Tree Height Growth Modelling Using LiDAR-Derived Topography Information
The concepts of ecotopes and forest sites are used to describe the correlative complexes defined by landform, vegetation structure, forest stand characteristics and the relationship between soil and physiography. Physically heterogeneous landscapes such as karst, which is characterized by abundant s...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/10/6/419 |
| _version_ | 1797529514297786368 |
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| author | Milan Kobal David Hladnik |
| author_facet | Milan Kobal David Hladnik |
| author_sort | Milan Kobal |
| collection | DOAJ |
| description | The concepts of ecotopes and forest sites are used to describe the correlative complexes defined by landform, vegetation structure, forest stand characteristics and the relationship between soil and physiography. Physically heterogeneous landscapes such as karst, which is characterized by abundant sinkholes and outcrops, exhibit diverse microtopography. Understanding the variation in the growth of trees in a heterogeneous topography is important for sustainable forest management. An R script for detailed stem analysis was used to reconstruct the height growth histories of individual trees (steam analysis). The results of this study reveal that the topographic factors influencing the height growth of silver fir trees can be detected within forest stands. Using topography modelling, we classified silver fir trees into groups with significant differences in height growth. This study provides a sound basis for the comparison of forest site differences and may be useful in the calibration of models for various tree species. |
| first_indexed | 2024-03-10T10:14:56Z |
| format | Article |
| id | doaj.art-af4e6e249186428ab91ec14056f4cb63 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T10:14:56Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-af4e6e249186428ab91ec14056f4cb632023-11-22T00:53:37ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-06-0110641910.3390/ijgi10060419Tree Height Growth Modelling Using LiDAR-Derived Topography InformationMilan Kobal0David Hladnik1Department of Forestry and Renewable Forest Resources, Biotechnical Faculty, University of Ljubljana, Večna Pot 83, 1000 Ljubljana, SloveniaDepartment of Forestry and Renewable Forest Resources, Biotechnical Faculty, University of Ljubljana, Večna Pot 83, 1000 Ljubljana, SloveniaThe concepts of ecotopes and forest sites are used to describe the correlative complexes defined by landform, vegetation structure, forest stand characteristics and the relationship between soil and physiography. Physically heterogeneous landscapes such as karst, which is characterized by abundant sinkholes and outcrops, exhibit diverse microtopography. Understanding the variation in the growth of trees in a heterogeneous topography is important for sustainable forest management. An R script for detailed stem analysis was used to reconstruct the height growth histories of individual trees (steam analysis). The results of this study reveal that the topographic factors influencing the height growth of silver fir trees can be detected within forest stands. Using topography modelling, we classified silver fir trees into groups with significant differences in height growth. This study provides a sound basis for the comparison of forest site differences and may be useful in the calibration of models for various tree species.https://www.mdpi.com/2220-9964/10/6/419stem analysisairborne laser scanningDEMsilver firDinaric Mountainskarst |
| spellingShingle | Milan Kobal David Hladnik Tree Height Growth Modelling Using LiDAR-Derived Topography Information ISPRS International Journal of Geo-Information stem analysis airborne laser scanning DEM silver fir Dinaric Mountains karst |
| title | Tree Height Growth Modelling Using LiDAR-Derived Topography Information |
| title_full | Tree Height Growth Modelling Using LiDAR-Derived Topography Information |
| title_fullStr | Tree Height Growth Modelling Using LiDAR-Derived Topography Information |
| title_full_unstemmed | Tree Height Growth Modelling Using LiDAR-Derived Topography Information |
| title_short | Tree Height Growth Modelling Using LiDAR-Derived Topography Information |
| title_sort | tree height growth modelling using lidar derived topography information |
| topic | stem analysis airborne laser scanning DEM silver fir Dinaric Mountains karst |
| url | https://www.mdpi.com/2220-9964/10/6/419 |
| work_keys_str_mv | AT milankobal treeheightgrowthmodellingusinglidarderivedtopographyinformation AT davidhladnik treeheightgrowthmodellingusinglidarderivedtopographyinformation |