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Masovno zajemanje podatkov na prostovoljni osnovi : diplomska naloga
ID Vičič, Blaž (Author), ID Podobnikar, Tomaž (Mentor) More about this mentor... This link opens in a new window, ID Šumrada, Radoš (Co-mentor)

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Abstract
Diplomska naloga obravnava metode množičnega zajemanja podatkov, ki temeljijo predvsem na zajemanju prostorskih podatkov iz spletnih virov ali pa na lastni izdelavi. Cilji so izdelati čim bolj kakovostne podatkovne zbirke in uporabiti čim manj plačljivih podatkov. Naloga predstavi začetke in razvoj svetovnega spleta ter osnove spletnega izvajanja množic kot podlago za takšen zajem podatkov. Predstavlja izdelavo digitalnega modela reliefa (DMR) iz plastnic in digitalnega modela površja iz podatkov SRTM. V praktičnem delu predstavimo pet primerov: dva primera iz okolja OpenStreetMap ter po en iz wikipedie, izdelave DMR-ja iz podatkov SRTM-ja in iz plastnic, pridobljenih iz VTK50. V OpenStreetMap-u demonstriramo urejanje izbranega območja. Wikipedio obravnavamo kot vir za izdelavo te diplomske naloge, ter ugotavljamo ustreznost podatkov za strokovne namene, iz podatkov SRTM-ja in DMR-ja lastne izdelave pa s postopki primerjave predstavimo višinske razlike med slojema. Rezultati so urejeno območje v OpenStreetMap-u in analiza, ki nakazuje ustreznost posameznih okolij za različne namene. Wikipedia se izkaže za delno ustrezen vir, njena uporaba se priporoča v kombinaciji z drugimi viri. Pri podatkih SRTM-ja obravnavamo zaradi geomorfološko pogojenih nepopolnih posnetih območij nastale podatkovne vrzeli in SRTMFill kot metodo zapolnjevanja teh vrzeli. Končni rezultat je ugotovitev, da je skupno reševanje problemov enostavnejše kot posamično, kar potrjuje domnevo diplomske naloge.

Language:Slovenian
Keywords:geodezija, diplomska naloga, UNI, množično zajemanje podatkov, svetovni splet, semantični splet
Work type:Undergraduate thesis
Typology:2.11 - Undergraduate Thesis
Organization:FGG - Faculty of Civil and Geodetic Engineering
Place of publishing:Ljubljana
Publisher:[B. Vičič]
Year:2014
Number of pages:XII, 70 str., 6 str. pril.
PID:20.500.12556/RUL-32496 This link opens in a new window
UDC:004.738.5:659.2:91(043.2)
COBISS.SI-ID:6821985 This link opens in a new window
Publication date in RUL:10.07.2015
Views:2291
Downloads:484
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Secondary language

Language:English
Title:Massive data collection on the basis of volunteered geographical information
Abstract:
The thesis examines methods of acquiring mass data, which are mainly based on getting spatial data from online sources or one's own designs. The goals of the thesis are to produce databases of the highest quality, while using as little pay-per-view data as possible. The thesis presents the beginnings and the development of the World Wide Web, and examines the basics of online implementation of mass data as the basis for such acquiring of data. It presents the production of the digital elevation model (DEM) from the contours and the surface model derived from SRTM data. The practical section presents five examples: two examples from OpenStreetMap and one from wikipedia, the production of the DEM based on SRTM data and countours derived from VTK50. The selected area is edited in OpenStreetMap. Wikipedia is regarded as a source for producing this thesis, and it is established whether the data is suitable for professional purposes or not, while the data from SRTM and the DEM of my own creation were used to compare the contours and thus present the differences in height between the layers. The results manifest themselves as an edited area in OpenStreetMap and the comparison which shows the suitability of individual environments for different purposes. Wikipedia turns out to be a partially suitable source and is recommended to be used in combination with other sources. SRTMFill is treated as a method for filling the gaps in SRTM data that arise due to the different angles of recording these emerging gaps. The end result is the finding that joint problem solving is easier than tackling problems individually, which confims the supposition of this thesis.

Keywords:graduation thesis, geodesy, massive data collection

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