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Remote Sensing for Land & Resources    2018, Vol. 30 Issue (4) : 1-7     DOI: 10.6046/gtzyyg.2018.04.01
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Research progress of remote sensing application on transportation meteorological disasters
Lin WANG1, Xun LI2, Yunxuan BAO1(), Yi SHAO1
1. College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044,China
2. Beijing Meteorological Service, Beijing 100089,China
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Abstract  

Disastrous weather is the main factor which threatens the transportation security. It is difficult for traditional ground observation stations to monitor and forecast weather condition along roads to meet the transportation needs. Remote sensing (RS) technology can overcome this shortage, and shows great potentiality in transport weather research. Disastrous weather conditions will cause significant changes of geometrical or spectral features in RS images. Based on the research results obtained by domestic and foreign scientists, this paper mainly introduced the application of RS to transportation networks, weather disasters monitoring and forecasting, traffic flow, secondary disasters and loss assessment. Researches on application of RS to several typical weather conditions, such as heavy fog, rain storm, dust storm, low temperature, ice and snow coverage, were emphasized. There are good theoretical basis and practical background for RS to be applied to transportation meteorological disasters. Notable effects have been primarily manifested. Such researches will become the trend and the hot spot in transportation meteorology. With the development of RS quantification level, this application will acquire more progress and will provide the basis for disaster mechanism analysis, roads dynamical monitoring and forecasting.

Keywords remote sensing      road transportation      meteorological disaster      traffic flow      secondary disaster     
:  P49  
Corresponding Authors: Yunxuan BAO     E-mail: baoyx@nuist.edu.cn
Issue Date: 07 December 2018
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Lin WANG
Xun LI
Yunxuan BAO
Yi SHAO
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Lin WANG,Xun LI,Yunxuan BAO, et al. Research progress of remote sensing application on transportation meteorological disasters[J]. Remote Sensing for Land & Resources, 2018, 30(4): 1-7.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2018.04.01     OR     https://www.gtzyyg.com/EN/Y2018/V30/I4/1
[1] OFCM(Office of the Federal Coordinator for Meteorological Services and Supporting Research) . Weather Information for Surface Transportation:National Needs Assessment Report[R].Washington,DC:U.S. Department of Commerce, 2002.
[2] 刘东, 马社强, 牛学军 . 我国高速公路交通事故特点分析[J]. 中国人民公安大学学报(自然科学版), 2008,14(4):65-68.
[2] Liu D, Ma S Q, Niu X J . Feature analyses of traffic accidents on Chinese highways[J]. Journal of Chinese People’s Public Security University(Science and Technology), 2008,14(4):65-68.
[3] 丁德平, 李迅, 张德山 , 等. G2京津塘高速公路万辆车流的交通事故灾害与气象综合指数的关系[J]. 灾害学, 2012,27(3):107-110.
[3] Ding D P, Li X, Zhang D S , et al. The traffic accidents of Huabei freeway and its relation to the meteorological composite index[J]. Journal of Catastrophology, 2012,27(3):107-110.
[4] 刘玲, 孟庆昕, 刘晓东 . 高分卫星遥感技术在公路地质灾害损毁评估中的应用[J]. 公路, 2014,( 4):159-165.
[4] Liu L, Meng Q X, Liu X D . Application of high-resolution remote sensing technology on road geological disasters[J]. Highway, 2014,( 4):159-165.
[5] 孙涵, 孙照渤, 李亚春 . 雾的气象卫星遥感光谱特征[J]. 南京气象学院学报, 2004,27(3):289-301.
doi: 10.3969/j.issn.1674-7097.2004.03.001 url: http://d.wanfangdata.com.cn/Periodical/njqxxyxb200403001
[5] Sun H, Sun Z B, Li Y C . Meteorological satellite remote-sensing spectral characteristics of fog[J]. Journal of Nanjing Institute of Meteoroloty, 2004,27(3):289-301.
[6] Gurka J J. Using satellite data for forecasting fog and stratus dissipation [C]//Preprint 5th Conference on Weather Forecasting and Analysis. 1974: 54-57.
[7] Eyre J R, Brownscombe J L, Allam R J . Detection of fog at night using advanced very high resolution radiometer (AVHRR) imagery[J]. Meteorological Magazine, 1984,113:266-271.
[8] Turner J, Allam R J, Maine D R . A case study of the detection of fog at night using channels 3 and 4 on the advanced very high resolution radiometer (AVHRR)[J]. Meteorological Magazine, 1986,115:285-290.
[9] Bendix J, Thies B, Nauss T , et al. A feasibility study of daytime fog and low stratus detection with Terra/Aqua MODIS over land[J]. Meteorological Applications. 2006,13(2):111-125.
doi: 10.1017/S1350482706002180 url: http://doi.wiley.com/10.1017/S1350482706002180
[10] 居为民, 孙涵, 张忠义 , 等. 卫星遥感资料在沪宁高速公路大雾监测中的初步应用[J]. 遥感信息, 1997,( 3):25-27.
[10] Ju W M, Sun H, Zhang Z Y , et al. Preliminary application of sate-llite remote sensing data on heavy fog monitoring of Huning Highway[J]. Remote Sensing Information, 1997,( 3):25-27.
[11] 李亚春, 孙涵, 李湘阁 , 等. 用GMS-5气象卫星资料遥感监测白天雾的研究[J]. 南京气象学院学报, 2001,24(3):343-349.
doi: 10.3969/j.issn.1674-7097.2001.03.007 url: http://d.wanfangdata.com.cn/Periodical/njqxxyxb200103007
[11] Li Y C, Sun H, Li X G , et al. Study on detection of daytime fog using GMS-5 weather satellite data[J]. Journal of Nanjing Institute of Meteorology, 2001,24(3):343-349.
[12] 周红妹, 汤绪, 葛伟强 , 等. 城市和沿海大雾遥感自动检测和云、雾分离技术研究[J]. 高原气象, 2011,30(3):675-682.
doi:
[12] Zhou H M, Tang X, Ge W Q , et al. Automatic detection of heavy fog and cloud-fog separation technology in city and coastal area of eastern China based on meteorological satellite remote sensing ima-ge[J]. Plateau Meteorology, 2011,30(3):675-682.
[13] 刘文, 龚佃利, 赵玉金 , 等. GMS气象卫星在暴雨灾害遥感监测中的应用[J]. 国土资源遥感, 2002,14(4):14-16.doi: 10.6046/gtzyyg.2002.04.03.
doi: 10.3969/j.issn.1001-070X.2002.04.003 url: http://d.wanfangdata.com.cn/Periodical/gtzyyg200204003
[13] Liu W, Gong D L, Zhao Y J , et al. The application of GMS satellite to the remote sensing monitoring of rainstorm disaster[J]. Remote Sensing for Land and Resources, 2002,14(4):14-16.doi: 10.6046/gtzyyg.2002.04.03.
[14] 刘元波, 傅巧妮, 宋平 , 等. 卫星遥感反演降水研究综述[J]. 地球科学进展, 2011,26(11):1162-1172.
doi: 10.11867/j.issn.1001-8166.2011.11.1162 url: http://d.wanfangdata.com.cn/Periodical/dqkxjz201111006
[14] Liu Y B, Fu Q N, Song P , et al. Satellite retrieval of precipitation:An overview[J]. Advances in Earth Science, 2011,26(11):1162-1172.
[15] Huffman G J, Adler R F, Morrissey M M , et al. Global precipitation at one-degree daily resolution from multi-satellite observations[J]. Journal of Hydrometeorology, 2001,2(1):36-50.
doi: 10.1175/1525-7541(2001)002<0036:GPAODD>2.0.CO;2 url: http://journals.ametsoc.org/doi/abs/10.1175/1525-7541%282001%29002%3C0036%3AGPAODD%3E2.0.CO%3B2
[16] 刘健, 张文建, 朱元竞 , 等. 中尺度强暴雨云团云特征的多种卫星资料综合分析[J]. 应用气象学报, 2007,18(2):158-164.
doi: 10.11898/1001-7313.20070204 url: http://d.wanfangdata.com.cn/Periodical/yyqxxb200702004
[16] Liu J, Zhang W J, Zhu Y J , et al. Case study on cloud properties of heavy rainfall based upon satellite data[J]. Journal of Applied Meteorological Science, 2007,18(2):158-164.
[17] 方宗义, 张运刚, 郑新江 , 等. 用气象卫星遥感监测沙尘暴的方法和初步结果[J]. 第四纪研究, 2001,21(1):48-55.
doi: 10.3321/j.issn:1001-7410.2001.01.006 url: http://d.wanfangdata.com.cn/Periodical_dsjyj200101006.aspx
[17] Fang Z Y, Zhang Y G, Zheng X J , et al. The method for monitoring dust devil using satellite and preliminary results[J]. Quaternary Sciences, 2001,21(1):48-55.
[18] 敖艳红, 裴浩, 杨丽萍 , 等. 应用气象卫星遥感技术监测沙尘暴的研究[J]. 自然灾害学报, 2004,13(4):99-104.
doi: 10.3969/j.issn.1004-4574.2004.04.017 url: http://d.wanfangdata.com.cn/Periodical/zrzhxb200404017
[18] Ao Y H, Pei H, Yang L P , et al. Research on monitoring sand-dust storm using satellite remote sensing technique[J]. Journal of Natural Disasters, 2004,13(4):99-104.
[19] King J I F . The radiative heat transfer of planet earth[M] //James A V A.Scientific Users of Earth Satellites. Second Edition.Michigan:University of Michigan Press, 1958: 133-136.
[20] Smith W L, Woolf H M, Revercomb H E . Linear simultaneous solution for temperature and absorbing constituent profiles from radiance spectra[J]. Applied Optics, 1991,30(9):1117-1123.
doi: 10.1364/AO.30.001117 pmid: 20582114 url: https://www.osapublishing.org/abstract.cfm?URI=ao-30-9-1117
[21] 祝善友, 张桂欣, 尹球 , 等. 地表温度热红外遥感反演的研究现状及其发展趋势[J]. 遥感技术与应用, 2006,21(5):420-425.
doi: 10.3969/j.issn.1004-0323.2006.05.004 url: http://www.cqvip.com/QK/96858A/20065/23103208.html
[21] Zhu S Y, Zhang G X, Yin Q , et al. Actualities and development trends of the study on land surface temperature retrieving from thermal infrared remote sensing[J]. Remote Sensing Technology and Application, 2006,21(5):420-425.
[22] 黄晓东, 梁天刚 . 牧区雪灾遥感监测方法的研究[J]. 草业科学, 2005,22(12):10-16.
[22] Huang X D, Liang T G . Study on the remotely sensed monitoring method of snow disaster in pastoral area[J]. Pratacultural Science, 2005,22(12):10-16.
[23] 孙知文, 于鹏珊, 夏浪 , 等. 被动微波遥感积雪参数反演方法进展[J]. 国土资源遥感, 2015,27(1):9-15.doi: 10.6046/gtzyyg.2015.01.02.
doi: 10.6046/gtzyyg.2015.01.02
[23] Sun Z W, Yu P S, Xia L , et al. Progress in study of snow parameter inversion by passive microwave remote sensing[J]. Remote Sensing for Land and Resources, 2015,27(1):9-15.doi: 10.6046/gtzyyg.2015.01.02.
[24] 范一大, 王磊, 聂娟 , 等. 我国低温雨雪冰冻灾害遥感监测评估技术——研究与应用[J]. 自然灾害学报, 2008,17(6):21-25.
doi: 10.3969/j.issn.1004-4574.2008.06.005 url: http://www.cqvip.com/Main/Detail.aspx?id=29184848
[24] Fan Y D, Wang L, Nie J , et al. Remote sensing monitoring and assessment technology for cryogenic freezing rain and snow disasters in China:Research and application[J]. Journal of Natural Disasters, 2008,17(6):21-25.
[25] 鲁安新, 史正涛, 保翰璋 , 等. 川藏公路通麦至拉月茶场段遥感地质调查[J]. 遥感技术与应用, 2001,16(2):81-85.
[25] Lu A X, Shi Z T, Bao H Z , et al. The investigation of geology using remote sensing on Pailong-layue chachang of Chuanzang Road[J]. Remote Sensing Technology and Application, 2001,16(2):81-85.
[26] 李志中, 赵长英 . 川藏公路中段地质灾害现象的航空遥感研究[J]. 国土资源遥感, 1998,10(3):14-18.doi: 10.6046/gtzyyg.1998.03.04.
doi: 10.6046/gtzyyg.1998.03.04 url: http://www.cnki.com.cn/Article/CJFDTotal-GTYG803.003.htm
[26] Li Z Z, Zhao C Y . The aerial photo study of geological hazards in the middle part of Chuanzang Highway[J]. Remote Sensing for Land and Resources, 1998,10(3):14-18.doi: 10.6046/gtzyyg.1998.03.04.
[27] 赵春川, 李永树, 张帅毅 . 基于高分影像的道路损毁评估方法探讨[J]. 测绘, 2016,39(1):3-6.
[27] Zhao C C, Li Y S, Zhang S Y . Study on approach to road damage assessment based on high-resolution image[J]. Surveying and Mapping, 2016,39(1):3-6.
[28] 刘亚岚, 谭衢霖, 孙国庆 , 等. 交通遥感方法与应用[M]. 北京: 科学出版社, 2012.
[28] Liu Y L, Tan Q L, Sun G Q , et al. Methods and Application of Tra-ffic Remote Sensing[M]. Bejing: Science Press, 2012.
[29] Suchandt S, Runge H, Breit H , et al. Automatic extraction of traffic flows using TerraSAR-X along-track interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010,48(2):807-819.
doi: 10.1109/TGRS.2009.2037919 url: http://ieeexplore.ieee.org/document/5393895/
[30] 邱金恒, 陈洪滨, 王普才 , 等. 大气遥感研究展望[J]. 大气科学, 2005,29(1):131-136.
doi: 10.3878/j.issn.1006-9895.2005.01.15
[30] Qiu J H, Chen H B, Wang P C , et al. A prospect on future atmospheric remote sensing[J]. Chinese Journal of Atmospheric Sciences, 2005,29(1):131-136.
[31] 徐冠华, 柳钦火, 陈良富 , 等. 遥感与中国可持续发展:机遇和挑战[J]. 遥感学报, 2016,20(5):679-688.
doi: 10.11834/jrs.20166308 url: http://www.cqvip.com/QK/92457A/201605/670281638.html
[31] Xu G H, Liu Q H, Chen L F , et al. Remote sensing for China’s sustainable development:Opportunities and challenges[J]. Journal of Remote Sensing, 2016,20(5):679-688.
[32] 李新, 黄春林 . 数据同化——一种集成多源地理空间数据的新思想[J]. 科技导报, 2004,( 12):13-16.
doi: 10.3321/j.issn:1000-7857.2004.12.004 url: http://d.wanfangdata.com.cn/Periodical/kjdb200412004
[32] Li X, Huang C L . Data assimilation:A new means for multi-source geospatial data integration[J]. Science and Technology Review, 2004,( 12):13-16.
[33] 李小文, 王祎婷 . 定量遥感尺度效应刍议[J]. 地理学报, 2013,68(9):1163-1169.
[33] Li X W, Wang Y T . Prospects on future developments of quantitative remote sensing[J]. Acta Geographica Sinica, 2013,68(9):1163-1169.
[34] 栾海军, 田庆久, 余涛 , 等. 定量遥感升尺度转换研究综述[J]. 地球科学进展, 2013,28(6):657-664.
doi: 10.11867/j.issn.1001-8166.2013.06.0657 url: http://www.cqvip.com/QK/94287X/201306/46147571.html
[34] Luan H J, Tian Q J, Yu T , et al. Review of up-scaling of quantitative remote sensing[J]. Advances in Earth Science, 2013,28(6):657-664.
[35] 艾叶青, 王中平 . 基于遥感技术的交通流检测[J]. 公路与汽运, 2014,( 163):53-56.
[35] Ai Y Q, Wang Z P . Traffic flow detection based on remote sensing technology[J]. Highways and Automotive Applications, 2014,( 4):53-56.
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