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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-cce00ae0-9b66-4ae6-9fc9-654e57300f2e

Czasopismo

Archiwum Fotogrametrii, Kartografii i Teledetekcji

Tytuł artykułu

Reduction of DTM obtained from LiDAR data for flood modeling

Autorzy Bakuła, K. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
Abstrakty
EN Recent years the cataclysm of flood has occurred in many regions around the world. For this reason, so much attention is focused on prediction of this cataclysm by creating flood risk maps and hydrodynamic – numerical simulation of flood water which are based on Digital Terrain Model (DTM). The modern techniques for automatic data acquisition provide very abundant amount of points. Actually, Light Detection and Ranging (LiDAR) is the most effective data source for DTM creation with density of one to few points per square meter and good height accuracy of less than 15 cm. This high redundancy of data is essential problem for algorithms used in programs for flood modeling. Many software generating such models are restricted with respect to the maximum number of points in DTM. Hundreds of thousands of points are too large number for complex calculations which describe fluid model of the flood water. In order to obtain reliable and accurate results, it is necessary to have DTM with an appropriate accuracy. The flood disaster also occurs in large areas what usually is associated with large data sets. However, it is possible to provide suitable DTM for flood modeling by its generalization without losing its accuracy, which could still ensure sufficient precision for hydrodynamic – numerical calculations. In this paper six reduction algorithms were tested to obtain DTM with small number of points and with accuracy comparable to the original model created from LiDAR data. The main criteria for this comparison was the relation between accuracy and reduction coefficient of final result. Methods used in this research were based on different DTM structures. GRID, TIN and hierarchical structures were compared in various approaches to obtain the most reduced and the most accurate terrain model of two study areas. As the result of the experiment the best methods for data reduction were chosen. Over 90% reduction rate and less than 20 cm root mean standard error were achieved in practice for different types of terrain with respect to input DTM. It was noted that hybrid and quad-tree grid based models can be even more efficient than a typical uniform GRID or TIN one.
Słowa kluczowe
PL DTM   generalizacja   LIDAR   algorytm   struktura danych  
EN DTM   generalization   lidar   algorithm   data structure  
Wydawca Zarząd Główny Stowarzyszenia Geodetów Polskich
Czasopismo Archiwum Fotogrametrii, Kartografii i Teledetekcji
Rocznik 2011
Tom Vol. 22
Strony 51--61
Opis fizyczny Bibliogr. 14 poz.
Twórcy
autor Bakuła, K.
  • Department of Photogrammetry Remote Sensing and Spatial Information Systems Faculty of Geodesy and Cartography, Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warszawa, Poland, k.bakula@gik.pw.edu.pl
Bibliografia
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12. Martín M. T., Rodríguez J., Irigoyen J., Martínez-Llario J. C., Arias P., 2009. Semiautomatic Process for Hybrid DTM Generalization based on Structural Elements Multianalysis. In: The Cartographic Journal, Vol. 46, pp. 146-154(9)
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14. Zhou Q., Chen Y, 2011. Generalization of DEM for terrain analysis using a compound method. In: ISPRS Journal of Photogrammetry and Remote Sensing, 66, pp.38-45.
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