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Remote Sensing
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The Application of Unmanned Aerial Systems in Search and Rescue...
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The Application of Unmanned Aerial Systems in Search and Rescue Activities

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Earth Observation for Emergency Management".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 24234

Special Issue Editors

Prof. Dr. Tomasz Niedzielski

E-Mail Website
Guest Editor
1. Department of Geoinformatics and Cartography, Faculty of Earth Sciences and Environmental Management, University of Wrocław, pl. Uniwersytecki 1, 50-137 Wrocław, Poland
2. SARUAV Ltd., 50-137 Wrocław, Poland
Interests: geoinformatics; unmanned aerial vehicles; person detection; image analysis; hydrology; hydroinformatics
Special Issues, Collections and Topics in MDPI journals
Dr. Daniele Giordan

E-Mail Website
Guest Editor
CNR IRPI, Turin, Italy
Interests: unmanned aerial vehicles; natural hazards; engineering geology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent advances in search and rescue (SAR) activities include the operational use of unmanned aerial vehicles (UAVs), known as drones. Although UAVs are commonly used in SAR missions, there is a growing demand for the development of methods for analysing drone-acquired data in an unsupervised fashion. This Special Issue focuses both on methodical papers on how data analysis during an SAR mission can be automated and on all aspects of the use of drones in SAR activities. New findings and recommendations in the field of drone-based SAR missions may facilitate searches and increase the probability of saving lives.

We are pleased to invite you to submit manuscripts on the use of UAVs in SAR activities as well as on new methods or approaches that make the applicability of drones in SAR more effective. We welcome theoretical contributions as well as field reports. Manuscripts focusing on terrestrial and marine environments are invited.

This Special Issue aims to broaden the knowledge about the use of unmanned aerial technologies in SAR services and to report on the recent progress of methods and procedures developed in this field.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Special unmanned aerial systems dedicated for search and rescue;
  • Use of consumer-grade drones in search and rescue;
  • Close-range photogrammetry in search and rescue;
  • Algorithms for person detection and tracking;
  • Special software for search and rescue with drones;
  • Field reports on the operational use of drones in search and rescue missions;
  • Reports from field experiments;
  • Drone payload use in search and rescue;
  • Terrain assessment with drones (e.g., snow/avalanche evaluation for rescuers);
  • Weather assessment with drones (e.g., wind evaluation for rescuers).

We look forward to receiving your contributions.

Prof. Dr. Tomasz Niedzielski
Dr. Daniele Giordan
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.

Keywords

  • unmanned aerial vehicle
  • search and rescue
  • drone
  • sensors
  • aerial monitoring.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

Jump to: Review

14 pages, 13200 KiB  
Communication
Person Mobility Algorithm and Geographic Information System for Search and Rescue Missions Planning
by Vladan Papić, Ana Šarić Gudelj, Ante Milan and Mario Miličević
Remote Sens. 2024, 16(4), 670; https://doi.org/10.3390/rs16040670 - 13 Feb 2024
Viewed by 863
Abstract
In search and rescue (SAR) operations, up-to-date information on the terrain is critical because every additional hour required to search for a person reduces the likelihood of success. Therefore, it is necessary to provide quick access and the best possible input data for [...] Read more.
In search and rescue (SAR) operations, up-to-date information on the terrain is critical because every additional hour required to search for a person reduces the likelihood of success. Therefore, it is necessary to provide quick access and the best possible input data for planners and search teams and to develop tools that can help them plan and monitor actions in real-time. This paper describes a novel system based on the use of GIS for planning actions and visualizing the situation on the ground. Special focus is devoted to the algorithm for assessing the mobility of the missing person. Using this algorithm, the area of the proposed search area is modeled based on obtained information about the type of terrain on which the searches are planned. The obtained results are presented as a new Geographic Information System layer and have proven to be a quality that helps in defining the search space. Further research is discussed, especially regarding the assessment of the passability of certain types of terrain. Full article
(This article belongs to the Special Issue The Application of Unmanned Aerial Systems in Search and Rescue Activities)
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Figure 1

Figure 1
<p>“Ring approach”—standard search and rescue scenario based on Euclidean distance from the IPP (initial planning point).</p> Full article ">Figure 2
<p>Illustration of the first four steps of PMA algorithm workflow execution. The passability matrix (P) contains values determined after the observed terrain map segmentation. Values of the list containing inside border segments (<span class="html-italic">E<sub>IN</sub></span>) after the first, second, and fourth steps of the PMA algorithm are executed. Final segment values after three steps colored green, fourth step results with value of segment colored orange. Segment values marked with (*) are temporary values.</p> Full article ">Figure 3
<p>Example of PMA algorithm results. (<b>a</b>) Segmented terrain map—input for the algorithm; (<b>b</b>) resulting search area (red). The grid shows the unit segments.</p> Full article ">Figure 4
<p>Overlayed Bing map with UAV-acquired images.</p> Full article ">Figure 5
<p>Image of terrain segmented according to detected types.</p> Full article ">Figure 6
<p>Setting the IPP (initial planning point) and the category of the missing person and defining the mobility area based on data from the ISRID database and experimentally obtained data on the reduction factor and the expected speed of the person using the QGIS plugin.</p> Full article ">Figure 7
<p>Comparison of the statistical curve and the search area based on the applied PMA algorithm.</p> Full article ">Figure 8
<p>Calculated search areas for five real cases from [<a href="#B35-remotesensing-16-00670" class="html-bibr">35</a>]. The radius of the 75% probability circle for the type of missing person is indicated. The shaded areas represent the search areas for the set maximum distances of 25%, 50%, and 75%. (<b>a</b>) Child 10-12, Old Rag Mountain; (<b>b</b>) Dementia, Brown’s Cove; (<b>c</b>) Despondent, Whiteoak Canyon; (<b>d</b>) Gatherer, Rattlesnake Run; (<b>e</b>) Mental Illness, Panorama—Turn Bridge Trail.</p> Full article ">
18 pages, 14385 KiB  
Article
First Successful Rescue of a Lost Person Using the Human Detection System: A Case Study from Beskid Niski (SE Poland)
by Tomasz Niedzielski, Mirosława Jurecka, Bartłomiej Miziński, Wojciech Pawul and Tomasz Motyl
Remote Sens. 2021, 13(23), 4903; https://doi.org/10.3390/rs13234903 - 3 Dec 2021
Cited by 14 | Viewed by 5071
Abstract
Recent advances in search and rescue methods include the use of unmanned aerial vehicles (UAVs), to carry out aerial monitoring of terrains to spot lost individuals. To date, such searches have been conducted by human observers who view UAV-acquired videos or images. Alternatively, [...] Read more.
Recent advances in search and rescue methods include the use of unmanned aerial vehicles (UAVs), to carry out aerial monitoring of terrains to spot lost individuals. To date, such searches have been conducted by human observers who view UAV-acquired videos or images. Alternatively, lost persons may be detected by automated algorithms. Although some algorithms are implemented in software to support search and rescue activities, no successful rescue case using automated human detectors has been reported on thus far in the scientific literature. This paper presents a report from a search and rescue mission carried out by Bieszczady Mountain Rescue Service near the village of Cergowa in SE Poland, where a 65-year-old man was rescued after being detected via use of SARUAV software. This software uses convolutional neural networks to automatically locate people in close-range nadir aerial images. The missing man, who suffered from Alzheimer’s disease (as well as a stroke the previous day) spent more than 24 h in open terrain. SARUAV software was allocated to support the search, and its task was to process 782 nadir and near-nadir JPG images collected during four photogrammetric flights. After 4 h 31 min of the analysis, the system successfully detected the missing person and provided his coordinates (uploading 121 photos from a flight over a lost person; image processing and verification of hits lasted 5 min 48 s). The presented case study proves that the use of an UAV assisted by SARUAV software may quicken the search mission. Full article
(This article belongs to the Special Issue The Application of Unmanned Aerial Systems in Search and Rescue Activities)
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Figure 1

Figure 1
<p>Recommendations on how to carry out a UAV mission, to ensure a high probability of detecting a lost person in an aerial image.</p> Full article ">Figure 2
<p>Influence of altitude above ground level on the area of the observed terrain (left vs. middle sketches) and the effect of departing from nadir-looking camera orientation on geometry, in respect to the center of projection (left vs. right sketches).</p> Full article ">Figure 3
<p>Side and front overlap of nadir images as an approach for not omitting person’s view.</p> Full article ">Figure 4
<p>True persons in flights 1–4 (land cover “a” and “b” from <a href="#remotesensing-13-04903-t001" class="html-table">Table 1</a>) with the information on successful (green “+” sign) and unsuccessful (red “−” sign) detections.</p> Full article ">Figure 5
<p>True persons in flights 5–9 (land cover “c” and “d” from <a href="#remotesensing-13-04903-t001" class="html-table">Table 1</a>) with the information on successful (green “+” sign) and unsuccessful (red “−” sign) detections.</p> Full article ">Figure 6
<p>True persons in flight 10 (land cover “e” from <a href="#remotesensing-13-04903-t001" class="html-table">Table 1</a>) with the information on successful (green “+” sign) and unsuccessful (red “−” sign) detections.</p> Full article ">Figure 7
<p>The hits suggested by the SARUAV software (pins in the map area—left) and the verification panel designed for human analysts (list of coordinates with attached image filenames as well as the area of interest centered on a found object—right).</p> Full article ">Figure 8
<p>Search and rescue activities undertaken during the search for a 65-year-old man who was lost near the village of Cergowa in Beskid Niski (SE Poland).</p> Full article ">Figure 9
<p>Mission area in the context of geographic location of Poland and its SE part. MRS is an abbreviation of Mountain Rescue Service.</p> Full article ">Figure 10
<p>Spatial coverage of RGB flights along with the corresponding flight paths, with superimposed IPP, LKP, and found location points.</p> Full article ">Figure 11
<p>View of the SARUAV graphical user interface, while the system detected the lost person in images collected in RGB flight 3.</p> Full article ">

Review

Jump to: Research

35 pages, 2670 KiB  
Review
Unmanned Aerial Vehicles for Search and Rescue: A Survey
by Mingyang Lyu, Yibo Zhao, Chao Huang and Hailong Huang
Remote Sens. 2023, 15(13), 3266; https://doi.org/10.3390/rs15133266 - 25 Jun 2023
Cited by 49 | Viewed by 15750
Abstract
In recent years, unmanned aerial vehicles (UAVs) have gained popularity due to their flexibility, mobility, and accessibility in various fields, including search and rescue (SAR) operations. The use of UAVs in SAR can greatly enhance the task success rates in reaching inaccessible or [...] Read more.
In recent years, unmanned aerial vehicles (UAVs) have gained popularity due to their flexibility, mobility, and accessibility in various fields, including search and rescue (SAR) operations. The use of UAVs in SAR can greatly enhance the task success rates in reaching inaccessible or dangerous areas, performing challenging operations, and providing real-time monitoring and modeling of the situation. This article aims to help readers understand the latest progress and trends in this field by synthesizing and organizing papers related to UAV search and rescue. An introduction to the various types and components of UAVs and their importance in SAR operations is settled first. Additionally, we present a comprehensive review of sensor integrations in UAVs for SAR operations, highlighting their roles in target perception, localization, and identification. Furthermore, we elaborate on the various applications of UAVs in SAR, including on-site monitoring and modeling, perception and localization of targets, and SAR operations such as task assignment, path planning, and collision avoidance. We compare different approaches and methodologies used in different studies, assess the strengths and weaknesses of various approaches, and provide insights on addressing the research questions relating to specific UAV operations in SAR. Overall, this article presents a comprehensive overview of the significant role of UAVs in SAR operations. It emphasizes the vital contributions of drones in enhancing mission success rates, augmenting situational awareness, and facilitating efficient and effective SAR activities. Additionally, the article discusses potential avenues for enhancing the performance of UAVs in SAR. Full article
(This article belongs to the Special Issue The Application of Unmanned Aerial Systems in Search and Rescue Activities)
►▼ Show Figures

Figure 1

Figure 1
<p>Schematic diagram of unmanned helicopter [<a href="#B12-remotesensing-15-03266" class="html-bibr">12</a>].</p> Full article ">Figure 2
<p>Figure of Quadcopter X [<a href="#B15-remotesensing-15-03266" class="html-bibr">15</a>].</p> Full article ">Figure 3
<p>Figure of fixed wing UAV [<a href="#B17-remotesensing-15-03266" class="html-bibr">17</a>].</p> Full article ">Figure 4
<p>Figure of hybrid UAV [<a href="#B21-remotesensing-15-03266" class="html-bibr">21</a>].</p> Full article ">Figure 5
<p>Illustration of CNN.</p> Full article ">Figure 6
<p>Path planning when tracking a target in [<a href="#B108-remotesensing-15-03266" class="html-bibr">108</a>].</p> Full article ">Figure 7
<p>Architecture block diagram of SLAM-based exploration in [<a href="#B143-remotesensing-15-03266" class="html-bibr">143</a>].</p> Full article ">Figure 8
<p>Local obstacle avoidance strategy in [<a href="#B154-remotesensing-15-03266" class="html-bibr">154</a>].</p> Full article ">
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