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Title:Zaznava bolezni in fizioloških motenj pšenice na podlagi sprememb vegetacijskih indeksov
Authors:ID Fridrih, Gašper (Author)
ID Lakota, Miran (Mentor) More about this mentor... New window
ID Rakun, Jurij (Comentor)
Files:.pdf VS_Fridrih_Gasper_2019.pdf (1,81 MB)
MD5: 646B6464C8636F60E11FEBF0482D4AE7
PID: 20.500.12556/dkum/997b3905-9903-473b-8ea2-7633766cc6d7
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FKBV - Faculty of Agriculture and Life Sciences
Abstract:V zadnjem času se uvajajo droni oz. brezpilotna letala (uav) za spremljanje razvoja rastlin. Prednosti uporabe se kažejo v preprostem načrtovanju, nemotenem delovanju in pridobivanju posnetkov iz ptičje perspektive. S prenosom sistemov multispektralnih kamer in nizko višino leta zagotavljajo visoko ločljivost rastlin. Pšenica je kultura, ki se goji v največjem obsegu površin, zato ponuja velik interes po pridobitvi prostorskih in časovnih informacijah o rastlini. V nalogi smo prikazali določevanje različnih vegetacijskih indeksov na osnovi multispektralnih posnetkov z droni. Snemanja so bila izvedena na površinah podjetja JERUZALEM SAT d.d. v različnih obdobjih rasti pšenice. Na osnovi zajetih posnetkov smo s pomočjo programske opreme Pix4Dfields generirali različne vegetacijske indekse in poiskali vzorčne povezave s stanjem na polju. Pridobljeni podatki omogočajo selektivne nanose gnojil in fitofarmacevtskih sredstev ter tako pripomorejo k prihrankom v proizvodnji in zmanjšanim obremenitvam okolja.
Keywords:dron, pšenica, multispektralna kamera, vegetacijski indeksi, daljinsko zaznavanje
Place of publishing:Maribor
Year of publishing:2019
PID:20.500.12556/DKUM-74521 New window
NUK URN:URN:SI:UM:DK:UBAPYTVH
Publication date in DKUM:09.09.2019
Views:1584
Downloads:207
Metadata:XML DC-XML DC-RDF
Categories:FKBV
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Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:29.08.2019

Secondary language

Language:English
Title:Detection of diseases nad physiological disturbances of wheat based on vegetation index charges
Abstract:Recently, unmanned aerial vehicles have been introduced into agriculture to monitor plant development. The main advantages are simple planning, immediate operation and cloud-based imaging. By wearing multispectral camera system and with low altitude of the flight UAVs assure high-resolution images of plants. Wheat is a crop grown on the largest surface area and therefore trigger interesting for acquisition of spatial and temporal information. In the thesis, we have shown the determination of different vegetation indices based on multispectral drone imagery. The recordings were made on the land of JERUZALEM SAT d.d. at different stages of wheat growth. Based on the captured images, various vegetation indices were generated using Pix4Dfields software to find sample connections to the real state of the field. Obtained data allow us to selectively apply fertilizers and plant protection products and they contribute to saving in production and reduce environmental burden.
Keywords:drone, wheat, multispectral camera, vegetation indices, remote sensing


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