无人机热红外城市地表温度精细特征研究
|
摘要
以南京市江宁区某大学校园为研究区,利用无人机搭载热红外成像仪获取6种典型城市下垫面(水体、灌木、草坪、荷兰砖路面、大理石路面、沥青路面)地表温度数据,分析其在不同天气、不同月份的变化状况,并估算其感热释放量,定量描述不同下垫面地表温度的精细特征。通过对地表温度与气象因子进行相关性分析,探究地表温度变化的影响因素。结果表明:不同天气条件下,下垫面地表温度变化特征、感热释放量均存在差异。晴天时不同下垫面地表温度日变化波动较大,沥青路面温度相对较高,感热释放量最大,大理石、荷兰砖路面次之。水体和灌木在白天几乎没有感热释放量,对热环境缓解效应明显。阴天时不同下垫面地表温度日变化均不明显,人工地表仍然是感热释放的主体。气象因子中,太阳辐射和空气温度与下垫面温度呈正相关,对下垫面有增温作用,空气湿度与下垫面温度呈负相关,对下垫面增温具有一定的抑制作用。研究为城市微环境研究提供了新的思路和方法,并能够为城市微热环境遥感研究提供一定的理论依据。
Taking a university campus in Jiangning District of Nanjing as the study area,we used an Unmanned Aerial Vehicle(UAV) mounted with a thermal infrared imager to map the land surface temperature of the study area for analysis of thermal variance and its change over different typical urban surface patterns.6 typical urban underlying surfaces(water,shrubs,grass,brick pavement,marble pavement and asphalt pavement) were identified in the study area.Thus,the objective of the study is to analyze the variation of the obtained land surface temperature among the surface patterns in the study area and to reveal the detailed characteristics of the LST changes under different weather conditions within a day and a month.The estimation of sensible heat release was conducted to quantitatively describe the fine characteristics of the surface temperature of different underlying surfaces.The influencing factors of surface temperature changes were investigated by correlating surface temperature with meteorological factors.The results showed that under different weather conditions,there were differences in the characteristics of surface temperature and sensible heat release on underlying surfaces.In sunny days,the diurnal variation of different underlying surfaces fluctuated greatly,the temperature of asphalt pavement was relatively high,and the sensible heat release was the largest,which had the greatest impact on the thermal environment,followed by the marble and brick pavement.The water and shrub almost had no sensible heat release during the day,and the remission effect on the thermal environment was obvious.In cloudy days,the diurnal variation of surface temperature on different underlying surfaces was not obvious and the artificial was still the main body of sensible heat release.Referring to meteorological factors,the solar radiation and the air temperature were positively correlated with the surface temperature of the underlying surface which had a warming effect on the underlying surface.The air humidity was negatively correlated with the temperature of the underlying surface,which played a role of cooling the land surface.This research will provide a new idea and method for the study of urban micro-thermal environment and a theoretical basis for the research of urban micro-thermal environment based on remote sensing.
Taking a university campus in Jiangning District of Nanjing as the study area,we used an Unmanned Aerial Vehicle(UAV) mounted with a thermal infrared imager to map the land surface temperature of the study area for analysis of thermal variance and its change over different typical urban surface patterns.6 typical urban underlying surfaces(water,shrubs,grass,brick pavement,marble pavement and asphalt pavement) were identified in the study area.Thus,the objective of the study is to analyze the variation of the obtained land surface temperature among the surface patterns in the study area and to reveal the detailed characteristics of the LST changes under different weather conditions within a day and a month.The estimation of sensible heat release was conducted to quantitatively describe the fine characteristics of the surface temperature of different underlying surfaces.The influencing factors of surface temperature changes were investigated by correlating surface temperature with meteorological factors.The results showed that under different weather conditions,there were differences in the characteristics of surface temperature and sensible heat release on underlying surfaces.In sunny days,the diurnal variation of different underlying surfaces fluctuated greatly,the temperature of asphalt pavement was relatively high,and the sensible heat release was the largest,which had the greatest impact on the thermal environment,followed by the marble and brick pavement.The water and shrub almost had no sensible heat release during the day,and the remission effect on the thermal environment was obvious.In cloudy days,the diurnal variation of surface temperature on different underlying surfaces was not obvious and the artificial was still the main body of sensible heat release.Referring to meteorological factors,the solar radiation and the air temperature were positively correlated with the surface temperature of the underlying surface which had a warming effect on the underlying surface.The air humidity was negatively correlated with the temperature of the underlying surface,which played a role of cooling the land surface.This research will provide a new idea and method for the study of urban micro-thermal environment and a theoretical basis for the research of urban micro-thermal environment based on remote sensing.
引文
[1] Liu Yonghong,Quan Weijun.Research on High Temperature Indices of Beijing City and Its Spatio-temporal Pattern based on Satellite Data[J].Climatic & Environmental Research,2014,19(3):332-342.[刘勇洪,权维俊.北京城市高温遥感指标初探与时空格局分析[J].气候与环境研究,2014,19(3):332-342.]
[2] Fang Chuanglin.Urbanization Process and Eco-environmental Effects[M].Beijing:Science Press,2008.[方创琳.城市化过程与生态环境效应[M].北京:科学出版社,2008.]
[3] Wu Liangyong.Expectations of 21st Century Architecture-source Material of the Beijing Chapter[J].Architectural Journal,1998(4):1-18.[吴良镛.21世纪建筑学的展望“北京宪章”基础材料[J].华中建筑,1998(4):1-18.]
[4] Liu Xiaotu.Urban Physical Environment and Sustainable Development[M].Nanjing:Southeast University Press,1999.[柳孝图.城市物理环境与可持续发展[M].南京:东南大学出版社,1999.]
[5] Liu Xiaotu,Yu Minde,Thermal Environment of Urban Area and The Improvement of Its Micro-thermal Environment[J].Environmental Science,1997(1):54-58.[柳孝图,余德敏.城市热环境及其微热环境的改善[J].环境科学,1997(1):54-58.]
[6] Qin Zhihao,Arnon K.Mono-window Algorithm for Retrieving Land Surface Temperature from Landsat TM6 Data[J].Acta Geographica Sinica,2001,56(4):456-466.[覃志豪,ArnonKarnieli.用陆地卫星TM6数据演算地表温度的单窗算法[J].地理学报,2001,56(4):456-466.]
[7] Song Ting,Duan Zheng,Liu Junzhi,et al.Comparison of Four Algorithms to Retrieve Land Surface Temperature Using Landsat 8 Satellite[J].Journal of Remote Sensing,2015,19(3):451-464[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.]
[8] Jang Zhangyan,Chen Yunhao,Li Jing.Heat Island Effect of Beijng based on Landsat TM Data[J].Geomatics & Information Science of Wuhan University,2006,31(2):120-123.[江樟焰,陈云浩,李京.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,2006,31(2):120-123.
[9] Li K,Chen Y,Wang M.Spatial-temporalVariations of Surface Urban Heat Island Intensity Induced by Different Definitions of Rural Extents in China[J].Sci Total Environ.2019,669:229-247.
[10] Li Zhaoliang,Duan Sibo,Tang Bohui,et al.Review of Methods for Land Surface Temperature derived from Thermal Infrared Remotely Sensed Data[J].Journal of Remote Sensing,2016.[李召良,段四波,唐伯惠,等.热红外地表温度遥感反演方法研究进展[J].遥感学报,2016,20(5):899-920.]
[11] Li Deren,Li Ming.Research Advance and Application Prospect of Unmanned Aerial Vehicle Remote Sensing System[J].Geomatics & Information Science of Wuhan University,2014,39(5):505-513.[李德仁,李明.无人机遥感系统的研究进展与应用前景[J].武汉大学学报·信息科学版,2014,39(5):505-513.]
[12] Zhang C.TheApplication of Small Anmanned Aerial Systems for Precision Agriculture:A Review[J].Precision Agriculture,2012,13(6):693-712.
[13] Chu Hongliang,Xiao Qing,Bai Jjunhua,et al.The Retrieval of Leaf Area Index based on Remote Sensing by Unmanned Aerial Vehicle[J].Remote Sensing Technology and Application,2017,32(1):140-148.[褚洪亮,肖青,柏军华,等.基于无人机遥感的叶面积指数反演[J].遥感技术与应用,2017,32(1):140-148.]
[14] Cui S Z,Zhou J G.Application of UAV Aerial System on Surveying and Mapping of Topographic Map at Scale 1∶1 000[J].Surveying & Mapping of Geology & Mineral Resources,2014,30(4):140-148.
[15] Zhang Chunbin,Yang Shengtian,Zhao Changsen,et al.Topographic Data Accuracy Verification of Small Consumer UAV[J].Journal of Remote Sensing,2018,22(1):185-195.[张纯斌,杨胜天,赵长森,等.小型消费级无人机地形数据精度验证[J].遥感学报,2018,22(1):185-195.]
[16] Chrétien L P,Théau J,Ménard P.Wildlife Multispecies Remote Sensing Using Visible and Thermal Infrared Imagery Acquired from AN Unmanned Aerial Vehicle (uav)[C]// International Conference on Unmanned Aerial Vehicles in Geomatics,2015,37:533-544.
[17] Zhang Zhengjian,Li Ainong,Bian Jinhu,et al.Estimating Aboveground Biomass of Grassland in Zoige by Visible Vegetation Index derived from Unmanned Aerial Vehicle Image[J].Remote Sensing Technology and Application,2016,31(1):51-62.[张正健,李爱农,边金虎,等.基于无人机影像可见光植被指数的若尔盖草地地上生物量估算研究[J].遥感技术与应用,2016,31(1):51-62.]
[18] Kraaijenbrink P D A,Shea J M,Litt M,et al.Mapping Surface Temperatures on a Debris-covered Glacier with an Unmanned Aerial Vehicle[J].Frontiers in Earth Science,2018,6:64-83.
[19] Sun Zhongyu,Chen Yanqiao,Yang Long,et al.Small Unmanned Aerial Vehicles for Low-altitude Remote Sensing and Its Application Progress in Ecology[J].Chinese Journal of Applied Ecology,2017,28(2):528-536.[孙中宇,陈燕乔,杨龙,等.轻小型无人机低空遥感及其在生态学中的应用进展[J].应用生态学报,2017,28(2):528-536.]
[20] Espinoza C Z,Khot L R,Sankaran S,et al.High Resolution Multispectral and Thermal Remote Sensing-based Water Stress Assessment in Subsurface Irrigated Grapevines[J].Remote Sensing,2017,9:961-975.
[21] Smigaj M,Gaulton R,Suarez J C,et al.CanopyTemperature From an Unmanned Aerial Vehicle as an Indicator of Tree Stress Associated with Red Band Needle Blight Severity[J].Forest Ecol Manag.2019,433:699-708.
[22] Homainejad N,Rizos C.Application of Multiple Categories of Unmanned Aircraft Systems (uas) in Different Airspaces for Bushfire Monitoring and Response[J].ISPRS-International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences,2015,XL-1/W4:55-60.
[23] Rahaghi A I,Lemmin U,Sage D,et al.AchievingHigh-resolution Thermal Imagery in Low-contrast Lake Surface Waters by Aerial Remote Sensing and Image Registration[J].Remote Sensing of Environment.2019,221:773-783.
[24] Zarco-Tejada PJ,González-Dugo V,Berni J A J.Fluorescence Temperature and Narrow-band Indices Acquired from a UAV Platform for Water Stress Detection Using a Micro-hyperspectral Imager and a Thermal Camera[J].Remote Sensing of Environment,2012,117(1):322-337.
[25] Calderón R,Navas-Cortés J A,Lucena C,et al.High-resolution Airborne Hyperspectral and Thermal Imagery for Early Detection of Verticillium Wilt of Olive Using Fluorescence Temperature and Narrow-band Spectral Indices[J].Remote Sensing of Environment,2013,139(139):231-245.
[26] Baluja J,Diago M P,Balda P,et al.Assessment ofVineyard Water Status Variability by Thermal and Multispectral Imagery Using an Unmanned Aerial Vehicle (UAV)[J].Irrigation Science,2012,30(6):511-522.
[27] Li Feng,Cui Ximin,Sun Guangtong,et al.Approach of Detecting Coal Fires by Unmanned Aerial Vehicle Thermal Infrared Remote Sensing Technology[J].Safety in Coal Mines,2017,48(12):97-100.[李峰,崔希民,孙广通,等.无人机热红外遥感煤火探测方法[J].煤矿安全,2017,48(12):97-100.]
[28] Dios M D,Ollero A.Automatic Detection of Windows Thermal Heat Losses in Buildings Using UAVs[C]// Automation Congress,2006.WAC ′06.World.IEEE,2006:1-6.
[29] Wu Zhifeng,Wang Yening,Kong Fanhua,et al.Analysis of the Thermal Characteristics of Selected Urban Surfaces in a Typical Residential Area based on Infrared Thermography[J].Acta Ecologica Sinica,2016,36(17) :5421-5431.[吴志丰,王业宁,孔繁花,等.基于热红外影像数据的典型居住区常见地表类型热特征分析[J].生态学报,2016,36(17):5421-5431.]
[30] Sagan V,Maimaitijiang M,Sidike P,et al.Uav-basedHigh Resolution Thermal Imaging for Vegetation Monitoring and Plant Phenotyping Using ici 8640 p,Flir vue pro 640R,and Thermomap Cameras[J].Remote Sensing,2019,11:330.
[31] Gao Shuaihua,Wang Ning.Thermal Infrared Detection based on UAV Remote Sensing Technology[J].China Science and Technology Information,2018,9:101-102.[高帅华,王宁.基于无人机遥感技术的热红外探测[J].中国科技信息,2018,9:101-102.]
[32] Li Xiaowen.Principle and Application of Remote Sensing[M].Beijing:Science Press,2008.[李小文.遥感原理与应用[M].北京:科学出版社,2008.]
[33] Voogt J A,Oke T R.Effects ofUrban Surface Geometry on Remotely-sensed Surface Temperature[J].International Journal of Remote Sensing,1998,19(5):895-920.
[34] Chen J M,Zhang R H.Studies on the Measurements of Crop Emissivity and Sky Temperature[J].Agricultural & Forest Meteorology,1989,49(1):23-34.
[35] Qin Y,Hiller J E.UnderstandingPavement-surface Energy Balance and Its Implications on Cool Pavement Development[J].Energy & Buildings,2014,85(85):389-399.
[36] Bentz D.A Computer Model to Predict the Surface Temperature and Time-of-Wetness of Concrete Pavements and Br[EB/OL].National Institute of Standands and Techonoleng,2000,6551.http://trud.trv.irg/vuew/474923.
[37] Landsberg L E.The Urban Climate[M].Academic Press,1981.
[38] Guo Shiyou,Zhou Zhenwei,Liu Chunsheng.Simulation Wind Speed Changes of the Different Height in Exponential Wind Profile[J].Heilongjiang Meteorology,2008,25:20-22.[国世友,周振伟,刘春生.用风廓线指数律模拟风速随高度变化[J].黑龙江气象,2008,25:20-22.]
[39] YangYajun,Zou Zhendong,Zhao Wenli,et al.Comparative Study on the Thermal Environment Effect of Six Urban Underlying Surfaces[J].Acta Scientiarum Naturalium Universitatis Pekinensis,2017,53(5):881-889[杨雅君,邹振东,赵文利,等.6种城市下垫面热环境效应对比研究[J].北京大学学报:自然科学版,2017,53(5):881-889.]
[2] Fang Chuanglin.Urbanization Process and Eco-environmental Effects[M].Beijing:Science Press,2008.[方创琳.城市化过程与生态环境效应[M].北京:科学出版社,2008.]
[3] Wu Liangyong.Expectations of 21st Century Architecture-source Material of the Beijing Chapter[J].Architectural Journal,1998(4):1-18.[吴良镛.21世纪建筑学的展望“北京宪章”基础材料[J].华中建筑,1998(4):1-18.]
[4] Liu Xiaotu.Urban Physical Environment and Sustainable Development[M].Nanjing:Southeast University Press,1999.[柳孝图.城市物理环境与可持续发展[M].南京:东南大学出版社,1999.]
[5] Liu Xiaotu,Yu Minde,Thermal Environment of Urban Area and The Improvement of Its Micro-thermal Environment[J].Environmental Science,1997(1):54-58.[柳孝图,余德敏.城市热环境及其微热环境的改善[J].环境科学,1997(1):54-58.]
[6] Qin Zhihao,Arnon K.Mono-window Algorithm for Retrieving Land Surface Temperature from Landsat TM6 Data[J].Acta Geographica Sinica,2001,56(4):456-466.[覃志豪,ArnonKarnieli.用陆地卫星TM6数据演算地表温度的单窗算法[J].地理学报,2001,56(4):456-466.]
[7] Song Ting,Duan Zheng,Liu Junzhi,et al.Comparison of Four Algorithms to Retrieve Land Surface Temperature Using Landsat 8 Satellite[J].Journal of Remote Sensing,2015,19(3):451-464[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.]
[8] Jang Zhangyan,Chen Yunhao,Li Jing.Heat Island Effect of Beijng based on Landsat TM Data[J].Geomatics & Information Science of Wuhan University,2006,31(2):120-123.[江樟焰,陈云浩,李京.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,2006,31(2):120-123.
[9] Li K,Chen Y,Wang M.Spatial-temporalVariations of Surface Urban Heat Island Intensity Induced by Different Definitions of Rural Extents in China[J].Sci Total Environ.2019,669:229-247.
[10] Li Zhaoliang,Duan Sibo,Tang Bohui,et al.Review of Methods for Land Surface Temperature derived from Thermal Infrared Remotely Sensed Data[J].Journal of Remote Sensing,2016.[李召良,段四波,唐伯惠,等.热红外地表温度遥感反演方法研究进展[J].遥感学报,2016,20(5):899-920.]
[11] Li Deren,Li Ming.Research Advance and Application Prospect of Unmanned Aerial Vehicle Remote Sensing System[J].Geomatics & Information Science of Wuhan University,2014,39(5):505-513.[李德仁,李明.无人机遥感系统的研究进展与应用前景[J].武汉大学学报·信息科学版,2014,39(5):505-513.]
[12] Zhang C.TheApplication of Small Anmanned Aerial Systems for Precision Agriculture:A Review[J].Precision Agriculture,2012,13(6):693-712.
[13] Chu Hongliang,Xiao Qing,Bai Jjunhua,et al.The Retrieval of Leaf Area Index based on Remote Sensing by Unmanned Aerial Vehicle[J].Remote Sensing Technology and Application,2017,32(1):140-148.[褚洪亮,肖青,柏军华,等.基于无人机遥感的叶面积指数反演[J].遥感技术与应用,2017,32(1):140-148.]
[14] Cui S Z,Zhou J G.Application of UAV Aerial System on Surveying and Mapping of Topographic Map at Scale 1∶1 000[J].Surveying & Mapping of Geology & Mineral Resources,2014,30(4):140-148.
[15] Zhang Chunbin,Yang Shengtian,Zhao Changsen,et al.Topographic Data Accuracy Verification of Small Consumer UAV[J].Journal of Remote Sensing,2018,22(1):185-195.[张纯斌,杨胜天,赵长森,等.小型消费级无人机地形数据精度验证[J].遥感学报,2018,22(1):185-195.]
[16] Chrétien L P,Théau J,Ménard P.Wildlife Multispecies Remote Sensing Using Visible and Thermal Infrared Imagery Acquired from AN Unmanned Aerial Vehicle (uav)[C]// International Conference on Unmanned Aerial Vehicles in Geomatics,2015,37:533-544.
[17] Zhang Zhengjian,Li Ainong,Bian Jinhu,et al.Estimating Aboveground Biomass of Grassland in Zoige by Visible Vegetation Index derived from Unmanned Aerial Vehicle Image[J].Remote Sensing Technology and Application,2016,31(1):51-62.[张正健,李爱农,边金虎,等.基于无人机影像可见光植被指数的若尔盖草地地上生物量估算研究[J].遥感技术与应用,2016,31(1):51-62.]
[18] Kraaijenbrink P D A,Shea J M,Litt M,et al.Mapping Surface Temperatures on a Debris-covered Glacier with an Unmanned Aerial Vehicle[J].Frontiers in Earth Science,2018,6:64-83.
[19] Sun Zhongyu,Chen Yanqiao,Yang Long,et al.Small Unmanned Aerial Vehicles for Low-altitude Remote Sensing and Its Application Progress in Ecology[J].Chinese Journal of Applied Ecology,2017,28(2):528-536.[孙中宇,陈燕乔,杨龙,等.轻小型无人机低空遥感及其在生态学中的应用进展[J].应用生态学报,2017,28(2):528-536.]
[20] Espinoza C Z,Khot L R,Sankaran S,et al.High Resolution Multispectral and Thermal Remote Sensing-based Water Stress Assessment in Subsurface Irrigated Grapevines[J].Remote Sensing,2017,9:961-975.
[21] Smigaj M,Gaulton R,Suarez J C,et al.CanopyTemperature From an Unmanned Aerial Vehicle as an Indicator of Tree Stress Associated with Red Band Needle Blight Severity[J].Forest Ecol Manag.2019,433:699-708.
[22] Homainejad N,Rizos C.Application of Multiple Categories of Unmanned Aircraft Systems (uas) in Different Airspaces for Bushfire Monitoring and Response[J].ISPRS-International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences,2015,XL-1/W4:55-60.
[23] Rahaghi A I,Lemmin U,Sage D,et al.AchievingHigh-resolution Thermal Imagery in Low-contrast Lake Surface Waters by Aerial Remote Sensing and Image Registration[J].Remote Sensing of Environment.2019,221:773-783.
[24] Zarco-Tejada PJ,González-Dugo V,Berni J A J.Fluorescence Temperature and Narrow-band Indices Acquired from a UAV Platform for Water Stress Detection Using a Micro-hyperspectral Imager and a Thermal Camera[J].Remote Sensing of Environment,2012,117(1):322-337.
[25] Calderón R,Navas-Cortés J A,Lucena C,et al.High-resolution Airborne Hyperspectral and Thermal Imagery for Early Detection of Verticillium Wilt of Olive Using Fluorescence Temperature and Narrow-band Spectral Indices[J].Remote Sensing of Environment,2013,139(139):231-245.
[26] Baluja J,Diago M P,Balda P,et al.Assessment ofVineyard Water Status Variability by Thermal and Multispectral Imagery Using an Unmanned Aerial Vehicle (UAV)[J].Irrigation Science,2012,30(6):511-522.
[27] Li Feng,Cui Ximin,Sun Guangtong,et al.Approach of Detecting Coal Fires by Unmanned Aerial Vehicle Thermal Infrared Remote Sensing Technology[J].Safety in Coal Mines,2017,48(12):97-100.[李峰,崔希民,孙广通,等.无人机热红外遥感煤火探测方法[J].煤矿安全,2017,48(12):97-100.]
[28] Dios M D,Ollero A.Automatic Detection of Windows Thermal Heat Losses in Buildings Using UAVs[C]// Automation Congress,2006.WAC ′06.World.IEEE,2006:1-6.
[29] Wu Zhifeng,Wang Yening,Kong Fanhua,et al.Analysis of the Thermal Characteristics of Selected Urban Surfaces in a Typical Residential Area based on Infrared Thermography[J].Acta Ecologica Sinica,2016,36(17) :5421-5431.[吴志丰,王业宁,孔繁花,等.基于热红外影像数据的典型居住区常见地表类型热特征分析[J].生态学报,2016,36(17):5421-5431.]
[30] Sagan V,Maimaitijiang M,Sidike P,et al.Uav-basedHigh Resolution Thermal Imaging for Vegetation Monitoring and Plant Phenotyping Using ici 8640 p,Flir vue pro 640R,and Thermomap Cameras[J].Remote Sensing,2019,11:330.
[31] Gao Shuaihua,Wang Ning.Thermal Infrared Detection based on UAV Remote Sensing Technology[J].China Science and Technology Information,2018,9:101-102.[高帅华,王宁.基于无人机遥感技术的热红外探测[J].中国科技信息,2018,9:101-102.]
[32] Li Xiaowen.Principle and Application of Remote Sensing[M].Beijing:Science Press,2008.[李小文.遥感原理与应用[M].北京:科学出版社,2008.]
[33] Voogt J A,Oke T R.Effects ofUrban Surface Geometry on Remotely-sensed Surface Temperature[J].International Journal of Remote Sensing,1998,19(5):895-920.
[34] Chen J M,Zhang R H.Studies on the Measurements of Crop Emissivity and Sky Temperature[J].Agricultural & Forest Meteorology,1989,49(1):23-34.
[35] Qin Y,Hiller J E.UnderstandingPavement-surface Energy Balance and Its Implications on Cool Pavement Development[J].Energy & Buildings,2014,85(85):389-399.
[36] Bentz D.A Computer Model to Predict the Surface Temperature and Time-of-Wetness of Concrete Pavements and Br[EB/OL].National Institute of Standands and Techonoleng,2000,6551.http://trud.trv.irg/vuew/474923.
[37] Landsberg L E.The Urban Climate[M].Academic Press,1981.
[38] Guo Shiyou,Zhou Zhenwei,Liu Chunsheng.Simulation Wind Speed Changes of the Different Height in Exponential Wind Profile[J].Heilongjiang Meteorology,2008,25:20-22.[国世友,周振伟,刘春生.用风廓线指数律模拟风速随高度变化[J].黑龙江气象,2008,25:20-22.]
[39] YangYajun,Zou Zhendong,Zhao Wenli,et al.Comparative Study on the Thermal Environment Effect of Six Urban Underlying Surfaces[J].Acta Scientiarum Naturalium Universitatis Pekinensis,2017,53(5):881-889[杨雅君,邹振东,赵文利,等.6种城市下垫面热环境效应对比研究[J].北京大学学报:自然科学版,2017,53(5):881-889.]
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |