Application of UAV in construction of smart city

doi:10.6046/gtzyyg.2018.04.02

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Abstract

Smart city is the inevitable choice for the development of China’s new urbanization. As a product of informatization and urban integration, smart city is gradually realized as an efficient and fine tool for managing people, money, material and things intelligently. The study of influence of UAV remote sensing technology in the construction of intelligent city plays an important role in accelerating the construction of smart cities. In this paper, the authors first reviewed the definition and development status of smart city, and then introduced the applications of unmanned aerial vehicle (UAV) from urban planning, illegal construction supervision, engineering environmental management, waste management, intelligent transportation, and other aspects.Finally, the development tendency was discussed.

Keywords unmanned aerial vehicle (UAV) remote sensing smart city application

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Issue Date: 07 December 2018

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	Changkui SUN
	Shanlei LIU
	Shengyao WANG
	Chao CHEN
	Quanfei SHEN
	Shanqiu SHI
	Wei WANG

Cite this article:

Changkui SUN,Shanlei LIU,Shengyao WANG, et al. Application of UAV in construction of smart city[J]. Remote Sensing for Land & Resources, 2018, 30(4): 8-12.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2018.04.02 OR https://www.gtzyyg.com/EN/Y2018/V30/I4/8

Fig.1 Constantly improved definition of smart city

[1]	陈鸿 . 智慧城市建设应运用“生态智慧”实现“智慧生态”[R]. 北京:WGDC2017地理信息开发者大会, 2017.
[1]	Chen H . Smart City Construction Should Use “Ecological Wisdom” to Achieve “Smart Ecology”[R]. Beijing:WGDC2017 Geographic Information Developers Conference, 2017.
[2]	崔铁军 . 地理信息科学在智慧城市建设中的作用[J]. 天津师范大学学报(自然科学版), 2017,37(3):47-53.
[2]	Cui T J . Role of geographic information science in the construction of smart city[J]. Journal of Tianjin Normal University (Natural Science Edition), 2017,37(3):47-53.
[3]	赵鹏, 陈阿霞 . 测绘地理信息在智慧城市建设中的作用[J]. 测绘与空间地理信息, 2015,38(3):127-129.
[3]	Zhao P, Chen A X . Discussion on influence of surveying and mapping information in construction of intelligent city[J]. Geomatics and Spatial Information Technology, 2015,38(3):127-129.
[4]	汪承义, 陈静波, 孟瑜 , 等. 新型航空遥感数据处理技术[M]. 北京: 化学工业出版社, 2016: 144-178.
[4]	Wang C Y, Chen J B, Meng Y , et al. Data Processing Technology in New Aviation Remote Sensing [M]. Beijing: Chemical Industry Press, 2016: 144-178.
[5]	刘先林服务( 适应/跟上)社会快速发展的地理信息产业[R]. 北京:中国测绘科学研究院, 2017.
[5]	Liu X L . Geographic Information Industry for Serving (Adapting/Keeping on) the Rapid Social Development [R]. Beijing:Chinses Academy of Surveying and Mapping, 2017.
[6]	熊璋智慧城市:创新的机遇与挑战[R]. 深圳:中国智慧城市产业技术创新战略联盟, 2013.
[6]	Xiong Z . Smart City:Opportunities and Challenges of Innovation [R]. Shenzhen:China Strategic Alliance of Smart City Industrial Technology Innovation, 2013.
[7]	王广斌, 崔庆宏 . 欧洲智慧城市建设案例研究:内容、问题及启示[J].中国科技论坛, 2013(7):123-128.
[7]	Wang G B, Cui Q H . Cases study of European smarter cities:Main points,problems and advices[J].Focus on Science and Technology in China,2013(7):123-128.
[8]	钟铃 . 新加坡智慧城市建设的经验及启示——以河南济原市城市建设为例[J]. 吉林工程技术师范学院学报, 2016,32(3):12-15. doi: 10.3969/j.issn.1009-9042.2016.03.004 url: http://www.cqvip.com/QK/88842X/201603/669163034.html
[8]	Zhong L . The experiences of smart city construction in Singapore and the enlightenment:Taking urban construction of Jiyuan,Henan as an example[J]. Journal of Jilin Teachers Institute of Engineering and Technology, 2016,32(3):12-15.
[9]	徐振强 . 中美智慧城市领域合作潜力分析与“十三五”合作思考[J].城市住宅, 2015(11):50-56.
[9]	Xu Z Q . Potential analysis of cooperation on smart city between US and China and thinking on the 13th “Five-year Plan” cooperation[J].City and House,2015(11):50-56.
[10]	刘伦, 刘合林, 王谦 , 等. 大数据时代的智慧城市规划:国际经验[J]. 国际城市规划, 2014,29(6):38-43,65. url: http://d.wanfangdata.com.cn/Periodical/gwcsgh201406006
[10]	Liu L, Liu H L, Wang Q , et al. Smart city planning in the era of big data:International experience[J]. Urban Planning International, 2014,29(6):38-43,65.
[11]	徐振强 . 智慧城市新思维[M]. 北京: 中国科学技术出版社, 2017: 203-210.
[11]	Xu Z Q. New Thinking in Smart City [M]. Beijing: Science and Technology of China Press, 2017: 203-210.
[12]	陈秉钊 . 当代城市规划导论[M]. 2版.北京: 中国建筑工业出版社, 2017: 25-37.
[12]	Chen B Z. An Introduction to Contemporary Urban Planning [M].2nd ed. Beijing: China Architecture and Building Press, 2017: 25-37.
[13]	杨李强, 张家根, 薛亮 . 无人机航拍在城市规划上的应用初探[J].城市管理, 2016(12):33-37.
[13]	Yang L Q, Zhang J G, Xue L . The application of aerial drones in city playing[J].Urban Management,2016(12):33-37.
[14]	王洛飞 . 无人机低空摄影测量在城市测绘保障中的应用前景[J]. 测绘与空间地理信息, 2014,37(2):217-219,222. doi: 10.3969/j.issn.1672-5867.2014.02.067 url: http://d.wanfangdata.com.cn/Periodical/dbch201402067
[14]	Wang L F . Unmanned aerial system applications and prospects in the urban survey and mapping[J]. Geomatics and Spatial Information Technology, 2014,37(2):217-219,222.
[15]	杨柳, 陈延辉, 岳德鹏 , 等. 无人机遥感影像的城市绿地信息提取[J]. 测绘科学, 2017,42(2):59-64.
[15]	Yang L, Chen Y H, Yue D P , et al. Information extraction of urban green space based on UAV remote sensing image[J]. Science of Surveying and Mapping, 2017,42(2):59-64.
[16]	曲林, 冯洋, 支玲美 , 等. 基于无人机倾斜摄影数据的实景三维建模研究[J]. 测绘与空间地理信息, 2015,38(3):38-39,43.
[16]	Qu L, Feng Y, Zhi L M , et al. Study on real 3D modeling of photographic data based on UAV[J]. Geomatics and Spatial Information Technology, 2015,38(3):38-39,43.
[17]	王琳, 吴正鹏, 姜兴钰 , 等. 无人机倾斜摄影技术在三维城市建模中的应用[J]. 测绘与空间地理信息, 2015,38(12):30-32. doi: 10.3969/j.issn.1672-5867.2015.12.009 url: http://d.wanfangdata.com.cn/Periodical/dbch201512009
[17]	Wang L, Wu Z P, Jiang X Y , et al. Application of the UAV oblique photography technique in 3D city modeling[J]. Geomatics and Spatial Information Technology, 2015,38(12):30-32.
[18]	杨国东, 王民水 . 倾斜摄影测量技术应用及展望[J]. 测绘与空间地理信息, 2016,39(1):13-15,18.
[18]	Yang G D, Wang M S . The tilt photographic measuration technique and expectation[J]. Geomatics and Spatial Information Technology, 2016,39(1):13-15,18.
[19]	王爽, 林璐, 徐健 , 等. 无人机辅助违章建筑监测[J]. 测绘标准化, 2017,33(1):39-41. url: http://www.cqvip.com/QK/96859X/201701/671696836.html
[19]	Wang S, Lin L, Xu J , et al. Illegal buildings monitoring with UAV[J]. Standardization of Surveying and Mapping, 2017,33(1):39-41.
[20]	杜培军, 谭琨, 夏俊士 , 等. 城市环境遥感的方法与实践[M]. 北京: 科学出版社, 2013: 30-35.
[20]	Du P J, Tan K, Xia J S , et al. Methods and Practice of Remote Sensing in Urban Environment[M]. Beijing: Science Press, 2013: 30-35.
[21]	张红, 李纯 . 国际科技动态跟踪——城市垃圾处理[M]. 北京: 清华大学出版社, 2013: 1-30.
[21]	Zhang H, Li C. International Technology Track:Urban Garbage Disposal [M]. Beijing: Tsinghua University Press, 2013: 1-30.
[22]	邱文城, 李土生, 吴祥发 , 等. 基于低空域小型无人机航拍技术的城市交通拥堵管控研究[J].科技创新与应用, 2017(16):25-26. url: http://d.wanfangdata.com.cn/Periodical/qgsj201716015
[22]	Qiu W C, Li T S, Wu X F , et al. Study on control of traffic jam based on aerial aerial technology of small UAV in lower spatial area[J].Innovation and Application of Science and Technology,2017(16):25-26.
[23]	李超 . 基于无人机的安防监控系统在智慧城市中的应用前景与实现[J].科技广场, 2014(6):72-75. doi: 10.3969/j.issn.1671-4792.2014.06.017 url: http://d.wanfangdata.com.cn/Periodical/kjgc201406017
[23]	Li C . Application prospect and implementation of security surveillance system based on unmanned aerial vehicle in smart city[J].Technology Square,2014(6):72-75.
[24]	熊殷 . 小型无人机在城管执法工作中的应用前景[J]. 上海城市管理, 2017,26(1):84-87.
[24]	Xiong Y . The application prospect of mini unmanned aerial vehicle in urban management law enforcement[J]. Shanghai Urban Management, 2017,26(1):84-87.
[25]	姜会义, 张学珍, 张学萍 , 等. 车载无人机在测绘应急保障中的应用[J]. 测绘与空间地理信息, 2016,39(7):171-172,178. url: http://d.wanfangdata.com.cn/Periodical/dbch201607055
[25]	Jiang H Y, Zhang X Z, Zhang X P , et al. The application of vehicle UAV in the surveying and mapping emergency safeguard[J]. Geomatics and Spatial Information Technology, 2016,39(7):171-172,178.
[26]	曹素妨 .无人机 , 让智能媒体时代再一次悸动[J].中国传媒科技, 2015(5):14-20.
[26]	Cao S F . UAV:Smart media era once again throbbing[J].Science and Technology for China’s Mass Media,2015(5):14-20.

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