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Abstract

To answer newscientific and ecological questions and monitormultiple forest changes, a fine scale characterization
of these ecosystems is needed, and could imply the mapping of specific species, of detailed forest types, and
of functional composition. This characterization can be now provided by the novel Earth Observation tools. This
study aims to contribute to understanding the innovation in forest and ecological research that can be brought in
by advanced remote sensing instruments, and proposes the guild mapping approach as a tool to efficientlymonitor
the varied tropical forest resources. We evaluated, in tropical Ghanaian forests, the ability of airborne
hyperspectral and simulated multispectral Sentinel-2 data, and derived vegetation indices and textures, to: distinguish
between two different forest types; to discriminate among selected dominant species; and to separate
trees species grouped according to their functional guilds: Pioneer, Non Pioneer Light Demanding, and Shade
Bearer. We then produced guild classification maps for each area using hyperspectral data. Our results showed
that with both hyperspectral and simulated Sentinel-2 data these discrimination tasks can be successfully accomplished.
Results also stressed the importance of texture features, especially if using the lower spectral and spatial
Sentinel-2 resolution data, and highlighted the important role of the new Sentinel-2 data for ecological monitoring.
Classification results showed a statistically significant improvement in overall accuracy using Support Vector
Machine, over Maximum Likelihood approach. We proposed the functional guilds mapping as an innovative
approach to: (i) monitor compositional changes, especially with respect to the effects of global climate change
on forests, and particularly in the tropical biome where the occurrence of hundreds of species prevents mapping
activities at species level; (ii) support large-scale forest inventories.