Special Issue "Drones for Natural Hazards"

A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drones in Ecology".

Deadline for manuscript submissions: 31 October 2023 | Viewed by 3128

Special Issue Editors

Department of Civil and Environmental Engineering, Politecnico di Milano, P.zza Leonardo da Vinci, 32, Building 3, 20133 Milano, Italy
Interests: disaster; landslides; remote sensing; UAV; photogrammetry; disaster; monitoring; mapping; geospatial artificial intelligence; open science
Department of Architecture, Built Environment and Construction Engineering (ABC), Politecnico di Milano, Via Ponzio 31, 20133 Milan, Italy
Interests: photogrammetry; laser scanning; automation; 3D modelling; monitoring; computer vision
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Special Issue Information

Dear Colleagues,

In recent years, unmanned aerial vehicles (UAVs) have undergone incredible technological development and, at the same time, developed an even wider application range. Consecutively, systems that offer high-resolution/-quality data products acquired in a non-invasive and remote manner are very widely adopted in the disaster risk management cycle—preparedness, response, recovery, and mitigation. Scholars and professionals alike are implementing and continue to develop applications of UAVs and intelligent swarms for a variety of tasks ranging from hazard mapping and monitoring to more operational ones such as emergency response and search and rescue.

In addition, UAV derived high resolutions datasets from passive or active sensors, are great assets for improving and validating spaceborne applications in the disaster domain.

Furthermore, the data products from such aerial systems are easy to implement with geographic information systems and combined with geospatial artificial intelligence are further advancing the progress and develop the scientific research, and decision-making processes.

Finally, the availability of consumer grade UAVs at affordable price is a main driving factor for adopting citizen science contribution to the risk-related activities.

We are pleased to invite you to submit manuscripts to the MDPI journal Drones for our Special Issue “Drones for Natural Hazards”. Articles should be related to but not limited by the considered topics:

  • UAV photogrammetry and remote sensing
  • Change detection
  • Emergency response
  • RTK/PPK- and GCP- based orientation and processing methods
  • Novel cloud processing services
  • New approaches for hazard monitoring and mapping
  • UAV Citizen science through collaborative approaches and platforms
  • Integration and validation and of satellite-based outputs through UAV-based observations

Dr. Vasil Yordanov
Dr. Luigi Barazzetti
Prof. Dr. Maria Antonia Brovelli
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. Drones is an international peer-reviewed open access monthly 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 2000 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.

 

Keywords

  • UAV
  • drones
  • hazards
  • mapping
  • geographic information science
  • remote sensing
  • landslides
  • floods
  • wildfires
  • volcanoes
  • disasters
  • relief

Published Papers (2 papers)

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Research

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Article
Estimating Landslide Surface Displacement by Combining Low-Cost UAV Setup, Topographic Visualization and Computer Vision Techniques
Drones 2023, 7(2), 85; https://doi.org/10.3390/drones7020085 - 27 Jan 2023
Viewed by 723
Abstract
Many techniques are available for estimating landslide surface displacements, whether from the ground, air- or spaceborne. In recent years, Unmanned Areal Vehicles have also been applied in the domain of landslide hazards, and have been able to provide high resolution and precise datasets [...] Read more.
Many techniques are available for estimating landslide surface displacements, whether from the ground, air- or spaceborne. In recent years, Unmanned Areal Vehicles have also been applied in the domain of landslide hazards, and have been able to provide high resolution and precise datasets for better understanding and predicting landslide movements and mitigating their impacts. In this study, we propose an approach for monitoring and detecting landslide surface movements using a low-cost lightweight consumer-grade UAV setup and a Red Relief Image Map (a topographic visualization technique) to normalize the input datasets and mitigate unfavourable illumination conditions that may affect the further implementation of Lucas–Kanade optical flow for the final displacement estimation. The effectiveness of the proposed approach in this study was demonstrated by applying it to the Ruinon landslide, Northern Italy, using the products of surveys carried out in the period 2019–2021. Our results show that the combination of different techniques can accurately and effectively estimate landslide movements over time and at different magnitudes, from a few centimetres to more than several tens of meters. The method applied is shown to be very computationally efficient while yielding precise outputs. At the same time, the use of only free and open-source software allows its straightforward adaptation and modification for other case studies. The approach can potentially be used for monitoring and studying landslide behaviour in areas where no permanent monitoring solutions are present. Full article
(This article belongs to the Special Issue Drones for Natural Hazards)
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Review

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Review
Drones for Flood Monitoring, Mapping and Detection: A Bibliometric Review
Drones 2023, 7(1), 32; https://doi.org/10.3390/drones7010032 - 01 Jan 2023
Viewed by 1586
Abstract
Floods are one of the most often occurring and damaging natural hazards. They impact the society on a massive scale and result in significant damages. To reduce the impact of floods, society needs to keep benefiting from the latest technological innovations. Drones equipped [...] Read more.
Floods are one of the most often occurring and damaging natural hazards. They impact the society on a massive scale and result in significant damages. To reduce the impact of floods, society needs to keep benefiting from the latest technological innovations. Drones equipped with sensors and latest algorithms (e.g., computer vision and deep learning) have emerged as a potential platform which may be useful for flood monitoring, mapping and detection activities in a more efficient way than current practice. To better understand the scope and recent trends in the domain of drones for flood management, we performed a detailed bibliometric analysis. The intent of performing the bibliometric analysis waws to highlight the important research trends, co-occurrence relationships and patterns to inform the new researchers in this domain. The bibliometric analysis was performed in terms of performance analysis (i.e., publication statistics, citations statistics, top publishing countries, top publishing journals, top publishing institutions, top publishers and top Web of Science (WoS) categories) and science mapping (i.e., citations by country, citations by journals, keyword co-occurrences, co-authorship, co-citations and bibliographic coupling) for a total of 569 records extracted from WoS for the duration 2000–2022. The VOSviewer open source tool has been used for generating the bibliographic network maps. Subjective discussions of the results explain the obtained trends from the bibliometric analysis. In the end, a detailed review of top 28 most recent publications was performed and subjected to process-driven analysis in the context of flood management. The potential active areas of research were also identified for future research in regard to the use of drones for flood monitoring, mapping and detection activities. Full article
(This article belongs to the Special Issue Drones for Natural Hazards)
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