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master's thesis
Automatizacija klasifikacije poplavljenog područja Gunje pomoću Python programskog jezika
diplomski rad
Zagreb: University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, 2022. urn:nbn:hr:169:043690
Mikšić, Josip
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

Mikšić, J. (2022). Automatizacija klasifikacije poplavljenog područja Gunje 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:169:043690

Mikšić, Josip. "Automatizacija klasifikacije poplavljenog područja Gunje pomoću Python programskog jezika : diplomski rad." Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, 2022. https://urn.nsk.hr/urn:nbn:hr:169:043690

Mikšić, Josip. "Automatizacija klasifikacije poplavljenog područja Gunje pomoću Python programskog jezika : diplomski rad." Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, 2022. https://urn.nsk.hr/urn:nbn:hr:169:043690

Mikšić, J. (2022). 'Automatizacija klasifikacije poplavljenog područja Gunje pomoću Python programskog jezika : diplomski rad', Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, accessed 25 November 2024, https://urn.nsk.hr/urn:nbn:hr:169:043690

Mikšić J. Automatizacija klasifikacije poplavljenog područja Gunje pomoću Python programskog jezika : diplomski rad [Master's thesis]. Zagreb: University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering; 2022 [cited 2024 November 25] Available at: https://urn.nsk.hr/urn:nbn:hr:169:043690

J. Mikšić, "Automatizacija klasifikacije poplavljenog područja Gunje pomoću Python programskog jezika : diplomski rad", Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:169:043690

Metadata
TitleAutomatizacija klasifikacije poplavljenog područja Gunje pomoću Python programskog jezika : diplomski rad
Title (english)Automatization of flood classification at Gunja area using Pyhton programming language : master's thesis
AuthorJosip Mikšić
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 country2022-02-11, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Mining, Petroleum and Geology Engineering
Geological Engineering
Abstract
Analiza i klasifikacija vodene površine na području Gunje, prije i poslije poplave u svibnju 2014. godine, vršena je na temelju snimaka Landsat 8 satelita. Pomoću zelenog i blisko infracrvenog spektra svjetlosti računa se NDWI indeks, a na temelju plavog i blisko infracrvenog spektra svjetlosti MNDWI. Modificirani INDEX dobiva se kao zbroj NDWI i MNDWI. Vodena površina na temelju dobivenih vrijednosti određena je pozitivnim vrijednostima. Prilikom binarne klasifikacije vodena površina zaprima vrijednost 1, dok površina koja nije pod vodom zaprima vrijednost 0. Obrada i analiza podataka provedena je kroz programski jezik Python i geografski informacijski sustav (QGIS).
Abstract (english)
The analysis and classification of the water surface at the Gunja area, before and after the flood in May 2014., was performed on the basis of images from Landsat 8 satellite. NDWI index is calculated using the green and near-infrared spectre of light, MNDWI index is based on the blue and near-infrared spectre of light. The modified INDEX is obtained as the sum of NDWI and MNDWI indexes. The water surface is determined as positive values, on the basis of the obtained values. During binary classification, water receives a value of 1, while non-water surface obtains a value of 0. Dana processing and analysis was performed through the Python programming language and the geographic iformation system (QGIS).
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:169:043690
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
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Created on2022-04-19 07:26:40