Standard deviation as the optimization criterion in the OptD method and its influence on the generated DTM - Publikacja - MOST Wiedzy

Wyszukiwarka

Standard deviation as the optimization criterion in the OptD method and its influence on the generated DTM

Abstrakt

Reduction of the measurement dataset is one of the current issues related to constantly developing technologies that provide large datasets, eg. laser scanning. It could seems that presence and evolution of processors computer, increase of hard drive capacity etc. is the solution for development of such large datasets. And in fact it is, however, the “lighter” datasets are easier to work with. Additionally, reduced datasets can be exchange/transfer/download faster via internet or cloud stored. Therefore the issue of data reduction algorithms/methods is continuously relevant. In this paper authors presented the results of the study whether the standard deviation of measurement data can be used as optimization criterion in the process of dataset reduction conducted by means of the OptD method. The OptD is based on the cartographic generalization methods. In iterative process irrelevant points are being removed and those that characteristic are being preserved, what in results means more points in complex fragments of scanned object/surface and less in flat/uncomplicated area. Obtained reduced datasets were then the basis for DTMs generation. For DTMs assessment RMSE was calculated

Cytowania

  • 0

    CrossRef

  • 0

    Web of Science

  • 1

    Scopus

Cytuj jako

Autorzy (2)

Pełna treść

pełna treść publikacji nie jest dostępna w portalu

Informacje szczegółowe

Kategoria:
Publikacja w czasopiśmie
Typ:
publikacja w in. zagranicznym czasopiśmie naukowym (tylko język obcy)
Opublikowano w:
E3S Web of Conferences nr 63, strony 1 - 5,
ISSN:
Język:
angielski
Rok wydania:
2018
Opis bibliograficzny:
Błaszczak-Bąk W., Sobieraj-Żłobińska A.. Standard deviation as the optimization criterion in the OptD method and its influence on the generated DTM. E3S Web of Conferences, 2018, Vol. 63, , s.1-5
DOI:
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1051/e3sconf/20186300011
Weryfikacja:
Politechnika Gdańska

wyświetlono 22 razy

Publikacje, które mogą cię zainteresować

Meta Tagi