据的根河市火烧迹地植被覆盖度时空分析[J].东北林业大学学报,43(11):62-69.
陈旭,李霖,王江,2015.城市绿地对热岛效应的缓解作用研究[J].生态环境学报,24(4):643-649.
郭红,龚文峰,李雁,等,2007.哈尔滨市热岛效应与植被的关系--基于RS和GIS的定量研究[J].自然灾害学报,16(2):22-26.
何介南,肖毅峰,吴耀兴,等,2011.4种城市绿地类型缓解热岛效应比较[J].中国农学通报,27(16):70-74.
黄良美,黄玉源,黎桦,等,2007.城市不同绿地生境小气候的时空变异规律分析[J].城市环境与城市生态,20(1):29-31,34.
黄伟峰,朱冠友,1988.深圳特区的城市气候[J].中山大学学报:自然科学,7(2):57-63.
江樟焰,陈云浩,李京,2006.基于Landsat TM数据的北京城市热岛研究[J].武汉大学学报·信息科学版,31(2):120-123.
李柏延,任志远,李瑞宗,等,2014.西安市地表温度反演及城市热岛强度定量化研究[J].资源科学,36(12):2631-2636.
李翔泽,李宏勇,张清涛,等,2014.不同地被类型对城市热环境的影响研究[J].生态环境学报,23(1):106-112.
梁娟,蔺银鼎,2007.城市森林对周边小气候时空格局的影响[J].中国农学通报,23(7):379-385.
蔺银鼎,韩学孟,武小刚,等,2006.城市绿地空间结构对绿地生态场的影响[J].生态学报,26(10):3339-3346.
凌丽媛,梁保平,2016.城市地表典型遥感参数与热岛效应时空分析研究--以桂林市为例[J].测绘与空间地理信息,39(3):24-27.
刘娇妹,李树华,杨志峰,2008.北京公园绿地夏季温湿效应[J].生态学杂志,27(11):1972-1978.
刘静,银山,张国胜,等,2009.毛乌素沙地17年间植被覆盖度变化的遥感监测[J].干旱区资源与环境,23(7):162-167.
刘鑫,甘淑,2011.基于Landsat数据的昆明地区热岛效应分析[J].科学技术与工程,11(13):3009-3013.
刘艳红,郭晋平,2009.基于植被指数的太原市绿地景观格局及其热环境效应[J].地理科学进展,28(5):798-804.
栾庆祖,叶彩华,刘勇洪,等,2014.城市绿地对周边热环境影响遥感研究--以北京为例[J].生态环境学报,23(2):252-261.
彭妮,周泓孙,李江林,等,2015.昆明近50年城市化气候变化特征及未来趋势[J].安徽农业科学,43(30):171-174,177.
钱成越,2010.基于ISODATA算法的土地利用状况调查[J].山西建筑,36(13):366-367.
权凌,周纪,李明松,等,2014.基于时间序列建模的城市热岛时间尺度成分分离方法与应用[J].地球科学进展,29(6):723-733.
宋毅,杨昆,赵旭东,等,2014.基于ETM+/TM数据的滇池流域不透水面变化与城市热岛效应关系研究[J].科学技术与工程,14(3):49-54.
孙绩华,冯健武,段玮,2015.昆明城市热岛效应变化特征研究[J].气候与环境研究,20(6):645-653.
王冬梅,孟兴民,刑钊,等,2012.基于RS的武都区植被覆盖度动态变化及其驱动力分析[J].干旱区资源与环境,26(11):92-97.
吴露露,罗旭,张雁,等,2008.中低分辨率遥感影像几何精校正[J].北京林业大学学报,30(1):78-82.
吴志刚,江滔,樊艳磊,等,2016.基于Landsat8数据的地表温度反演及分析研究[J].工程地球物理学报,13(1):135-142.
徐赛萍,沙晋明,刘玉琴,等,2014.城市热岛效应对植被生态环境质量的响应研究--以福州市马尾区为例[J].福建师范大学学报(自然科学版),30(3):137-146.
张好,徐涵秋,李乐,等,2014.成都市热岛效应与城市空间发展关系分析[J].地球信息科学学报,16(1):70-78.
赵颜创,赵小锋,旷达,2014.宁波城市热岛随城市化演变的多指标综合分析[J].生态环境学报,23(10):1628-1635.
郑亦佳,刘树华,何萍,等,2017.滇中地区夏季城市热岛效应的数值模拟研究[J].北京大学学报(自然科学版),53(4):639-651.
周坚华,1998.城市生存环境绿色量值群的研究(5)--绿化三维量及其应用研究[J].中国园林,(5):61-63.
SHAHMOHAMADI P,CHE-ANI A I,ETESSAM I,et al.,2011.Healthy environment:the need to mitigate urban heat island effects on human health[J].Procedia Engineering,20:61-70.
WENG Q H,LU D S,SCHUBRING J,2004.Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies[J].Remote Sensing of Environment,89(4):467-483.
包月梅,孙紫英,赵鹏武,等,2015.基于遥感数据的根河市火烧迹地植被覆盖度时空分析[J].东北林业大学学报,43(11):62-69.
陈旭,李霖,王江,2015.城市绿地对热岛效应的缓解作用研究[J].生态环境学报,24(4):643-649.
郭红,龚文峰,李雁,等,2007.哈尔滨市热岛效应与植被的关系--基于RS和GIS的定量研究[J].自然灾害学报,16(2):22-26.
何介南,肖毅峰,吴耀兴,等,2011.4种城市绿地类型缓解热岛效应比较[J].中国农学通报,27(16):70-74.
黄良美,黄玉源,黎桦,等,2007.城市不同绿地生境小气候的时空变异规律分析[J].城市环境与城市生态,20(1):29-31,34.
黄伟峰,朱冠友,1988.深圳特区的城市气候[J].中山大学学报:自然科学,7(2):57-63.
江樟焰,陈云浩,李京,2006.基于Landsat TM数据的北京城市热岛研究[J].武汉大学学报·信息科学版,31(2):120-123.
李柏延,任志远,李瑞宗,等,2014.西安市地表温度反演及城市热岛强度定量化研究[J].资源科学,36(12):2631-2636.
李翔泽,李宏勇,张清涛,等,2014.不同地被类型对城市热环境的影响研究[J].生态环境学报,23(1):106-112.
梁娟,蔺银鼎,2007.城市森林对周边小气候时空格局的影响[J].中国农学通报,23(7):379-385.
蔺银鼎,韩学孟,武小刚,等,2006.城市绿地空间结构对绿地生态场的影响[J].生态学报,26(10):3339-3346.
凌丽媛,梁保平,2016.城市地表典型遥感参数与热岛效应时空分析研究--以桂林市为例[J].测绘与空间地理信息,39(3):24-27.
刘娇妹,李树华,杨志峰,2008.北京公园绿地夏季温湿效应[J].生态学杂志,27(11):1972-1978.
刘静,银山,张国胜,等,2009.毛乌素沙地17年间植被覆盖度变化的遥感监测[J].干旱区资源与环境,23(7):162-167.
刘鑫,甘淑,2011.基于Landsat数据的昆明地区热岛效应分析[J].科学技术与工程,11(13):3009-3013.
刘艳红,郭晋平,2009.基于植被指数的太原市绿地景观格局及其热环境效应[J].地理科学进展,28(5):798-804.
栾庆祖,叶彩华,刘勇洪,等,2014.城市绿地对周边热环境影响遥感研究--以北京为例[J].生态环境学报,23(2):252-261.
彭妮,周泓孙,李江林,等,2015.昆明近50年城市化气候变化特征及未来趋势[J].安徽农业科学,43(30):171-174,177.
钱成越,2010.基于ISODATA算法的土地利用状况调查[J].山西建筑,36(13):366-367.
权凌,周纪,李明松,等,2014.基于时间序列建模的城市热岛时间尺度成分分离方法与应用[J].地球科学进展,29(6):723-733.
宋毅,杨昆,赵旭东,等,2014.基于ETM+/TM数据的滇池流域不透水面变化与城市热岛效应关系研究[J].科学技术与工程,14(3):49-54.
孙绩华,冯健武,段玮,2015.昆明城市热岛效应变化特征研究[J].气候与环境研究,20(6):645-653.
王冬梅,孟兴民,刑钊,等,2012.基于RS的武都区植被覆盖度动态变化及其驱动力分析[J].干旱区资源与环境,26(11):92-97.
吴露露,罗旭,张雁,等,2008.中低分辨率遥感影像几何精校正[J].北京林业大学学报,30(1):78-82.
吴志刚,江滔,樊艳磊,等,2016.基于Landsat8数据的地表温度反演及分析研究[J].工程地球物理学报,13(1):135-142.
徐赛萍,沙晋明,刘玉琴,等,2014.城市热岛效应对植被生态环境质量的响应研究--以福州市马尾区为例[J].福建师范大学学报(自然科学版),30(3):137-146.
张好,徐涵秋,李乐,等,2014.成都市热岛效应与城市空间发展关系分析[J].地球信息科学学报,16(1):70-78.
赵颜创,赵小锋,旷达,2014.宁波城市热岛随城市化演变的多指标综合分析[J].生态环境学报,23(10):1628-1635.
郑亦佳,刘树华,何萍,等,2017.滇中地区夏季城市热岛效应的数值模拟研究[J].北京大学学报(自然科学版),53(4):639-651.
周坚华,1998.城市生存环境绿色量值群的研究(5)--绿化三维量及其应用研究[J].中国园林,(5):61-63.