Road Extraction and Distress Assessment by Spaceborne, Airborne and Terrestrial Platforms
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 43529
Special Issue Editors
Interests: UAV; aircraft and satellite remote sensing; multispectral and hyperspectral remote sensing; imaging spectroscopy; asphalt pavement analysis by remote sensing techniques; analysis of bituminous mixtures by digital imaging processing; characterization of traditional and bio-plastics by hyperspectral devices; photogrammetry and 3D modelling; GIS and geospatial statistics; calibration/validation; land use land cover change; downscaling techniques
Special Issues, Collections and Topics in MDPI journals
Interests: hyperspectral and multispectral imagery; quantitative remote sensing; AI applications; road pavement distress assessment; remote sensing for natural disaster assessment
Special Issues, Collections and Topics in MDPI journals
Interests: GIS; GNSS; remote sensing; photogrammetry; cultural heritage surveys
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
As known, road maintenance has a deep impact on authorities' financial plans. Currently, to reach standard safety conditions, numerous PMS systems and indicators are used for pavement assessment such as the Pavement Condition Index (PCI), or the Structure Index (SI) but, both don’t allow a rapid synoptic pavement investigation for large road networks. Moreover, due to their need to be calculated from in situ surveys, the acquisition of such indices is expensive and time consuming. Hence, in the last decade the advancement of automated or semi-automated procedures is stimulated for pavement distress detection and analysis. Here because, a great interest has grown-up in the scientific community to the adoption of remote sensed non-invasive techniques in several experimental settings.
Remote sensing represents an interesting alternative and challenge for road extraction and pavement aging condition monitoring by using both passive and active satellite sensors. Moreover, the increase in the adoption of Artificial Intelligence (AI) and Big Data based on remote sensing allows us to manage and share in a more efficient way such huge data frames.
Furthermore, the use of Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) show an increase of their implications on these topics and are frequently related to field surveys. Such kinds of technologies attain higher outcomes when remote sensed data are correlated to the standardized parameters.
The aim of this special issue is to collect research or review papers focusing on innovative and multidisciplinary approaches on road extraction or distress assessment using spaceborne, aerial and terrestrial platforms in different experimental surroundings. Additionally, papers focusing on new field approaches related to spectroscopy, photogrammetry, GPR, LIDAR, laser scanners, etc. are also welcome.
Dr. Alessandro Mei
Prof. Dr. Xianfeng Zhang
Prof. Dr. Valerio Baiocchi
Guest Editors
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Keywords
- road extraction and pavement distress analysis
- spaceborne, airborne and terrestrial platforms
- UAV and UGV
- multispectral and hyperspectral Remote Sensing
- time series analysis and change detection
- imaging spectroscopy
- Pavement Condition Index, Structure Index, Serviceability Index
- Pavement Management systems (PMS)
- bituminous mixtures analyses by non-invasive techniques
- photogrammetry and 3D modelling
- GIS modelling for management plan
- Decision Support Systems based on remote sensed techniques
- geomatics
- AI
- deep learning
- data fusion
- Ground Penetrating Radar (GPR)
- Accelerated Pavement Tests (APT)
- lidar and laser scanning
- geometric reconstruction
- pattern recognition
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