Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 432420
Title Mapping tropical forest trees using high-resolution aerial digital photographs
Author(s) Garzon-Lopez, C.X.; Bohlman, S.A.; Olff, H.; Jansen, P.A.
Source Biotropica 45 (2013)3. - ISSN 0006-3606 - p. 308 - 316.
DOI https://doi.org/10.1111/btp.12009
Department(s) Wildlife Ecology and Conservation
Forest Ecology and Forest Management
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2013
Keyword(s) rain-forest - spatial-patterns - scale - dispersal - imagery - identification - biodiversity - limitation - management - dynamics
Abstract The spatial arrangement of tree species is a key aspect of community ecology. Because tree species in tropical forests occur at low densities, it is logistically challenging to measure distributions across large areas. In this study, we evaluated the potential use of canopy tree crown maps, derived from high-resolution aerial digital photographs, as a relatively simple method for measuring large-scale tree distributions. At Barro Colorado Island, Panama, we used high-resolution aerial digital photographs (~0.129 m/pixel) to identify tree species and map crown distributions of four target tree species. We determined crown mapping accuracy by comparing aerial and ground-mapped distributions and tested whether the spatial characteristics of the crown maps reflect those of the ground-mapped trees. Nearly a quarter (22%) of the common canopy species had sufficiently distinctive crowns to be good candidates for reliable mapping. The errors of commission (crowns misidentified as a target species) were relatively low, but the errors of omission (missed canopy trees of the target species) were high. Only 40 percent of canopy individuals were mapped on the air photographs. Despite failing to accurately predict exact abundances of canopy trees, crown distributions accurately reproduced the clumping patterns and spatial autocorrelation features of three of four tree species and predicted areas of high and low abundance. We discuss a range of ecological and forest management applications for which this method can be useful.
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