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Special Issue "Feature Papers of Engineering Remote Sensing"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".

Deadline for manuscript submissions: 8 December 2023 | Viewed by 2800

Special Issue Editors

1. Department of Civil, Environmental, Land, Building Engineering and Chemistry - DICATECh - Polytechnic University of Bari, 70126 Bari, Italy
2. Geoinformatics Division, Department of Urban Planning & Environment, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
Interests: change detection; SAR; photogrammetry; deep learning; land cover mapping; geo big data; time series analysis; urban remote sensing; forest fire; mobile mapping
Special Issues, Collections and Topics in MDPI journals
Department of Civil, Environmental and Mechanical Engineering, University of Trento, 38122 Trento, Italy
Interests: methods for spatial and temporal filtering of remote sensed data and digital surface models; GNSS for water resources; SAR and optical remote sensing for river and lake science
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The importance of remote sensing methods and techniques for different engineering branches has been well known for several decades, even before the deployment of the first satellite sensor for Earth observation. Indeed, it has been recognized since the first applications of aerial and close-range photogrammetry to mapping, digital terrain and man-made object modeling, ground and infrastructures geomatic monitoring, cultural heritage documentation, and industrial metrology. These still constitute most of the fields of remote sensing applications in engineering.

Anyway, continuous technology improvement (with respect to sensors and computational facilities) has made available more and more data, in an increasingly distributed and shared way, and at a higher and higher rate; thanks to this, new important application fields have been opened, such as natural hazard and disasters monitoring and documentation, and intelligent transport systems. In addition, requests for new demanding applications have asked for new data quality assessment, integration, and analysis methods.

The main aim of this Issue is therefore the presentation and discussion of new sensors and data processing methods, in relation to the above-mentioned application fields, related to civil, constructional, environmental, industrial safety, and civil protection engineering. Manuscripts for this important Issue of Remote Sensing will be accepted by the editorial office, the Editor-in-Chief and editorial board members by invitation only.

Prof. Dr. Mattia Crespi
Prof. Dr. Andrea Nascetti
Prof. Dr. Alfonso Vitti
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at 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.


  • sensors
  • methods
  • data processing
  • civil engineering
  • constructional engineering
  • environmental engineering
  • civil protection
  • industrial safety

Published Papers (1 paper)

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19 pages, 2435 KiB  
Petri-Net Based Multi-Objective Optimization in Multi-UAV Aided Large-Scale Wireless Power and Information Transfer Networks
Remote Sens. 2021, 13(13), 2611; - 03 Jul 2021
Cited by 5 | Viewed by 1834
Power consumption in wireless sensor networks is high, and the lifetime of a battery has become a bottleneck, restricting network performance. Wireless power transfer with a ground mobile charger is vulnerable to interference from the terrain and other factors, and hence it is [...] Read more.
Power consumption in wireless sensor networks is high, and the lifetime of a battery has become a bottleneck, restricting network performance. Wireless power transfer with a ground mobile charger is vulnerable to interference from the terrain and other factors, and hence it is difficult to deploy in practice. Accordingly, a novel paradigm is adopted where a multi-UAV (unmanned aerial vehicle) with batteries can transfer power and information to SDs (sensor devices) in a large-scale sensor network. However, there are discrete events, continuous process, time delay, and decisions in such a complicated system. From the perspective of a hybrid system, a hybrid colored cyber Petri net system is proposed here to depict and analyze this problem. Furthermore, the energy utilization rate and information collection time delay are conflict with each other; therefore, UAV-aided wireless power and information transfer is formulated as a multi-objective optimization problem. For this reason, the MAC-NSGA II (multiple ant colony-nondominated sorting genetic algorithm II) is proposed in this work. Firstly, the optimal trajectory of multiple UAVs was obtained, and on this basis, the above two objectives were optimized simultaneously. Large-scale simulation results show that the proposed algorithm is superior to NSGA II and MOEA/D in terms of energy efficiency and information collection delay. Full article
(This article belongs to the Special Issue Feature Papers of Engineering Remote Sensing)
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