Proposed Technology of lidar data processing to build DTM

• Autorzy: Błaszczak-Bąk W. , Janowski A.
• Języki publikacji: EN

Abstrakty

EN

Light Detection and Ranging (LiDAR) is a sensing technology whieh has application in building the Digital Terrain Model (DTM). A point cloud generated from laser scanning makes up the so-called large dataset, which is difficult and sometimes even impossible to use directly. Import of LiDAR point cloud into appropriate software and its processing is time-consuming and demands high computing power. Therefore, it is advisable to optimize the volume of observation results which make up the point cloud. The following paper presents operation of a modified algorithm for optimization of points' number in a large dataset [Błaszczak W., 2006]. The optimization involves reduction and uses existing cartographic generalization methods. The optimized dataset was filtered, and during the process the points representing the terrain were separated from data representing non-ground elements. Filtration was carried out with the application of a proposed new method including trend line in search belts, and the laser power used to register points. The optimized and filtered data set was then used to build a DTM. The results obtained encourage further detailed study of theoretical and empirical character.

Słowa kluczowe

EN

DTM; lidar; cartography

PL

DTM; LIDAR; kartografia

• Wydawca: Wydział Geodezji i Kartografii Politechniki Warszawskiej
• Czasopismo: Reports on Geodesy
• Rocznik: 2009
• Tom: z. 2/87
• Strony: 29--38
• Opis fizyczny: Bibliogr. 9 poz., rys., wykr.

Twórcy

autor

Błaszczak-Bąk W.

autor

Janowski A.

Bibliografia

• [1] Axelsson P., 2000: DEM generation from laser scanner data using adaptive TIN models. International Archives of Photogrammetry and Remote Sensing Vol. XXXIII/4B, Amsterdam.
• [2] Błaszczak W., 2006: Optymalizacja dużych zbiorów wyników pomiaru zasilający bazy danych systemówinformacji przestrzennej. Praca doktorska. Olsztyn.
• [3] Błaszczak W., Kamiński W., 2007: Data number reduction in measurement results set using optimization algorithm. FIG Working Week 2007. Strategic Integration of Surveying Services. The Hong Kong Institute of Surveyors. Hong Kong. CD-ROM.
• [4] Błaszczak W., Kamiński W., 2007: Optymalizacja dużych zbiorów wyników pomiaru zasilających bazy danych systemów informacji przestrzennej. Przegląd Geodezyjny nr 6/2007, str. 7-9.
• [5] Brovelli M. A., Cannata M., Longoni U. M., 2002: Managing and processing LIDAR data within GRASS. Proccedingsof the Open source GIS – GRASS user conference, Trento.
• [6] Hyyppä J., Pyssalo U., Hyyppä H., Samberg A., 2002: Elevation accuracy of laser scanning – derived digital terrain and target models inforest environment. International Archives of Photogrammetry and Remote Sensing, Vol. XXXIV/ 3A, Graz.
• [7] Marmol U., Jachimski J., 2004: A FFT based method of filtering airborne laser scanner data. International Archivesof Photogrammetry and Remote Sensing Vol. XXXIII/3, s. 1147-1152, Istanbul.
• [8] Vosselman G., 2001: Adjustment and filtering of raw laser altimetry data. OEEPE Workshop on Airborne Laserscanning and Interferometric SAR for Detailed Digital Elevation Models, Stockholm.
• [9] Wack R., Wimmer A., 2002: Digital terrain models from airborne laser scanner data – a grid based approach. International Archives of Photogrammetry and Remote Sensing, Vol. XXXIV / 3B, Graz.