Publication detail

Detecting Forest Road Wearing Course Damage Using Different Methods of Remote Sensing

HRŮZA, P. MIKITA, T. TYAGUR, N. KREJZA, Z. CIBULKA, M. PROCHÁZKOVÁ, A. PATOČKA, Z.

Original Title

Detecting Forest Road Wearing Course Damage Using Different Methods of Remote Sensing

Type

journal article in Web of Science

Language

English

Original Abstract

Currently, a large part of forest roads with a bituminous surface course constructed in the Czech Republic in the second half of the last century has been worn out. The aim of the study is to verify the possibility and the accuracy of the road wearing course damage detected by four different remote sensing methods: close range photogrammetry, terrestrial laser scanning, mobile laser scanning and airborne laser scanning. At the beginning of verification, cross sections of the road surface were surveyed geodetically and then compared with the cross sections created in the DTMs which were acquired using the four methods mentioned above

Keywords

mobile laser scanning; terrestrial laser scanning; photogrammetry; airborne laser scanning; forest road wearing course

Authors

HRŮZA, P.; MIKITA, T.; TYAGUR, N.; KREJZA, Z.; CIBULKA, M.; PROCHÁZKOVÁ, A.; PATOČKA, Z.

Released

21. 3. 2018

Publisher

MDPI AG

ISBN

2072-4292

Periodical

Remote Sensing

Year of study

2018

Number

10

State

Swiss Confederation

Pages from

1

Pages to

17

Pages count

17

URL

https://www.researchgate.net/publication/323938486_Detecting_Forest_Road_Wearing_Course_Damage_Using_Different_Methods_of_Remote_Sensing

BibTex

@article{BUT153306,
  author="Petr {Hrůza} and Tomáš {Mikita} and Nataliya {Tyagur} and Zdeněk {Krejza} and Miloš {Cibulka} and Andrea {Procházková} and Zdeněk {Patočka}",
  title="Detecting Forest Road Wearing Course Damage Using Different Methods of Remote Sensing
",
  journal="Remote Sensing",
  year="2018",
  volume="2018",
  number="10",
  pages="1--17",
  doi="10.3390/rs10040492",
  issn="2072-4292",
  url="https://www.researchgate.net/publication/323938486_Detecting_Forest_Road_Wearing_Course_Damage_Using_Different_Methods_of_Remote_Sensing"
}