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Novo Mesto, Slovenia

Radovan D.,Geodetski Institute Slovenije
Geodetski Vestnik | Year: 2011

The geodetic profession provides geodetic data obtained in the fields of fundamental geodetic system, real estate and topography. Users integrate this data with other spatial data. The quality of such applications depends on the data quality; however, the providers and the users are not sufficiently aware of the cascading transfer of errors from the primary data layers to the secondary, derived data. Geodesy has traditionally considered errors mainly as positional errors, according to the law of the transfer of errors. Since the era of widespread digitizing of geodetic data began in the 1990s, data quality in the realm of geographic information systems has been expressed with the standardized parameters of data quality, and with metadata, of which positional accuracy is just one type. Unfortunately, in this way, the knowledge about which data is a reference can be obscured. To many users, it is not clear what is the specified quality referred to. This article describes, and intentionally uses, the term 'cascading', since for the rise of data quality one needs to upgrade data level by data level, starting first with the reference data and the semantic definitions of object types, and continuing by updating and harmonizing the secondary data, which were developed from the primary level. The reasons for the change of paradigm regarding the treatment of quality are considered. As the cascading poor quality of geodetic data can become a serious threat for the reputation of the profession of geodesy, several contemporary applications and projects are described in which this has already happened. In the conclusion, proposals are given for improving the situationion.


Aerial laser scanning (LIDAR) enables quick acquisition of terrain data and it can be used for the study of terrain under the vegetation. Therefore LIDAR is very appropriate for different geomorphologic studies. In this paper different characteristics of LIDAR are described, especially those which are important for decision, if LIDAR data are appropriate for the possible needs. The most important factors are the number of points per area unit (points/m 2) and the positional accuracy of the LIDAR data. On the example of landslides, rockfalls and different karst features the most suitable LIDAR data sets are defined. Based on the dimension of different geomorphologic features the number of LIDAR points per square meter will be defined. The largest landslides and different karst features can be studied with LIDAR data of 5 to 12 points/m 2. For medium extent landslides and smaller rockfalls the usage of more than 12 points/m 2 is recommended. For monitoring of more dynamic geomorphologic features, such as landslides, very accurate LIDAR data is needed. For static features, such as different karst features, only average LIDAR accuracy is needed.


In September 2010, one of the greatest floods in recent decades affected Slovenia, following intense rain between September 16th and 19th. Members of the Anton Melik Geographical Institute of the Scientific Research Centre of the Slovenian Academy of Sciences and Arts made their first terrestrial oblique imaging of the floods on Ljubljansko Barje (the Ljubljana moor) from Sv. Ana hill over Podpeč on the September 20th, 2010. The floods on the Ljubljana moor, Radensko polje and Dobrepolje were later also covered with handheld imaging made from helicopter on September 23rd, 2010. Terrestrial imaging was made in the time of the highest waters and the imaging from helicopter when the floods were retreating. The floods on Ljubljana moor around Podpeč are presented. Images made with the Canon PowerShot SX10 IS non-metric camera were used. The camera was calibrated afterwards, but the calibration data could not be used directly due to not knowing the parameters of zoom in the time of imaging.The flooding boundary was measured from the non-metric images with the interactive orientation of image on the DEM. The results of interactive orientation of non-metric images made with the photogrammetrically derived DEM with a cell size of 5 m × 5 m and LiDAR derived DEM with a cell size of 1 m × 1 m are presented. The evaluation of the method for the 3D data acquisition is also made.


A procedure of robust determination of the approximate coordinates of points in a horizontal geodetic network is presented. The primary aim is not accuracy but the reliability of the obtained coordinates. The motivation is to enable further processing according to the Gauss-Markov model. It is a linear mathematical model, thus the approximate values of unknowns are necessary input data. Disposable methods of determining coordinates of points and combinatorics of over-determined solutions dependent upon redundant observations are discussed. A geometrical approach is used, based on the fact that every point is an intersection of a pair of curves. The geometrical quality of each individual solution is evaluated from the intersection angle of both curves. A weight assigned to each solution is a function of that angle. Calculating coordinates is a successive procedure; each step assures the determination of one network point. The algorithm comprises searching for a typical solution among all solutions for an individual point. In order to avoid eventual gross errors, the procedure is based on robust statistics. The efficiency of three basic measures of location is tested on a practical example. The point is a generalization of mean, median, and mode i.e. the centre of mass, spatial median, and spatial mode. Gross errors are introduced into the network by using a Monte Carlo simulation.


Cekada M.T.,Geodetski Institute Slovenije | Zorn M.,Geografski Institute Antona Melika | Kaufmann V.,University of Graz | Lieb G.K.,University of Graz
Geodetski Vestnik | Year: 2012

In the last century and a half, average summer temperatures have slowly been rising worldwide. The most observable consequence of this is the change in glacier sizes. For monitoring glacier area and volume, various measuring techniques exist-from measurements with a measuring tape and geodetic measurements to remote sensing and photogrammetry. A comparison of different measuring techniques on two Slovenian glaciers (the Triglav and Skuta glaciers) and two Austrian glaciers (the Gössnitzkees and Hornkees glaciers) is made. A long-term glacial retreat trend is presented for the Gössnitzkees, Hornkees, and Triglav glaciers because these glaciers can be monitored throughout the entire twentieth century by means of archival data. Despite their different sizes, the annual trend of glacial retreat was approximately the same in the period between 1929 and 2006.

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