@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",
}
