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Research article - Peer-reviewed, 2019

Tree crown segmentation based on a tree crown density model derived from Airborne Laser Scanning

Holmgren, Johan;Lindberg, Eva;

Abstract

This letter describes a new algorithm for automatic tree crown delineation based on a model of tree crown density, and its validation. The tree crown density model was first used to create a correlation surface, which was then input to a standard watershed segmentation algorithm for delineation of tree crowns. The use of a model in an early step of the algorithm neatly solves the problem of scale selection. In earlier studies, correlation surfaces have been used for tree crown segmentation, involving modelling tree crowns as solid geometric shapes. The new algorithm applies a density model of tree crowns, which improves the model's suitability for segmentation of Airborne Laser Scanning (ALS) data because laser returns are located inside tree crowns. The algorithm was validated using data acquired for 36 circular (40 m radius) field plots in southern Sweden. The algorithm detected high proportions of field-measured trees (40-97% of live trees in the 36 field plots: 85% on average). The average proportion of detected basal area (cross-sectional area of tree stems, 1.3 m above ground) was 93% (range: 84-99%). The algorithm was used with discrete return ALS point data, but the computation principle also allows delineation of tree crowns in ALS waveform data.

Published in

Remote Sensing Letters

2019, volume: 10, number: 12, pages: 1143-1152
Publisher: TAYLOR & FRANCIS LTD

Authors' information

Swedish University of Agricultural Sciences, Department of Forest Resource Management
Swedish University of Agricultural Sciences, Department of Forest Resource Management

Associated SLU-program

Remningstorp

UKÄ Subject classification

Remote Sensing
Forest Science

Publication Identifiers

DOI: https://doi.org/10.1080/2150704X.2019.1658237

URI (permanent link to this page)

https://res.slu.se/id/publ/101610