Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2067/2087
Titolo: Exploring forest structural complexity by multi-scale segmentation of VHR imagery
Autori: Lamonaca, Andrea
Corona, Piermaria
Barbati, Anna
Parole chiave: Structural complexity;Spatial heterogeneity;Multi-scale segmentation;QuickBird;Beech forest;Neighbourhood-based structural indices
Data pubblicazione: 2008
Editore: Elsevier
Fonte: Lamonaca, A., Corona, P., Barbati, A. 2008. Exploring forest structural complexity by multi-scale segmentation of VHR imagery. "Remote Sensing of Environment" 112 ( 6): 2839-2849.
Forests are complex ecological systems, characterised by multiple-scale structural and dynamical patterns which are not inferable from a system description that spans only a narrow window of resolution; this makes their investigation a difficult task using standard field sampling protocols.

We segment a QuickBird image covering a beech forest in an initial stage of old-growthness – showing, accordingly, a good degree of structural complexity – into three segmentation levels. We apply field-based diversity indices of tree size, spacing, species assemblage to quantify structural heterogeneity amongst forest regions delineated by segmentation. The aim of the study is to evaluate, on a statistical basis, the relationships between spectrally delineated image segments and observed spatial heterogeneity in forest structure, including gaps in the outer canopy. Results show that: some 45% of the segments generated at the coarser segmentation scale (level 1) are surrounded by structurally different neighbours; level 2 segments distinguish spatial heterogeneity in forest structure in about 63% of level 1 segments; level 3 image segments detect better canopy gaps, rather than differences in the spatial pattern of the investigated structural indices.

Results support also the idea of a mixture of macro and micro structural heterogeneity within the beech forest: large size populations of trees homogeneous for the examined structural indices at the coarser segmentation level, when analysed at a finer scale, are internally heterogeneous; and vice versa.

Findings from this study demonstrate that multiresolution segmentation is able to delineate scale-dependent patterns of forest structural heterogeneity, even in an initial stage of old-growth structural differentiation. This tool has therefore a potential to improve the sampling design of field surveys aimed at characterizing forest structural complexity across multiple spatio-temporal scales.
L'articolo è disponibile sul sito dell'editore www.sciencedirect.com
URI: http://hdl.handle.net/2067/2087
ISSN: 0034-4257
DOI: 10.1016/j.rse.2008.01.017
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