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master's thesis
Detekcija snježnih površina u NP Paklenica pomoću Python programskog jezika
diplomski rad
Zagreb: University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, 2020. urn:nbn:hr:169:514029
Keglević, Sven
University of Zagreb
Faculty of Mining, Geology and Petroleum Engineering
Department of Geophysical Exploration and Mine Surveying

Institutional repository: Faculty of Mining, Geology and Petroleum Engineering Repository, University of Zagreb

Cite this document

Keglević, S. (2020). Detekcija snježnih površina u NP Paklenica pomoću Python programskog jezika : diplomski rad (Master's thesis). Zagreb: University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:169:514029

Keglević, Sven. "Detekcija snježnih površina u NP Paklenica pomoću Python programskog jezika : diplomski rad." Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, 2020. https://urn.nsk.hr/urn:nbn:hr:169:514029

Keglević, Sven. "Detekcija snježnih površina u NP Paklenica pomoću Python programskog jezika : diplomski rad." Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, 2020. https://urn.nsk.hr/urn:nbn:hr:169:514029

Keglević, S. (2020). 'Detekcija snježnih površina u NP Paklenica pomoću Python programskog jezika : diplomski rad', Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, accessed 29 April 2024, https://urn.nsk.hr/urn:nbn:hr:169:514029

Keglević S. Detekcija snježnih površina u NP Paklenica pomoću Python programskog jezika : diplomski rad [Master's thesis]. Zagreb: University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering; 2020 [cited 2024 April 29] Available at: https://urn.nsk.hr/urn:nbn:hr:169:514029

S. Keglević, "Detekcija snježnih površina u NP Paklenica pomoću Python programskog jezika : diplomski rad", Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:169:514029

Metadata
TitleDetekcija snježnih površina u NP Paklenica pomoću Python programskog jezika : diplomski rad
Title (english)Snow surface detection in NP Paklenica using Python programming language : master's thesis
AuthorSven Keglević
MentorIvan Medved (mentor)
Committee memberIvan Medved (predsjednik povjerenstva)
Committee memberJasna Orešković (član povjerenstva)
Committee memberTomislav Korman (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Mining, Geology and Petroleum Engineering
(Department of Geophysical Exploration and Mine Surveying)
Zagreb
Defense date and country2020-09-22, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Mining, Petroleum and Geology Engineering
Geological Engineering
Abstract
Na području Nacionalnog parka Paklenica analizira se stanje snježnog pokrova na temelju satelitskih snimki satelita Landsat 8 i Sentinel-2. Prikupljene su satelitske snimke područja snimljene unutar vremenskog perioda između listopada 2014. i svibnja 2020. godine. Pomoću zelenog i kratkovalnog infracrvenog kanala satelitskih snimaka računa se NDSI indeks, odnosno normaliziran indeks razlike u snijegu. Područja s pozitivnom vrijednosti NDSI indeksa su područja pod snježnim pokrivačem. Obrada podataka provodi se u programskom jeziku Python. Primjenjuje se analitička metoda računanja NDSI indeksa, te tri metode strojnog učenja: neuronske mreže, K-means i Mean shift metoda.
Abstract (english)
In the area of the Paklenica National Park, the condition of the snow cover is analyzed on the basis of satellite images of the Landsat 8 and Sentinel-2 satellites. Collected satellite images are taken within time period between October 2014 and May 2020. The NDSI index, ie the normalized snow difference index, is calculated using the green and shortwave infrared channels of satellite images. Areas with a positive NDSI index value are areas under snow cover. Data processing is performed in the Python programming language. The analytical method of NDSI index calculation is applied, as well as three machine learning methods: neural networks, K-means and Mean shift method.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:169:514029
Study programmeTitle: Geological engineering; specializations in: Hydrogeology and engineering geology, Environmental geology
Course: Environmental geology
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka geološkog inženjerstva (magistar/magistra inženjer/inženjerka geološkog inženjerstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2020-10-19 09:29:20