Please wait a minute...
img

官方微信

遥感技术与应用  2021, Vol. 36 Issue (3): 673-681    DOI: 10.11873/j.issn.1004-0323.2021.3.0673
遥感应用     
遥感城市热岛提取的影响因素分析
尹翠景1(),封凯1,王奇2,刘磊1()
1.长安大学地球科学与资源学院,西部矿产资源与地质工程教育部重点实验室,陕西 西安 710054
2.中国资源卫星应用中心,北京 100094
Analysis of Influence Factors of Urban Heat Island Effect based on Remote Sensing
Cuijing Yin1(),Kai Feng1,Qi Wang2,Lei Liu1()
1.School of Earth Science and Resources,Chang’an University,Xi’an 710054,China
2.China Siwei Surveying and Mapping Techology Co. Ltd. ,Beijing 100094,China
 全文: PDF(6427 KB)   HTML
摘要:

随着城市化进程的加快,热岛效应成为当今社会热点问题,研究主要集中于热岛强度变化和景观格局影响分析。遥感热岛提取结果受到多方面因素的影响,因此影像选择尤为关键。以石家庄地区为例,选取不同季节、相同季节但植被状态不同的Landsat影像以及ASTER夜间影像,分析季节、农田生长状态、昼夜等因素对遥感热岛提取结果的影响。研究表明:农田作物生长茂盛、平均温度高的季节,遥感热岛提取效果较好且热岛强度较大;农田作物收获后,土地裸露,为保证遥感热岛有效提取应选择夜间数据。实验结果可为热岛研究过程中遥感数据选择和分析提供参考。

关键词: 城市热岛遥感石家庄影响因素    
Abstract:

With the rapid growth of urbanization, the heat island effect has become a hot issue in today’s society. Most of the existing researches focus on the analysis of heat island intensity change and landscape pattern influence. In fact, the extraction results of remote sensing heat island are affected by many factors. Image selection is particularly critical. Taking Shijiazhuang as an example, Landsat (different seasons and different vegetation status in the same season) and ASTER night images were used in this paper. These data were used to analyze the impacts of season, farmland growth state, daytime and night and other factors on the extraction results of remote sensing heat island. Research show that, in the seasons with flourish crops growth, high average temperature, remote sensing heat island extraction effect is better and the intensity of heat island is larger. After the harvest of farmland crops, the land is bare. To ensure the quality of remote sensing heat island extraction, night data should be selected. The experimental results can provide reference for the selection and analysis of remote sensing data in the process of heat island research.

Key words: Urban Heat Island    Remote sensing    Shijiazhuang    Influence factors
收稿日期: 2020-05-21 出版日期: 2021-07-22
ZTFLH:  X16  
基金资助: 中央高校基本科研业务费专项资金项目(300102278303)
通讯作者: 刘磊     E-mail: yiyin.jing@foxmail.com;liul@chd.edu.cn
作者简介: 尹翠景(1995-),女,河北沧州人,硕士,主要从事遥感应用研究。E?mail: yiyin.jing@foxmail.com
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
尹翠景
封凯
王奇
刘磊

引用本文:

尹翠景,封凯,王奇,刘磊. 遥感城市热岛提取的影响因素分析[J]. 遥感技术与应用, 2021, 36(3): 673-681.

Cuijing Yin,Kai Feng,Qi Wang,Lei Liu. Analysis of Influence Factors of Urban Heat Island Effect based on Remote Sensing. Remote Sensing Technology and Application, 2021, 36(3): 673-681.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2021.3.0673        http://www.rsta.ac.cn/CN/Y2021/V36/I3/673

图1  研究区位置图
传感器成像时间(UTC)
Landsat 82015年7月12日02:59
2015年7月12日03:00
Landsat 52009年4月6日02:47
2009年4月6日02:47
2009年6月25日02:48
2009年6月25日02:48
2009年8月12日02:49
2009年8月12日02:49
2009年10月15日02:50
2009年10月15日02:50
2009年12月18日02:50
2009年12月18日02:51
ASTER2015年6月26日14:34
2015年6月26日14:41
表1  石家庄遥感影像信息
图2  4个时相地表温度等级分布图
城区地温平均值/℃郊区地温平均值/℃差值/℃
春季29.5228.301.22
夏季40.3634.835.53
秋季23.0225.46-2.44
冬季-1.390.07-1.46
表2  4个时相热岛强度统计表
图3  农田作物对热岛效应的影响
图4  昼夜温度等级分布图
1 Keikhosravi Q. The Effect of Heat Waves on the Intensification of the Heat Island of Iran’s Metropolises(Tehran, Mashhad, Tabriz, Ahvaz)[J]. Urban Climate, 2019, 28:100453. doi:10.1016/j.uclim.2019.100453.
doi: 10.1016/j.uclim.2019.100453
2 Venter Z S, Brousse O, Esau I, et al. Hyperlocal Mapping of Urban Air Temperature Using Remote Sensing and Crowdsourced Weather Data[J]. Remote Sensing of Environment, 2020, 242: 111791. doi:10.1016/j.rse.2020.111791.
doi: 10.1016/j.rse.2020.111791
3 Parison S, Hendel M, Royon L. A Statistical Method for Quantifying the Field Effects of Urban Heat Island Mitigation Techniques[J]. Urban Climate,2020,33:100651. doi:10.1016/ j.uclim.2020.100651.
doi: 10.1016/ j.uclim.2020.100651
4 Du J, Xiang X Y, Zhao B Y, et al. Impact of Urban Expansion on Land Surface Temperature in Fuzhou, China Using Landsat Imagery[J]. Sustainable Cities and Society,2020,61: 102346. doi: 10.1016/j.scs.2020.102346.
doi: 10.1016/j.scs.2020.102346
5 Mushtaha E, Shareef S, Alsyouf I, et al. A Study of the Impact of Major Urban Heat Island Factors in a Hot Climate Courtyard: The Case of the University of Sharjah, UAE[J]. Sustainable Cities and Society,2021,69:102844. doi: 10.1016/J.SCS.2021.102844.
doi: 10.1016/J.SCS.2021.102844
6 Liu Yupeng, Yang Bo, Chen Chong. Temporal and Spatial Analysis of Urban Heat Island in Changsha Remote Sensing Data[J]. Remote Sensing Information, 2011,26(6):73-78.
6 刘宇鹏,杨波,陈崇.基于遥感的长沙市城市热岛效应时空分析[J].遥感信息,2011,26(6):73-78.
7 Wang Liang, Meng Qingyan, Wu jun, et al. Monitoring and Analyzing Spatio-temporal Changes of Heat Island Intensity in Beijing Main Urban Construction Area from 2005 to 2014[J]. Journal of Geo-information Science, 2015, 17(9):1047-1054.
7 王靓,孟庆岩,吴俊,等.2005~2014年北京市主要城建区热岛强度时空格局分析[J].地球信息科学学报,2015,17(9):1047-1054.
8 Zhang Yang, Hu Deyong, Cao Shisong, et al. Monitoring Urban Heat Island Intensity of Beijing - Tianjin - Hebei Urban Agglomeration on Remote Sensing and its Relationship with Urban Scale[J]. Journal of Capital Normal University (Natural Science Edition), 2018, 39(5):72-80.
8 张旸,胡德勇,曹诗颂,等.京津冀城市群热岛强度遥感监测及其城市规模效应分析[J].首都师范大学学报(自然科学版),2018,39(5):72-80.
9 Lu Huimin, Li Fei, Zhang Meiliang, et al. Effects of Landscape Pattern on Annual Variation of Thermal Environment in Hangzhou[J]. Remote Sensing Technology and Application, 2018,33(3):398-407.
9 卢惠敏,李飞,张美亮,等.景观格局对杭州城市热环境年内变化的影响分析[J].遥感技术与应用,2018,33(3):398-407.
10 Pan Minghui, Lan Siren, Zhu Liying, et al. Influence of Landscape Pattern Types on Heat Island Effect over Central Fuzhou City[J]. China Environmental Science,2020,40(6):2635-2646.
10 潘明慧,兰思仁,朱里莹,等.景观格局类型对热岛效应的影响——以福州市中心城区为例[J]. 中国环境科学,2020,40(6):2635-2646.
11 Li Xiaoyong, Kuang Wenhui. The Effects of Urban Land Cover Composition and Structure on Land Surface Temperature in Beijing, Tianjin, and Shijiazhuang[J]. Chinese Journal of Ecology, 2019, 38(10):3057-3065.
11 李孝永,匡文慧.北京、天津和石家庄城市地表覆盖组分与结构特征对地表温度的影响[J].生态学杂志,2019,38(10):3057-3065.
12 Zhao Hongmei. Remote Sensing the Spatial Distribution of the Heat Island Effect in Shijiazhuang City[D]. Shijiazhuang:Hebei Normal University,2008.
12 赵红梅.基于遥感的石家庄市城市热岛效应的空间分异规律研究[D].石家庄:河北师范大学,2008.
13 Li Haifeng. Contrastive Analysis of Black-body Temperature and Land Surface Temperature based on TM Image[J]. Geospatial Information, 2018,16(3):47-49,53,9.
13 李海峰.基于TM影像的亮温与地温数据比对分析[J].地理空间信息,2018,16(3):47-49,53,9.
14 Ruan Junjie. Effect of Urban Parks on Thermal Environment in Summer: A Case Study in Shanghai[J]. Ecology and Environmental Sciences, 2016, 25(10):1663-1670.
14 阮俊杰.城市公园对夏季热环境的影响——以上海市中心城区为例[J].生态环境学报,2016,25(10):1663-1670.
15 Wang Tianxing, Chen Songlin, Ma Ya, et al. Comparison on Scale Effect of Urban Heat Island Defined by Brightness Temperature and Land Surface Temperature[J]. Geography and Geo-Information Science, 2007(6):73-77.
15 王天星,陈松林,马娅,等.亮温与地表温度表征的城市热岛尺度效应对比研究[J].地理与地理信息科学,2007(6):73-77.
16 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.
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 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, 20(5):899-920.
17 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.
18 Jin Diandian, Gong Zhaoning. Algorithms Comparison of Land Surface Temperature Retrieval from Landsat Series Data: A Case Study in Qiqihar[J]. Remote Sensing Technology and Application, 2018,33(5):830-841.
18 金点点,宫兆宁.基于Landsat系列数据地表温度反演算法对比分析——以齐齐哈尔市辖区为例[J].遥感技术与应用,2018,33(5):830-841.
19 Wang Lei, Wang Jie, Fu Lin, et al. Characteristics of Vegetation Coverage Changes in Nanchong Jurisdiction in the Past Fifteen Years[J]. Ecological Science,2019,38(1):159-167.
19 王磊,王杰,付林,等.南充市辖区近15年植被覆盖度变化特征[J].生态科学,2019,38(1):159-167.
20 Huang Jücong, Zhao Xiaofeng, Tang Lina, et al. Analysis on the Seasonal Changes of Urban Thermal Landscape Pattern and Its Application[J]. Ecology and Environmental Sciences, 2011,20(2):304-310.
20 黄聚聪,赵小锋,唐立娜,等.城市热力景观格局季节变化特征分析及其应用[J].生态环境学报,2011,20(2):304-310.
21 Wu Zhigang, Jiang Tao, Fan Yanlei, et al. Land Surface Temperature Retrieval and Result Analysis based on Landsat 8 Data in Wuhan City[J]. Chinese Journal of Engineering Geophysics, 2016, 13(1):135-142.
21 吴志刚,江滔,樊艳磊,等.基于Landsat 8数据的地表温度反演及分析研究——以武汉市为例[J].工程地球物理学报,2016,13(1):135-142.
22 Xu Hanqiu. Analysis on Urban Heat Island Effect based on the Dynamics of Urban Surface Biophysical Descriptors[J]. Acta Ecologica Sinica, 2011, 31(14):3890-3901.
22 徐涵秋.基于城市地表参数变化的城市热岛效应分析[J].生态学报,2011,31(14):3890-3901.
23 Qiao Zhi, Sun Zongyao, Sun Xihua, et al. Prediction and Analysis of Urban Thermal Environment Risk and Its Spatio-Temporal Pattern[J]. Acta Ecologica Sinica, 2019, 39(2):649-659.
23 乔治,孙宗耀,孙希华,等.城市热环境风险预测及时空格局分析[J].生态学报,2019,39(2):649-659.
24 Kedia S,Bhakare S, Dwivedi A K, et al. Estimates of Change in Surface Meteorology and Urban Heat Island over Northwest India: Impact of Urbanization[J]. Urban Climate, 2021, 36: 100782. doi: 10.1016/J.UCLIM.2021.100782.
doi: 10.1016/J.UCLIM.2021.100782
25 Harmay N S M, Kim D, Choi M. Urban Heat Island Associated with Land Use/Land Cover and Climate Variations in Melbourne, Australia[J]. Sustainable Cities and Society, 2021, 69: 102861. doi: 10.1016/J.SCS.2021.102861.
doi: 10.1016/J.SCS.2021.102861
26 Peng S S, Piao S L, Ciais P, et al. Surface Urban Heat Island Across 419 Global Big Cities[J]. Environment Science Technology,2012,46(2):696-703. doi:10.1021/es2030438.
doi: 10.1021/es2030438
27 Peng Shaolin, Zhou Kai, Ye Youhua, et al. Research Progress in Urban Heat Island[J]. Ecology and Environment,2005,14(4):574-579.
27 彭少麟,周凯,叶有华,等.城市热岛效应研究进展[J].生态环境,2005,14(4):574-579.
28 Peng Baofa, Shi Yishao, Wang Hefeng, et al. The Impacting Mechanism and Laws of Function of Urban Heat Island Effect: A Case Study of Shanghai[J]. Acta Geographic Sinica, 2013, 68(11):1461-1471.
28 彭保发,石忆邵,王贺封,等.城市热岛效应的影响机理及其作用规律——以上海市为例[J].地理学报,2013,68(11):1461-1471.
29 Chen Binhui, Feng Yao, Yuan Jianguo, et al. Spatiotemporal Difference of Urban Heat Island in Jing-Jin-Ji Area based on MODIS Land Surface Temperature[J]. Acta Scientiarum Naturalium Universitatis Pekinensis,2016,52(6):1134-1140.
29 陈彬辉,冯瑶,袁建国,等.基于MODIS地表温度的京津冀地区城市热岛时空差异研究[J].北京大学学报(自然科学版),2016,52(6):1134-1140.
30 Tan J K N,Belcher R N, Tan H T W, et al. The Urban Heat Island Mitigation Potential of Vegetation Depends on Local Surface Type and Shade[J]. Urban Forestry & Urban Greening,2021,62:127128. doi:10.1016/J.UFUG.2021. 127128.
doi: 10.1016/J.UFUG.2021. 127128
31 Mathew A,Khandelwal S,Kaul N.Spatio-temporal Variations of Surface Temperatures of Ahmedabad City and Its Relationship with Vegetation and Urbanization Parameters as Indicators of Surface Temperatures[J].Remote Sensing Applications: Society and Environment,2018,11:119-139. doi:10.1016/j.rsase.2018.05.003.
doi: 10.1016/j.rsase.2018.05.003
32 Qiao Zhi, Tian Guangjin. Spatiotemporal Diversity and Regionalization of the Urban Thermal Environment in Beijing[J]. Journal of Remote Sensing,2014,18(3):715-734.
32 乔治,田光进.北京市热环境时空分异与区划[J].遥感学报,2014,18(3):715-734.
33 Qiao Zhi, Huang Ningyu, Xu Xinliang, et al. Spatio-Temporal Pattern and Evolution of the Urban Thermal Landscape in Metropolitan Beijing between 2003 and 2017[J]. Acta Geographica Sinica,2019,74(3):475-489.
33 乔治,黄宁钰,徐新良,等.2003~2017年北京市地表热力景观时空分异特征及演变规律[J].地理学报,2019,74(3):475-489.
34 Wang Gang, Zhang Qiuping, Xiao Rongbo, et.al. Thermal Island Regulation Difference of Urban Green Spaces between Autumn and Winter in Guangzhou, South China[J]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2018,57(5):38-48.
34 王刚,张秋平,肖荣波,等.秋冬季节广州城市绿地对热岛效应的调控作用差异分析[J].中山大学学报(自然科学版),2018,57(5):38-48.
[1] 罗婕纯一,秦龙君,毛鹏,熊育久,赵文利,高辉辉,邱国玉. 水质遥感监测的关键要素叶绿素a的反演算法研究进展[J]. 遥感技术与应用, 2021, 36(3): 473-488.
[2] 刘鹤,顾玲嘉,任瑞治. 基于无人机遥感技术的森林参数获取研究进展[J]. 遥感技术与应用, 2021, 36(3): 489-501.
[3] 黄艳,郑玮. 基于无线传感器网络的森林生态系统观测试验平台构建[J]. 遥感技术与应用, 2021, 36(3): 502-510.
[4] 廖鸿燕,周小成,黄洪宇. 基于无人机遥感技术的台风灾害倒伏绿化树木检测[J]. 遥感技术与应用, 2021, 36(3): 533-543.
[5] 王淑静,赖佩玉,郝斌飞,马明国,韩旭军. 西南地区2001~2019年森林损失特征遥感监测与时空分析[J]. 遥感技术与应用, 2021, 36(3): 552-563.
[6] 胥鑫,朱迪. 星载差分吸收气压雷达的系统仿真与性能分析[J]. 遥感技术与应用, 2021, 36(3): 594-604.
[7] 高子为,孙伟伟,程朋根,杨刚,孟祥超. 融合高分辨率遥感影像和POI数据的多特征潜在语义信息用于识别城市功能区[J]. 遥感技术与应用, 2021, 36(3): 618-626.
[8] 李昕娟,林家元,胡桂胜,赵伟. 西南山地典型流域地震前后泥石流物源遥感精细识别[J]. 遥感技术与应用, 2021, 36(3): 638-648.
[9] 陈敏,潘佳威,李江杰,徐璐,刘加敏,韩健,陈奕云. 结合VGGNet与Mask R-CNN的高分辨率遥感影像建设用地检测[J]. 遥感技术与应用, 2021, 36(2): 256-264.
[10] 陈妮,应丰,王静,李健. 基于U-Net的高分辨率遥感图像土地利用信息提取[J]. 遥感技术与应用, 2021, 36(2): 285-292.
[11] 林娜,冯丽蓉,张小青. 基于优化Faster-RCNN的遥感影像飞机检测[J]. 遥感技术与应用, 2021, 36(2): 275-284.
[12] 李庆,陈俊杰,李庆亭,李柏鹏,卢凯旋,昝露洋,陈正超. 基于SSD模型的京津冀地区尾矿库检测[J]. 遥感技术与应用, 2021, 36(2): 293-303.
[13] 祝一诺,高婷,王术东,周磊,杜明义. 基于迁移学习再训练模型和高分遥感数据的建筑垃圾自动识别方法[J]. 遥感技术与应用, 2021, 36(2): 314-323.
[14] 帅艳民,杨健,吴昊,邵聪颖,徐辛超,刘明岳,刘涛,梁继. 基于无人机观测的水稻冠层样方多角度反射特点分析[J]. 遥感技术与应用, 2021, 36(2): 342-352.
[15] 邵文静,孙伟伟,杨刚. 高光谱遥感影像纹理特征提取的对比分析[J]. 遥感技术与应用, 2021, 36(2): 431-440.