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Tree Height Growth Modelling Using LiDAR-Derived Topography Information
被引:4
作者:
Kobal, Milan
[1
]
Hladnik, David
[1
]
机构:
[1] Univ Ljubljana, Biotech Fac, Dept Forestry & Renewable Forest Resources, Vecna Pot 83, Ljubljana 1000, Slovenia
关键词:
stem analysis;
airborne laser scanning;
DEM;
silver fir;
Dinaric Mountains;
karst;
FOREST SITE PRODUCTIVITY;
SPECIES COMPOSITION;
LANDSCAPE;
MOUNTAIN;
INDEX;
PREDICTION;
VARIABLES;
STANDS;
AREA;
D O I:
10.3390/ijgi10060419
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
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.
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页数:16
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