All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Very High Density Point Clouds from UAV Laser Scanning for Automatic Tree Stem Detection and Direct Diameter Measurement

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F20%3A85003" target="_blank" >RIV/60460709:41320/20:85003 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.mdpi.com/2072-4292/12/8/1236" target="_blank" >https://www.mdpi.com/2072-4292/12/8/1236</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3390/rs12081236" target="_blank" >10.3390/rs12081236</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Very High Density Point Clouds from UAV Laser Scanning for Automatic Tree Stem Detection and Direct Diameter Measurement

  • Original language description

    Three-dimensional light detection and ranging (LiDAR) point clouds acquired from unmanned aerial vehicles (UAVs) represent a relatively new type of remotely sensed data. Point cloud density of thousands of points per square meter with survey-grade accuracy makes the UAV laser scanning (ULS) a very suitable tool for detailed mapping of forest environment. We used RIEGL VUX-SYS to scan forest stands of Norway spruce and Scots pine, the two most important economic species of central European forests, and evaluated the suitability of point clouds for individual tree stem detection and stem diameter estimation in a fully automated workflow. We segmented tree stems based on point densities in voxels in subcanopy space and applied three methods of robust circle fitting to fit cross-sections along the stems: (1) Hough transform, (2) random sample consensus (RANSAC), and (3) robust least trimmed squares (RLTS). We detected correctly 99% and 100% of all trees in research plots for spruce and pine, respectively

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20705 - Remote sensing

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Remote Sensing

  • ISSN

    2072-4292

  • e-ISSN

  • Volume of the periodical

    12

  • Issue of the periodical within the volume

    8

  • Country of publishing house

    NN -

  • Number of pages

    20

  • Pages from-to

    1-20

  • UT code for WoS article

    000534628800009

  • EID of the result in the Scopus database

    2-s2.0-85084547638