2019
DOI: 10.1007/s11056-019-09754-5
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Monitoring forest structure to guide adaptive management of forest restoration: a review of remote sensing approaches

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Cited by 125 publications
(91 citation statements)
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References 132 publications
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“…Forest structural complexity has been widely studied (Camarretta et al., 2020; Ishii et al., 2004; McElhinny et al., 2005), but there is less research on tree structural complexity, which was the focus of this study. TLS can provide traditional tree attributes (i.e., DBH, volume, crown dimensions) for characterizing tree structure, but its potential can also be expanded for new attributes.…”
Section: Discussionmentioning
confidence: 99%
“…Forest structural complexity has been widely studied (Camarretta et al., 2020; Ishii et al., 2004; McElhinny et al., 2005), but there is less research on tree structural complexity, which was the focus of this study. TLS can provide traditional tree attributes (i.e., DBH, volume, crown dimensions) for characterizing tree structure, but its potential can also be expanded for new attributes.…”
Section: Discussionmentioning
confidence: 99%
“…These results can be useful to manage C. libani natural and non-natural stands. Afforestation programs by ENM models could be carried out to deal with the expected climate change together with other disciplines such as remote sensing (Camarretta et al 2020).…”
Section: Discussionmentioning
confidence: 99%
“…While we are now able to quantify the structural complexity of forests, we still lack a clear picture of the spatial patterns of structural complexity at the stand level [40]. After identifying the target structural complexity at the stand level, e.g., by taking the structural complexity of an old-growth forest as a reference, it is also crucial to identify the structural characteristics of such a reference that resulted in a given complexity.…”
Section: Introductionmentioning
confidence: 99%