Weather-related disasters represent a major threat to the sustainable development of society. This study focuses directly on the assessment of the state of spatial information quality for the needs of hydrodynamic modeling. Based on the selected procedures and methods designed for the collection and processing of spatial information, the aim of this study was to assess their qualitative level of suitability for 3D flood event modeling in accordance with the Infrastructure for Spatial Information in the European Community (INSPIRE) Directive. In the evaluation process we entered geodetic measurements and the digital relief model 3.5 (DMR 3.5) available for the territory of the Slovak Republic. The result of this study is an assessment of the qualitative analysis on three levels: (i) main channel and surrounding topography data from geodetic measurements; (ii) digital relief model; and (iii) hydrodynamic/hydraulic modeling. The qualitative aspect of the input data shows the sensitivity of a given model to changes in the input data quality condition. The average spatial error in the determination of a point’s position was calculated as 0.017 m of all measured points along a watercourse and its slope foot and slope edge. Although the declared accuracy of DMR 3.5 is assumed to be ±2.50 m, in some of the sections in the selected area there were differences in elevation up to 4.79 m. For this reason, we needed a combination of DMR 3.5 and geodetic measurements to refine the input model for the process of hydrodynamic modeling. The quality of the hydrological data for the monitored N annual flow levels was of fourth-class reliability for the selected area.
The present article summarizes the progress and results of geodetic works during the construction of a geodetic network inside the Dobšinská Ice Cave underground space to monitor temporal and spatial changes in its ice filling. In order to objectively evaluate the changes, parameter estimations of the first-and second-order of the geodetic network from the set of field geodetic measurements were provided, and a robust analysis of the network was applied in terms of the assessment of impacts of potential outlier measurements on the network geometry. AbstractPredložený príspevok sumarizuje priebeh a výsledky geodetických prác počas budovania polohovej geodetickej siete založenej v podzemných priestoroch Dobšinskej ľadovej jaskyne za účelom monitorovania časových a priestorových zmien jej ľadovej výplne. V snahe objektívneho vyhodnotenia týchto zmien boli zo súborov terénnych geodetických meraní stanovené odhady I. a II. rádu geodetickej siete a z hľadiska posúdenia vplyvu potenciálnych odľahlých meraní na geometriu siete bola aplikovaná robustná analýza tejto siete.
The basis of mathematical analysis of geodetic measurements is the method of least squares (LSM), whose bicentenary we celebrated in 2006. In geodetic practice, we quite often encounter the phenomenon when outlier measurements penetrate into the set of measured data as a result of e.g. the impact of physical environment. That fact led to modifications of LSM that have been increasingly published mainly in foreign literature in recent years. The mentioned alternative estimation methods are e.g. robust estimation methods and methods in linear programming. The aim of the present paper is to compare LSM with the robust estimation methods on an example of a regression line. AbstraktZákladom matematickej analýzy dát je metóda najmenších štvorcov (MNŠ), ktorej dvesté výročie sme si pripomenuli v roku 2006. V geodetickej praxi sa v dôsledku napr. vplyvu fyzikálneho prostredia pomerne často stretávame s javom, že do súboru meraných dát prenikajú odľahlé merania. Práve táto skutočnosť viedla k modifikáciám MNŠ ktoré sa v posledných rokoch čoraz častejšie publikujú predovšetkým v zahraničnej literatúre. Spomínanými alternatívnymi odhadovacími metódami, sú napr. robustné odhadovacie metódy a metódy lineárneho programovania. Náplňou predloženého príspevku je porovnanie MNŠ s robustnými odhadovacími metódami na príklade regresnej priamky.
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