Results 31 to 40 of about 2,732,569 (203)
ROBUST APPROACH FOR URBAN ROAD SURFACE EXTRACTION USING MOBILE LASER SCANNING 3D POINT CLOUDS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Road surface extraction is crucial for 3D city analysis. Mobile laser scanning (MLS) is the most appropriate data acquisition system for the road environment because of its efficient vehicle-based on-road scanning opportunity.
A. Nurunnabi +4 more
doaj +1 more source
Road Extraction from High-Resolution Remote Sensing Images via Local and Global Context Reasoning
Remote Sensing, 2023 Road extraction from high-resolution remote sensing images is a critical task in image understanding and analysis, yet it poses significant challenges because of road occlusions caused by vegetation, buildings, and shadows.
Jie Chen +7 more
doaj +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Obtaining Road information from high-resolution remote sensing images is gaining attention in intelligent transportation systems. Existing road extraction methods tend to improve road connectivity with graph convolution or global attention, however ...
Ziqing Luo +5 more
semanticscholar +1 more source
Leveraging optical and SAR data with a UU-Net for large-scale road extraction
International Journal of Applied Earth Observations and Geoinformation, 2021 Road datasets are fundamental and imperative for traffic management and urban planning. Different high-resolution optical remote sensing images are widely used for automatic road extraction but the results are usually limited to local scale and spectral ...
Yinyi Lin +6 more
doaj +1 more source
Remote Sensing, 2022 Road information plays a fundamental role in many applications. However, at present, it is difficult to extract road information from the traditional nighttime light images in view of their low spatial and spectral resolutions.
Dingkun Chang +3 more
doaj +1 more source
Efficient Occluded Road Extraction from High-Resolution Remote Sensing Imagery
Remote Sensing, 2021 Road extraction is important for road network renewal, intelligent transportation systems and smart cities. This paper proposes an effective method to improve road extraction accuracy and reconstruct the broken road lines caused by ground occlusion ...
Dejun Feng +4 more
doaj +1 more source
LGNet: Location-Guided Network for Road Extraction From Satellite Images
IEEE Transactions on Geoscience and Remote Sensing, 2023 Road connectivity is vital in road extraction for accurate vehicle navigation. However, the segmentation-based methods fail to model the connectivity resulting in broken road segments. Therefore, we propose a location-guided network (LGNet) for promoting
Jingtao Hu +4 more
semanticscholar +1 more source
D-FusionNet: road extraction from remote sensing images using dilated convolutional block
GIScience & Remote Sensing, 2023 Deep learning techniques have been applied to extract road areas from remote sensing images, leveraging their efficient and intelligent advantages.
Ruixuan Zhang +8 more
semanticscholar +1 more source
Extracting Flooded Roads by Fusing GPS Trajectories and Road Network [PDF]
ISPRS International Journal of Geo-Information, 2019 Urban roads are the lifeline of urban transportation and satisfy the commuting and travel needs of citizens. Following the acceleration of urbanization and the frequent extreme weather in recent years, urban waterlogging is occurring more than usual in summer and has negative effects on the urban traffic networks. Extracting flooded roads is a critical
Shiying She +4 more
openaire +2 more sources
Remote Sensing, 2023 Extracting roads from remote sensing images is of significant importance for automatic road network updating, urban planning, and construction.
Shaofu Lin +8 more
semanticscholar +1 more source