Sustainable Applications of Satellite Video Technology in Transportation Land Planning and Management

The accurate perception and prediction of traffic parameters like vehicles is essential to transportation land planning and management. Video satellites launched in recent years have brought promising opportunities into this field, providing a wide perspective and high frame frequency for extracting moving vehicles. However, detecting moving vehicles remains a challenge due to their small size, which diminishes shape and texture details, often causing them to blend with noise or other objects. To address this issue, we propose an effective method for moving vehicle detection in video satellites by integrating road maps. Experiments conducted on videos sampled from Jilin-1 and Skysat satellites show that our approach achieves F-scores of 0.98 and 0.87, respectively, which are superior to the three traditional methods, Gaussian mixture model (GMM), improved frame difference (IFD), and visual background extractor (ViBe). Our method can be used for accurate parameter estimation in real traffic, which paves the way for the application of video satellites in transportation land planning and management.