Congestion Analysis Based on Remote Sensing Images

Hanning Yuan; Jiakai Yang; Xiaolei Li; Shengyu Ma

doi:10.1007/978-981-13-0893-2_37

Congestion Analysis Based on Remote Sensing Images

Hanning Yuan^*
, Jiakai Yang
, Xiaolei Li
, Shengyu Ma

^*此作品的通讯作者

Beijing Institute of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

Most Congestion analysis are based on the urban traffic video surveillance, which depend on the quality of existing surveillance equipments. In this paper, we propose a novel method to perform congestion analysis by utilizing remote sensing images for undeveloped areas or disaster-affected areas where lack of traffic video surveillance. Firstly, the vehicles and extract road area is detected from remote sensing images using objects detection technique. Then the number of Vehicles in the road are counted and mapped into data instances. Finally, density-based clustering algorithm is adopted to find the locations which are probably the Congestion points. The experimental results on real world datasets demonstrate that the proposed method can perform congestion analysis effectively.

源语言	英语
主期刊名	Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers
编辑	Fuling Bian, Hanning Yuan, Jing Geng, Chuanlu Liu, Tisinee Surapunt
出版商	Springer Verlag
页	345-352
页数	8
ISBN（印刷版）	9789811308925
DOI	https://doi.org/10.1007/978-981-13-0893-2_37
出版状态	已出版 - 2018
已对外发布	是
活动	5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017 - Chiang Mai, 泰国期限: 8 12月 2017 → 10 12月 2017

出版系列

姓名	Communications in Computer and Information Science
卷	848
ISSN（印刷版）	1865-0929

会议

会议	5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017
国家/地区	泰国
市	Chiang Mai
时期	8/12/17 → 10/12/17

联合国可持续发展目标

此成果有助于实现下列可持续发展目标：

可持续发展目标 11 可持续城市和社区

访问文件

10.1007/978-981-13-0893-2_37

其它文件与链接

链接到 Scopus 的出版物

引用此

Yuan, H., Yang, J., Li, X., & Ma, S. (2018). Congestion Analysis Based on Remote Sensing Images. 在 F. Bian, H. Yuan, J. Geng, C. Liu, & T. Surapunt (编辑), Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers (页码 345-352). (Communications in Computer and Information Science; 卷 848). Springer Verlag. https://doi.org/10.1007/978-981-13-0893-2_37

Yuan, Hanning ; Yang, Jiakai ; Li, Xiaolei 等. / Congestion Analysis Based on Remote Sensing Images. Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. 编辑 / Fuling Bian ; Hanning Yuan ; Jing Geng ; Chuanlu Liu ; Tisinee Surapunt. Springer Verlag, 2018. 页码 345-352 (Communications in Computer and Information Science).

@inproceedings{dd456fed339e444ab32df9fbd6860865,

title = "Congestion Analysis Based on Remote Sensing Images",

abstract = "Most Congestion analysis are based on the urban traffic video surveillance, which depend on the quality of existing surveillance equipments. In this paper, we propose a novel method to perform congestion analysis by utilizing remote sensing images for undeveloped areas or disaster-affected areas where lack of traffic video surveillance. Firstly, the vehicles and extract road area is detected from remote sensing images using objects detection technique. Then the number of Vehicles in the road are counted and mapped into data instances. Finally, density-based clustering algorithm is adopted to find the locations which are probably the Congestion points. The experimental results on real world datasets demonstrate that the proposed method can perform congestion analysis effectively.",

keywords = "Congestion analysis, Remote sensing image, Road extraction, Vehicle detection",

author = "Hanning Yuan and Jiakai Yang and Xiaolei Li and Shengyu Ma",

note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Singapore Pte Ltd.; 5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017 ; Conference date: 08-12-2017 Through 10-12-2017",

year = "2018",

doi = "10.1007/978-981-13-0893-2\_37",

language = "English",

isbn = "9789811308925",

series = "Communications in Computer and Information Science",

publisher = "Springer Verlag",

pages = "345--352",

editor = "Fuling Bian and Hanning Yuan and Jing Geng and Chuanlu Liu and Tisinee Surapunt",

booktitle = "Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers",

address = "Germany",

}

Yuan, H, Yang, J, Li, X & Ma, S 2018, Congestion Analysis Based on Remote Sensing Images. 在 F Bian, H Yuan, J Geng, C Liu & T Surapunt (编辑), Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. Communications in Computer and Information Science, 卷 848, Springer Verlag, 页码 345-352, 5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017, Chiang Mai, 泰国, 8/12/17. https://doi.org/10.1007/978-981-13-0893-2_37

Congestion Analysis Based on Remote Sensing Images. / Yuan, Hanning; Yang, Jiakai; Li, Xiaolei 等.
Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. 编辑 / Fuling Bian; Hanning Yuan; Jing Geng; Chuanlu Liu; Tisinee Surapunt. Springer Verlag, 2018. 页码 345-352 (Communications in Computer and Information Science; 卷 848).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Congestion Analysis Based on Remote Sensing Images

AU - Yuan, Hanning

AU - Yang, Jiakai

AU - Li, Xiaolei

AU - Ma, Shengyu

PY - 2018

Y1 - 2018

N2 - Most Congestion analysis are based on the urban traffic video surveillance, which depend on the quality of existing surveillance equipments. In this paper, we propose a novel method to perform congestion analysis by utilizing remote sensing images for undeveloped areas or disaster-affected areas where lack of traffic video surveillance. Firstly, the vehicles and extract road area is detected from remote sensing images using objects detection technique. Then the number of Vehicles in the road are counted and mapped into data instances. Finally, density-based clustering algorithm is adopted to find the locations which are probably the Congestion points. The experimental results on real world datasets demonstrate that the proposed method can perform congestion analysis effectively.

AB - Most Congestion analysis are based on the urban traffic video surveillance, which depend on the quality of existing surveillance equipments. In this paper, we propose a novel method to perform congestion analysis by utilizing remote sensing images for undeveloped areas or disaster-affected areas where lack of traffic video surveillance. Firstly, the vehicles and extract road area is detected from remote sensing images using objects detection technique. Then the number of Vehicles in the road are counted and mapped into data instances. Finally, density-based clustering algorithm is adopted to find the locations which are probably the Congestion points. The experimental results on real world datasets demonstrate that the proposed method can perform congestion analysis effectively.

KW - Congestion analysis

KW - Remote sensing image

KW - Road extraction

KW - Vehicle detection

UR - https://www.scopus.com/pages/publications/85049022715

U2 - 10.1007/978-981-13-0893-2_37

DO - 10.1007/978-981-13-0893-2_37

M3 - Conference contribution

AN - SCOPUS:85049022715

SN - 9789811308925

T3 - Communications in Computer and Information Science

SP - 345

EP - 352

BT - Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers

A2 - Bian, Fuling

A2 - Yuan, Hanning

A2 - Geng, Jing

A2 - Liu, Chuanlu

A2 - Surapunt, Tisinee

PB - Springer Verlag

T2 - 5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017

Y2 - 8 December 2017 through 10 December 2017

ER -

Congestion Analysis Based on Remote Sensing Images

摘要

出版系列

会议

联合国可持续发展目标

访问文件

其它文件与链接

指纹

引用此