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Title:Identifying even- and uneven-aged forest stands using low-resolution nationwide lidar data
Authors:ID Pintar, Anže Martin (Author)
ID Skudnik, Mitja (Author)
Files:.pdf PDF - Presentation file, download (15,08 MB)
MD5: F965FA5DCEE0786E4CE3FFA25FC4E7F7
 
URL URL - Source URL, visit https://www.mdpi.com/1999-4907/15/8/1407
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo SciVie - Slovenian Forestry Institute
Abstract:In uneven-aged forests, trees of different diameters, heights, and ages are located in a small area, which is due to the felling of individual trees or groups of trees, as well as small-scale natural disturbances. In this article, we present an objective method for classifying forest stands into even- and uneven-aged stands based on freely available low-resolution (with an average recording density of 5 points/m2) national lidar data. The canopy closure, dominant height, and canopy height diversity from the canopy height model and the voxels derived from lidar data were used to classify the forest stands. Both approaches for determining forest structural diversity (canopy height diversity—CHDCHM and CHDV) yielded similar results, namely two clusters of even- and uneven-aged stands, although the differences in vertical diversity between even- and uneven-aged stands were greater when using CHM. The first analysis, using CHM for the CHD assessment, estimated the uneven-aged forest area as 49.3%, whereas the second analysis using voxels estimated it as 34.3%. We concluded that in areas with low laser scanner density, CHM analysis is a more appropriate method for assessing forest stand height heterogeneity. The advantage of detecting uneven-aged structures with voxels is that we were able to detect shade-tolerant species of varying age classes beneath a dense canopy of mature, dominant trees. The CHDCHM values were estimated to be 1.83 and 1.86 for uneven-aged forests, whereas they were 1.57 and 1.58 for mature even-aged forests. The CHDV values were estimated as 1.50 and 1.62 for uneven-aged forests, while they were 1.33 and 1.48 for mature even-aged forests. The classification of stands based on lidar data was validated with data from measurements on permanent sample plots. Statistically significantly lower average values of the homogeneity index and higher values of the Shannon–Wiener index from field measurements confirm the success of the classification of stands based on lidar data as uneven-aged forests.
Keywords:uneven-aged forest, lidar data, canopy height model, voxels, canopy height diversity
Publication status:Published
Publication version:Version of Record
Publication date:01.01.2024
Year of publishing:2024
Number of pages:str. 1-16
Numbering:Vol. 15, iss. 8, [articel no.] 1407
PID:20.500.12556/DiRROS-20201 New window
UDC:630*53
ISSN on article:1999-4907
DOI:10.3390/f15081407 New window
COBISS.SI-ID:204230147 New window
Note:Nasl. z nasl. zaslona; Opis vira z dne 13. 8. 2024;
Publication date in DiRROS:13.08.2024
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Downloads:685
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Record is a part of a journal

Title:Forests
Shortened title:Forests
Publisher:MDPI
ISSN:1999-4907
COBISS.SI-ID:3872166 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P4-0107-2020
Name:Gozdna biologija, ekologija in tehnologija

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:J2-3055-2021
Name:ROVI – Združevanje in obdelava radarskih in optičnih časovnih vrst satelitskih posnetkov za spremljanje naravnega okolja

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:lidar, višina krošnje, drevesne krošnje


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