Road vector database plays an important role in post-earthquake relief, rescue and reconstruction.However, due to data privacy policy, it is difficult for general users to obtain high-precision and complete vector dat...Road vector database plays an important role in post-earthquake relief, rescue and reconstruction.However, due to data privacy policy, it is difficult for general users to obtain high-precision and complete vector data of road network. The OpenStreetMap(OSM) project provides an open-source, global free road dataset, but there are inevitable geo-localization/projection errors, which will lead to large errors in hazard survey analysis. In this paper, we proposed a road centerline correction method using postearthquake aerial images. Under the constraint of the vector road map(OpenStreetMap), we rectified the centerline by the context feature and spectral gradient feature of post-event images automatically.The experiment implemented on 0.5 m/pixel post-event aerial images of Haiti, 2010, showed that the completeness and extraction quality of proposed method were over 90% and 80% without any manual intervention.展开更多
基金supported by Scientific Research Fund of Institute of Seismology and Institute of Crustal Dynamics,China Earthquake Administration(Grant No.IS2018262761)
文摘Road vector database plays an important role in post-earthquake relief, rescue and reconstruction.However, due to data privacy policy, it is difficult for general users to obtain high-precision and complete vector data of road network. The OpenStreetMap(OSM) project provides an open-source, global free road dataset, but there are inevitable geo-localization/projection errors, which will lead to large errors in hazard survey analysis. In this paper, we proposed a road centerline correction method using postearthquake aerial images. Under the constraint of the vector road map(OpenStreetMap), we rectified the centerline by the context feature and spectral gradient feature of post-event images automatically.The experiment implemented on 0.5 m/pixel post-event aerial images of Haiti, 2010, showed that the completeness and extraction quality of proposed method were over 90% and 80% without any manual intervention.
