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Reduction of measurement data before Digital Terrain Model generation vs. DTM generalisation

Abstract

Modern data acquisition technologies provide large datasets that are not always necessary in its entirety to properly accomplish the goal of the study. In addition, such datasets are often cumbersome for rational processing, and their processing is time and labour consuming. Therefore, methods that enable to reduce the size of the measurement dataset, such as the generalization of the Digital Terrain Model (DTM) or the reduction method at the initial processing of measurement data, are often used. Such methods of reduction can include the Optimum Dataset method (OptD). The paper presents two approaches of decrease the LiDAR (Light Detection and Ranging) dataset. The first approach is based on the generalization of DTM in AutoCADCivil 3D 2018, the second is based on the OptD method. Obtained reduced datasets were used to create the isoline maps that depict overflow land in open-pit mining. The results of the study have allowed to formulate conclusions which show that the reduction must be well-thought and that the degree of reduction must be set in a way, that it allows to maintain the characteristics of the terrain.

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Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
SURVEY REVIEW no. 51, pages 422 - 430,
ISSN: 0039-6265
Language:
English
Publication year:
2018
Bibliographic description:
Błaszczak-Bąk W., Poniewiera M., Sobieraj-Żłobińska A., Kowalik M.: Reduction of measurement data before Digital Terrain Model generation vs. DTM generalisation// SURVEY REVIEW. -Vol. 51, iss. 368 (2018), s.422-430
DOI:
Digital Object Identifier (open in new tab) 10.1080/00396265.2018.1474685
Verified by:
Gdańsk University of Technology

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