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A review of road extraction from remote sensing images
Journal of Traffic and Transportation Engineering (English ed. Online), 2016 As a significant role for traffic management, city planning, road monitoring, GPS navigation and map updating, the technology of road extraction from a remote sensing (RS) image has been a hot research topic in recent years.
Weixing Wang +5 more
doaj +5 more sources
Road Extraction with Satellite Images and Partial Road Maps [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2023 Road extraction is a process of automatically generating road maps mainly from satellite images. Existing models all target to generate roads from the scratch despite that a large quantity of road maps, though incomplete, are publicly available (e.g. those from OpenStreetMap) and can help with road extraction.
Qianxiong Xu +3 more
arxiv +5 more sources
Road Extraction from High Resolution Remote Sensing Images Based on Vector Field Learning [PDF]
Sensors, 2021 Accurate and up-to-date road network information is very important for the Geographic Information System (GIS) database, traffic management and planning, automatic vehicle navigation, emergency response and urban pollution sources investigation.
Peng Liang +4 more
doaj +2 more sources
Multiscale Road Extraction in Remote Sensing Images. [PDF]
Comput Intell Neurosci, 2019 Recent advances in convolutional neural networks (CNNs) have shown impressive results in semantic segmentation. Among the successful CNN-based methods, U-Net has achieved exciting performance. In this paper, we proposed a novel network architecture based on U-Net and atrous spatial pyramid pooling (ASPP) to deal with the road extraction task in the ...
Wulamu A, Shi Z, Zhang D, He Z.
europepmc +5 more sources
Remote Sensing Road Extraction by Road Segmentation Network [PDF]
Applied Sciences, 2021 Road extraction from remote sensing images has attracted much attention in geospatial applications. However, the existing methods do not accurately identify the connectivity of the road. The identification of the road pixels may be interfered with by the
Jiahai Tan, Ming Gao, Kai Yang, Tao Duan
doaj +3 more sources
Road Extraction in SAR Images Using Ordinal Regression and Road-Topology Loss [PDF]
Remote Sensing, 2021 The road extraction task is mainly composed of two subtasks, namely, road detection and road centerline extraction. As the road detection task and road centerline extraction task are strongly correlated, in this paper, we introduce a multitask learning ...
Xiaochen Wei, Xiaolei Lv, Kaiyu Zhang
doaj +3 more sources
Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds [PDF]
Sensors, 2016 Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a ...
Li Yan +5 more
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Fully Convolutional Network for Automatic Road Extraction from Satellite Imagery [PDF]
arXiv, 2018 Analysis of high-resolution satellite images has been an important research topic for traffic management, city planning, and road monitoring. One of the problems here is automatic and precise road extraction. From an original image, it is difficult and computationally expensive to extract roads due to presences of other road-like features with straight
Alexander V. Buslaev +3 more
arxiv +3 more sources
Automatic Road Centerline Extraction from Imagery Using Road GPS Data [PDF]
Remote Sensing, 2014 Road centerline extraction from imagery constitutes a key element in numerous geospatial applications, which has been addressed through a variety of approaches.
Chuqing Cao, Ying Sun
doaj +3 more sources
Remote Sensing, 2023 Road extraction is crucial in urban planning, rescue operations, and military applications. Compared to traditional methods, using deep learning for road extraction from remote sensing images has demonstrated unique advantages.
Xudong Wang +5 more
doaj +1 more source