Experimental design of road traffic flow monitoring based on high-resolution remote sensing images

In order to monitor the traffic flow on the road surface, an experimental process of automatic road network extraction and vehicle monitoring using high-resolution remote sensing images was designed. Firstly, the D-Link network is used to perform binary semantic segmentation on the high-resolution remote sensing images to extract the road area, the coherence, edge expansion and smoothness of the extracted road are optimized by morphological closed operation processing for the preliminary extraction results, the road area is obtained by using the extracted road area as a mask, the vehicle target detection is carried out by using the deep learning algorithm, and the vehicle target density is represented by drawing the heat map. The experimental results show that the designed experiment can realize the monitoring of road traffic flow.