Individual tree detection and spatial distribution analysis without reference data

Tóth, Zsolt György and Farkas, Péter and Novotni, Adrienn (2024) Individual tree detection and spatial distribution analysis without reference data. DIMENZIÓK: MATEMATIKAI KÖZLEMÉNYEK, 12. pp. 33-41. ISSN 2064-2172

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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.

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