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  • 1
    In: Remote Sensing, MDPI AG, Vol. 13, No. 23 ( 2021-12-03), p. 4903-
    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, 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.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2513863-7
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  • 2
    In: Przegląd Geograficzny, Institute of Geography and Spatial Organization, Polish Academy of Sciences, Vol. 92, No. 3 ( 2020), p. 377-389
    Abstract: A comparison between errors associated with snow-cover reconstruction performed by processing aerial imagery acquired by a visible-light camera mounted on board unmanned aerial vehicles, one the one hand; and average terrain roughness, on the other, revealed a dependent relationship between these variables. A stronger correlation is noted for two of the studied test areas (Polana Izerska and Krobica, both located in SW Poland), as opposed to the remaining site (Drożyna, SW Poland). In particular, correlations are noticeable where the analysis is performed in moving windows. It is typical for terrain where depth of snow cover is reconstructed with severe errors to reveal a high degree of roughness caused by single trees, clumps of trees or buildings. Ambiguous results are obtained for the Drożyna research field. While the character of the dependent relationship there seems consistent with results for the remaining sites, the strength is low. The lower values for the correlation coefficient were driven by observations for which errors were found to be high while values for the Topographic Ruggedness Index were at the same time low. This effect can be explained by reference to the specific nature of the area reconstructed, which is much transformed by human activity. It proves difficult to reconstruct the depth of snow cover on roads properly, as these are either partially cleared or snow or characterised by its loss in the course of melting. Low thickness of snow cover is thus found to be a constrained when it comes to the generation of accurate reconstructions of the depth of snow cover. This is in fact a finding in agreement with what has been reported by other authors.
    Type of Medium: Online Resource
    ISSN: 2300-8466 , 0033-2143
    URL: Issue
    Language: Polish
    Publisher: Institute of Geography and Spatial Organization, Polish Academy of Sciences
    Publication Date: 2020
    detail.hit.zdb_id: 2667464-6
    detail.hit.zdb_id: 209415-0
    SSG: 14
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