Journal cover Journal topic
Geoscientific Instrumentation, Methods and Data Systems An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 1.182 IF 1.182
  • IF 5-year value: 1.437 IF 5-year
    1.437
  • CiteScore value: 3.0 CiteScore
    3.0
  • SNIP value: 0.686 SNIP 0.686
  • IPP value: 1.36 IPP 1.36
  • SJR value: 0.538 SJR 0.538
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 11 Scimago H
    index 11
  • h5-index value: 13 h5-index 13
Preprints
https://doi.org/10.5194/gid-5-549-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gid-5-549-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  21 Dec 2015

21 Dec 2015

Review status
This preprint has been withdrawn by the authors.

Estimation of forest parameters using airborne laser scanning data

J. Cohen J. Cohen
  • Finnish Meteorological Institute, P.O. BOX 503, 00101 Helsinki, Finland

Abstract. Methods for the estimation of forest characteristics by airborne laser scanning (ALS) data have been introduced by several authors. Tree height (TH) and canopy closure (CC) describing the forest properties can be used in forest, construction and industry applications, as well as research and decision making. The National Land Survey has been collecting ALS data from Finland since 2008 to generate a nationwide high resolution digital elevation model. Although this data has been collected in leaf-off conditions, it still has the potential to be utilized in forest mapping. A method where this data is used for the estimation of CC and TH in the boreal forest region is presented in this paper. Evaluation was conducted in eight test areas across Finland by comparing the results with corresponding Multi-Source National Forest Inventory (MS-NFI) datasets. The ALS based CC and TH maps were generally in a good agreement with the MS-NFI data. As expected, deciduous forests caused some underestimation in CC and TH, but the effect was not major in any of the test areas. The processing chain has been fully automated enabling fast generation of forest maps for different areas.

This preprint has been withdrawn.

J. Cohen

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

J. Cohen

J. Cohen

Viewed

Total article views: 1,008 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
471 481 56 1,008 47 68
  • HTML: 471
  • PDF: 481
  • XML: 56
  • Total: 1,008
  • BibTeX: 47
  • EndNote: 68
Views and downloads (calculated since 21 Dec 2015)
Cumulative views and downloads (calculated since 21 Dec 2015)

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 17 Sep 2020
Publications Copernicus
Download
Withdrawal notice

This preprint has been withdrawn.

Short summary
An automatic process for the estimation of forest properties in high spatial resolution using National Land Survey's airborne laser scanning data is presented. Results were evaluated by compering against national MS-NFI forest data. The estimation accuracy was generally good, but deciduous forests in leaf-off conditions caused somewhat underestimation. The method can be used to support e.g. forest managing, construction planning, wood industry and other remote sensing applications and research.
An automatic process for the estimation of forest properties in high spatial resolution using...
Citation