Individual tree detection and spatial distribution analysis without reference data
Year: 2024
Type: article
Abstract: This study processed two 100x100m areas from LiDAR dataset: a forest and a mixed forest-plantation. Progressive Morphological Filtering (PMF) and Local Maximum Filtering (LMF) methods identified 257 trees in the forest and 47 in the mixed area, showing (depending on the method) partly random, partly regular spacing in the forest and clustering in mixed areas. The density assessments and nearest-neighbour evaluations with G statistic, K statistic, Monte Carlo method, and quadrat tests revealed a significant difference in tree distribution, highlighting the effectiveness of these methods for detecting spatial patterns in diverse forest environments, too.
DOI: 10.20312/dim.2024.04
Authors: Zsolt Tóth, Péter Farkas, Adrienn Novotni
Institution: University of Sopron
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: diamond
OpenAlex ID: W4409673224