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EN
One of the challenges faced by surveyors in acquisition of accurate spatial data for mining applications is the risk involved in acquiring data in rugged terrains and difficult or inaccessible areas. With the advent of modern technology, accurate geospatial data can now be safely obtained for proper mining documentation periodically. The use of Unmanned Aerial Vehicles (UAVs) for data acquisition in mine surveying has been a viable means of obtaining reliable geospatial data rapidly and efficiently. The main goal of this study is to develop a semi-automatic UAV-based system for the acquisition of spatial data required for the estimation of the volume of earthworks. A DJI Phantom 4 quadcopter was used for the acquisition of image data of the project site, while the images were processed into a Digital Elevation Model (DEM) using Pix4Dmapper v2.0.1, which was then imported into the MATLAB-based system developed for the automatic estimation of the volume of earthworks. The volume obtained from the automated system was thus compared with the volume obtained directly from the Pix4Dmapper software, having specified a contour interval of 1 and an allowable error rate of ±3% as the standard error. While ±1.02% error was observed in the volume estimated using the Pix4Dmapper, the developed automated system yielded an estimated precision of ±0.81% in its volume estimation, which proves to be more robust for automatic volume estimation in terms of accuracy and precision.
PL
Artykuł prezentuje najważniejsze metody pozyskiwania danych przestrzennych, które wykorzystywane są w procesie BIM. Zostały przedstawione także aspekty geodezyjne związane z uzyskaniem wirtualnej chmury punktów, w której możliwe jest wykonanie rzeczywistych modeli 3D.
EN
Described are the most important methods of spatial data capture that are used in the BIM process. Presented are also geodetic aspects connected with obtaining the virtual point cloud in which it is possible to make the real 3D models.
EN
The east-central part of the Kamienne Mountains in the Sudetes has long been known as an area where landslides occur in abundance. Their extent was shown on first detailed geological maps from the early 20th century and later on Polish geological maps published in the 1970 and 1990. The total landslide area mapped was about 100 ha. The availability of LiDAR data allowed to build digital elevation models of very high resolution and to attempt landslide mapping using diagnostic landform assemblages as guidelines. 30 separate landslides have been mapped, including complex landslide areas involving overlapping landslide bodies oflikely different origin. The total landslide area is at least300 ha, while the largest complexes cover 40-50 ha. LiDAR-based models proved extremely useful in landslide mapping, espe- cially in forested areas.
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