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Naslov:Identifying even- and uneven-aged forest stands using low-resolution nationwide lidar data
Avtorji:ID Pintar, Anže Martin (Avtor)
ID Skudnik, Mitja (Avtor)
Datoteke:.pdf PDF - Predstavitvena datoteka, prenos (15,08 MB)
MD5: F965FA5DCEE0786E4CE3FFA25FC4E7F7
 
URL URL - Izvorni URL, za dostop obiščite https://www.mdpi.com/1999-4907/15/8/1407
 
Jezik:Angleški jezik
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:Logo SciVie - Gozdarski inštitut Slovenije
Povzetek: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.
Ključne besede:uneven-aged forest, lidar data, canopy height model, voxels, canopy height diversity
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Datum objave:01.01.2024
Leto izida:2024
Št. strani:str. 1-16
Številčenje:Vol. 15, iss. 8, [articel no.] 1407
PID:20.500.12556/DiRROS-20201 Novo okno
UDK:630*53
ISSN pri članku:1999-4907
DOI:10.3390/f15081407 Novo okno
COBISS.SI-ID:204230147 Novo okno
Opomba:Nasl. z nasl. zaslona; Opis vira z dne 13. 8. 2024;
Datum objave v DiRROS:13.08.2024
Število ogledov:287
Število prenosov:672
Metapodatki:XML DC-XML DC-RDF
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Gradivo je del revije

Naslov:Forests
Skrajšan naslov:Forests
Založnik:MDPI
ISSN:1999-4907
COBISS.SI-ID:3872166 Novo okno

Gradivo je financirano iz projekta

Financer:ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
Številka projekta:P4-0107-2020
Naslov:Gozdna biologija, ekologija in tehnologija

Financer:ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
Številka projekta:J2-3055-2021
Naslov:ROVI – Združevanje in obdelava radarskih in optičnih časovnih vrst satelitskih posnetkov za spremljanje naravnega okolja

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:lidar, višina krošnje, drevesne krošnje


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