The reliable and accurate detection of bridges plays an important role in imaging-driven transportation surveillance. It is capable of timely providing the traffic information, leading to safer and more convenient transportation. However, the visual quality of observed images is often inevitably reduced owing to the adverse weather conditions, e.g., haze and low lightness. It is still difficult to adopt the existing powerful deep learning methods to reliably and accurately detect the bridges under different imaging conditions. To achieve satisfactory bridge detection results, we first propose to exploit the data augmentation strategy and physical imaging method to generate the natural-looking experimental dataset, which contains latent high-quality images and their hazy and low-light versions. We then investigate how to further promote the deep learning-based bridge detection methods through the manually generated dataset. It is obvious that the generalization abilities of these deep neural networks are significantly improved using this data augmentation strategy. In this work, we constructed an original dataset consisting of 3500 images of size 900×600, collected under normal imaging condition. Extensive detection experiments will be performed based on the augmented dataset. Experimental results have demonstrated that our automatic bridge detection framework could generate more reliable and accurate results compared with existing detection methods.

Beijing is one of the largest cities in China, which has suffered from land subsidence for a long time. According to the study from 2005 to 2017, the maximum subsidence rate of Beijing is more than 10 cm/year. This paper will use Sentinel-1A TOPS data for the first time to reveal the land subsidence of Beijing from 2017 to 2018 by using time series interferometry. SBAS-InSAR technology was used for time series analysis. The annual mean subsidence rate and time series subsidence of Beijing were obtained. The results show that the east of Chaoyang district and the northwest of Tongzhou district were the severe subsidence areas in Beijing, and the subsidence rate is more than 10 cm/year, which indicates that the subsidence area in Beijing is continuous in recent years, and corresponding measures should be taken by the government.