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  Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data

Vaglio Laurin, G., Puletti, N., Hawthorne, W., Liesenberg, V., Corona, P., Papale, D., et al. (2016). Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data. Remote Sensing of Environment, 176, 163-176. doi:10.1016/j.rse.2016.01.017.

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 Creators:
Vaglio Laurin, Gaia1, Author
Puletti, Nicola, Author
Hawthorne, William, Author
Liesenberg, Veraldo, Author
Corona, Piermaria, Author
Papale, Dario, Author
Chen, Qi, Author
Valentini, Riccardo, Author
Affiliations:
1External Organizations, ou_persistent22              

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Free keywords: Earth Observations; In-situ Observations
 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.

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 Dates: 2016-01-212016-02-052016
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
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 Identifiers: Other: BEX511
DOI: 10.1016/j.rse.2016.01.017
 Degree: -

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Project name : BACI
Grant ID : 640176
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: Remote Sensing of Environment
Source Genre: Journal
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Publ. Info: New York : Elsevier
Pages: - Volume / Issue: 176 Sequence Number: - Start / End Page: 163 - 176 Identifier: ISSN: 0034-4257
CoNE: https://pure.mpg.de/cone/journals/resource/954925437513