Extraction of road congestion information by change detection of multi-temporal satellite observing images
- Yan Wang, Hong Zhou, Hua Xu, Zhonghua He, Liping Lei
- Corresponding Author
- Yan Wang
Available Online November 2016.
- https://doi.org/10.2991/aest-16.2016.13How to use a DOI?
- road congestion; change detection; satellite observation; multi-temporal.
- Road congestion has been significantly affecting our live and environment. It is important to get the information of traffic congestion in a real time. In this study, we present an approach by the detecting the vehicles to view the traffic conditions using the satellite observing image from Gaofen-4 (GF-4). GF-4 is a fixed satellite which obtains the images with a high timely interval of 20s but its spatial resolution is 50m. This study seeks the application of this satellite observation to get the information of traffic congestion using its advantage of high time-frequency observation by the change detection of images over the road when the different number of vehicle are occupying over the road. We used the high spatial resolution (1m) images of Gaofen-2 (GF-2) to simulate the scenario of different road congestions, after that the simulated images is transferred into Gaofen-4 data by down the spatial resolution to 50m. The result of our study shows that heavy road congestion over the highway, the length of road congestion is larger than 1km, can be detected from 50m GF-4 images. The result demonstrates that the observation of GF-4 could be an alternate way for the real time monitoring of traffic condition.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yan Wang AU - Hong Zhou AU - Hua Xu AU - Zhonghua He AU - Liping Lei PY - 2016/11 DA - 2016/11 TI - Extraction of road congestion information by change detection of multi-temporal satellite observing images BT - 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/aest-16.2016.13 DO - https://doi.org/10.2991/aest-16.2016.13 ID - Wang2016/11 ER -