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Regeneracija gozdov v Zgornji Mežiški dolini – zaznavanje sprememb z daljinskim zaznavanjem : magistrsko delo
Potočnik Buhvald, Ana (Author), Oštir, Krištof (Mentor) More about this mentor... This link opens in a new window, Kanjir, Urša (Co-mentor)

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Abstract
Magistrsko delo predstavlja uporabnost daljinsko zaznanih posnetkov pri spremljanju regeneracije gozdov na nekdanjem rudniškem območju v Zgornji Mežiški dolini. Vrednotenje temelji na časovni analizi dolge časovne vrste satelitskih posnetkov Landsat, zajetih med junijem 1984 in januarjem 2016. Pri zaznavanju sprememb je uporabljen normiran diferencialni vegetacijski indeks (NDVI) in algoritem BFAST Monitor, ki časovno vrsto razdeli na stabilno/referenčno periodo in periodo odkrivanja sprememb. BFAST Monitor s svojo robustnostjo omogoča enostavno odkrivanje sprememb, ki se pojavljajo v različnih časovnih intervalih. Spremembe lahko zaznavamo na specifično izbranih rastrskih celicah in tako pridemo do časovnih profilov, ki kažejo večleten dinamičen razvoj gozdov ali pa izdelamo karte sprememb, iz katerih enostavno razberemo razvojne trende vegetacije na poljubno izbranem območju. Časovni profili v magistrskem delu so izdelani za štiri specifične lokacije, ki ležijo v neposredni bližini vira onesnaževanja v Žerjavu in katerih stanje že vrsto let spremljajo tudi strokovnjaki Biotehniške fakultete Univerze v Ljubljani. Obe študiji dokazujeta enake razvojne trende – stanje gozdov na analiziranih območjih se skozi opazovano časovno obdobje izboljšuje oz. gozdovi doživljajo regeneracijo. Končne karte sprememb prikazujejo spremembe, ki so bile zaznane v treh različnih časovnih intervalih, in sicer v 21-letnem (1995–2016), v 16-letnem (2000–2016) in v 11-letnem časovnem obdobju (2005–2016). V vseh treh izbranih časovnih intervalih je prevladovalo število pozitivnih sprememb, kar je dodatno potrdilo dejstvo, da se gozdovi v Zgornji Mežiški dolini in tudi njeni okolici v zadnjih tridesetih letih regenerirajo. Glede na dobljene rezultate, ki so potrdili vse zastavljene delovne hipoteze, se lahko tehnologija daljinskega zaznavanja, ki je stroškovno hitra in učinkovita, uporablja kot pomoč pri nadaljnjem spremljanju zdravstvenega stanja gozdov v Sloveniji.

Language:Slovenian
Keywords:Regeneracija gozdov, daljinsko zaznavanje, Landsat, analize časovnih vrst, BFAST Monitor
Work type:Master's thesis/paper (mb22)
Tipology:2.09 - Master's Thesis
Organization:FGG - Faculty of Civil and Geodetic Engineering
Year:2018
Publisher:[A. Potočnik Buhvald]
UDC:528.8:504.122(497.4)(043.3)
COBISS.SI-ID:8418401 Link is opened in a new window
Views:778
Downloads:509
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Secondary language

Language:English
Title:Forest Regeneration in the Upper Meža Valley – Detecting Changes with Remote Sensing : master thesis
Abstract:
This master’s thesis presents the applicability of remote sensing images in monitoring forest regeneration at the former mining site in the Upper Meža Valley. The analysis is based on a time series of Landsat dataset taken between June 1984 and January 2016. Changes were detected using normalized difference vegetation index (NDVI) as an input for BFAST Monitor algorithm, which divides time series into a stable history period and a detection period. The robust method BFAST Monitor offers a simple way of detecting changes occurring at different time intervals. The changes can be detected in specific selected raster cells, which enable generation of time profiles that show a dynamic multi-year forest regeneration, or can be mapped showing the trends in revegetation in an arbitrarily selected area. The time profiles in this master’s thesis were generated for four specific locations in the immediate vicinity of the source of pollution in the town of Žerjav that have also been monitored by experts of the Biotechnical Faculty of the University of Ljubljana for many years. Both studies show the same trends: the state of the forests in the analysed areas has improved during the period of observation; or rather, the forests are regenerating. The final maps show the changes determined in three different time intervals: a 21-year time interval (1995–2016), a 16-year time interval (2000–2016) and an 11-year time interval (2005–2016). The number of positive changes predominates in all three time intervals, which further corroborates the fact that the forests in the Upper Meža Valley and its surroundings have been regenerating for the past 30 years. The results confirm all working hypotheses set in this paper and show that remote sensing technology can be used as an affordable, fast and effective means of assistance in further monitoring of forest health in Slovenia.

Keywords:Forest Regeneration, Remote Sensing, Landsat, Time Series Analysis, BFAST Monitor

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