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Title:Odkrivanje obolelih in posušenih dreves hrasta z uporabo drona in multispektralne kamere : diplomsko delo
Authors:ID Paunović, Anđela (Author)
ID Vindiš, Peter (Mentor) More about this mentor... New window
Files:.pdf VS_Paunovic_Andela_2025.pdf (2,33 MB)
MD5: 3108C01BE0170AA39AED26AD591E26B9
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FKBV - Faculty of Agriculture and Life Sciences
Abstract:Izvleček V diplomskem delu smo raziskali možnost odkrivanja obolelih in posušenih dreves hrasta z uporabo drona in multispektralne kamere. Namen raziskave je bil preveriti učinkovitost sodobnih metod daljinskega zaznavanja pri hitrejšem in natančnejšem prepoznavanju dreves v stresu v primerjavi s tradicionalnimi fizičnimi obhodi. V rezervatu Cigonca smo izvedli prelet z dronom DJI Phantom 4, opremljenim z multispektralno kamero Parrot Sequoia. Zajete podatke smo obdelali s programom PIX4Dfields ter nato izdelali ortomozaik in izračunali indeks NDVI, na podlagi katerega smo določili tri potencialno stresna območja. Nato smo opravili fizični obhod za potrditev rezultatov. Ugotovili smo, da so bila drevesa na vseh treh območjih dejansko prizadeta. Na območju 1 (NDVI 0,45–0,49) so bila drevesa preraščena z bršljanom, kar je zmanjšalo njihovo vitalnost. Na območju 2 (NDVU 0,36–0,39) so bila drevesa močno poškodovana zaradi glivičnih okužb ter so imela razpoke in slabo porasle krošnje. Na območju 3 (NDVI 0,29–0,32) so bila drevesa povsem posušena in brez ekonomske vrednosti. Iz rezultatov je razvidno, da uporaba drona in multispektralne kamere omogoča hitro, učinkovito in prostorsko natančno zaznavanje stresnih območij ter bistveno prispeva k pravočasnemu ukrepanju za ohranjanje vitalnosti hrastovih gozdov in zmanjšanje gospodarske škode.
Keywords:hrast, sušenje, dron, multispektralna kamera
Place of publishing:Maribor
Place of performance:Maribor
Publisher:A. Paunović
Year of publishing:2025
Number of pages:1 spletni vir (1 datoteka PDF (VI, 28 str.))
PID:20.500.12556/DKUM-95452 New window
UDC:582.623.2:632:629.7.014.9:681.783.322(043.2)=163.6
COBISS.SI-ID:255106563 New window
Publication date in DKUM:28.10.2025
Views:158
Downloads:20
Metadata:XML DC-XML DC-RDF
Categories:FKBV
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Licences

License:CC BY-NC 4.0, Creative Commons Attribution-NonCommercial 4.0 International
Link:http://creativecommons.org/licenses/by-nc/4.0/
Description:A creative commons license that bans commercial use, but the users don’t have to license their derivative works on the same terms.
Licensing start date:19.09.2025

Secondary language

Language:English
Title:Detection of diseased and dried out oak trees using a drone and a multispectral camera
Abstract:This thesis explores the possibility of detecting diseased and dried oak trees using a drone equipped with a multispectral camera. The aim of the research was to evaluate the effectiveness of modern remote sensing methods in identifying stressed trees more quickly and accurately compared to traditional ground-based inspections. In the Cigonca reserve, we carried out a drone flight with a DJI Phantom 4 equipped with a Parrot Sequoia multispectral camera. We processed the collected data using PIX4Dfields software, then created an orthomosaic and calculated the NDVI index, which we used to identify three potentially stressed areas. We then carried out a physical inspection to validate the results. The findings confirmed that the trees in all three areas were affected. In Area 1 (NDVI 0.45–0.49), the trees were covered with ivy, which reduced their vitality. In Area 2 (NDVI 0.36–0.39), the trees were severely damaged by fungal infections and showed trunk cracks and sparse less vital. In Area 3 (NDVI 0.29–0.32), the trees were completely dried out and had no economic value. The results indicate that the use of drones and multispectral cameras can enable a fast, efficient, and spatially accurate detection of stress areas, as well as significantly contribute to timely interventions for preserving the vitality of oak forests and consequently reducing economic losses.
Keywords:oak, drying, drone, multispectral camera


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