Road Extraction and Distress Assessment by Spaceborne, Airborne and Terrestrial Platforms (Second Edition)

Dear Colleagues,

To reach standard safety conditions, numerous Pavement Management Systems are used for pavement assessment, but don’t allow a rapid and synoptic examination for large road networks. Moreover, due to their need to be calculated from in situ surveys, the acquisition of pavement condition indices is expensive and time consuming. Hence, in the last decade Remote Sensing advancements allow to pursue newest automated or semi-automated procedures 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.

Here because the aim of this special issue is to collect research or review papers focusing on innovative approaches on road distress assessment or extraction using spaceborne/aerial (Remote Sensing) and Unmanned Aerial Vehicles (UAVs) (Proximal Sensing) platforms in different experimental surroundings. Additionally, papers focusing on new approaches related to Near Sensing technologies such as Unmanned Ground Vehicles (UGVs) or field spectroscopy, considered preparators’ for RS analysis, are also welcome.

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. Also, geo-statistics can help to improve the knowledge of spectral variability related to pavement distress.

Furthermore, the use of PS techniques shows an increase of their implications on these topics and are frequently related to LIDAR, multi and hyperspectral cameras and field surveys. Such kinds of technologies attain higher outcomes when remote sensed data are correlated to the standardized parameters.

The previous volume of ‘Road Extraction and Distress Assessment by Spaceborne, Airborne and Terrestrial Platforms’, was a great success. 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.

Dr. Alessandro Mei
Prof. Dr. Valerio Baiocchi
Prof. Dr. Xianfeng Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• road extraction and pavement distress analysis
• very hight resolution satellite imagery
• airborne remote sensing
• synthetic aperture radar (SAR)
• UAV and UGV
• multispectral and hyperspectral remote sensing
• time series analysis
• change detection
• imaging spectroscopy
• pavement management systems (PMS)
• photogrammetry and 3D modelling
• GIS modelling for management plan
• decision support systems based on remote sensed techniques
• geostatistics
• artificial intelligence
• ML (machine learning)
• CNN
• deep learning
• data fusion
• light detection and ranging (LiDAR)
• pattern recognition

• Road Extraction and Distress Assessment by Spaceborne, Airborne and Terrestrial Platforms in Remote Sensing (13 articles)