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Primerjava prostornin na osnovi podatkov zajema z letalniki : diplomska naloga
Grahor, Vid (Author), Koler, Božo (Mentor) More about this mentor... This link opens in a new window, Urbančič, Tilen (Co-mentor), Stopar, Bojan (Thesis defence commission member), Kogoj, Dušan (Thesis defence commission member)

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Abstract
V diplomski nalogi je opravljena analiza prostornin deponiranega materiala, na osnovi oblakov točk zajema z brezpilotnima ploviloma, kvadrokopterjem in letalnikom. Pred obdelava oblakov točk je bila izvedena s programom MeshLab. Za izračun prostornin smo uporabili različne metode interpolacij (Metoda naravnih sosedov, Metoda inverzne razdalje, Multikvadratična funkcija, Navadni zlepki, Bayesov kriging, TIN), ter različne dimenzije gridnih celic (0,1 m, 0,2 m, 0,3 m, 0,4 m, 0,5 m). Interpolacije so bile izvedene v programu ArcGis - ArcMap 10.2. Zaradi zaraščenosti deponije, ki v oblaku točk predstavlja šum, so bile interpoliranim gridnim ploskvam dodane klasično posnete detajlne točke. Prostornine so bile izračunane s programom AutoCAD Civil 3D 2013. Referenčno vrednost za oceno kakovosti določitve prostornin z različnimi metodami interpolacij, ter za različne velikosti gridnih celic, predstavlja prostornina določena z metodo TIN. Na osnovi analize višin oblakov točk je bilo ugotovljeno, da sta oblaka točk določena v različnih vertikalnih datumih. Ker so prostornine določene za vsak oblak točk posebej, to ne vpliva na izračun prostornin. Analiza rezultatov na obravnavani deponiji je pokazala, da obstajajo razlike v določitvi prostornin z različnimi interpolacijskimi metodami. Izbrana velikost gridne celice do 1 m bistveno ne vpliva na izračun prostornin. Razlike v izračunu prostornin med različnima oblakoma točk so manjše od 5%. Oblaka točk sta torej primerljive kakovosti.

Language:Slovenian
Keywords:geodezija, diplomska naloga, UNI, izračun prostornin, letalniki, oblak točk, interpolacija, gridne celice, TIN, metoda naravnih sosedov, metoda inverzne razdalje, multikvadratična funkcija, navadni zlepki, Bayesov kriging
Work type:Undergraduate thesis (m5)
Tipology:2.11 - Undergraduate Thesis
Organization:FGG - Faculty of Civil and Geodetic Engineering
Year:2014
Publisher:[V. Grahor]
Number of pages:XVI, 64 str., 1 pril.
Place:Ljubljana
UDC:528.01:629.73(043.2)
COBISS.SI-ID:6627681 This link opens in a new window
Views:1613
Downloads:504
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Secondary language

Language:English
Title:Volumes comparison based on UAV point cloud
Abstract:
In the graduation thesis the analysis of volumes of deposited material, based on point clouds from unmanned aerial vehicles is accomplished. Point clouds were preprocessed in MeshLab. We used various interpolation methods (Inverse Distance Weighted, Natural Neighbor, Multiquadric Function, Regularized Spline, Empirical Bayesian Kriging) to produce grid surfaces with different grid cell dimensions (0,1 m, 0,2 m, 0,3 m, 0,4 m, 0,5 m). Interpolations were proceeded in ArcGis - ArcMap 10.2. Because the deposited material was overgrown with vegetation, additional points measured with polar method were added in point cloud. Volumes of deposited material were computed in AutoCAD Civil 3D 2013. Reference value, for quality control of volume computation with different interpolation methods and different grid cell dimensions, is based on TIN method. From the analysis, based on point cloud heights we founded, that the point clouds are determined in a different vertical datum. Volumes are determined for each point cloud separately, so the different vertical datum does not affect on volume computation. The analysis of the results, for discussed material depot showed, the differences, of volumes computation, between each interpolation methods, are present. Chosen grid cell size by 1 m, does not affect significantly on volume computation. Deviations of volume computations between each point cloud are smaller than 5%. Therefore the point clouds are comparable in quality.

Keywords:Volumes computation, UAV, point cloud, interpolation, grid cells, TIN, Inverse Distance Weighted, Natural Neighbor, Multiquadric Function, Regularized Spline, Empirical Bayesian Kriging

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