Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/47818
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dc.contributor.authorVaglio Laurin, Gaiait
dc.contributor.authorPuletti, Nicolait
dc.contributor.authorHawthorne, Williamit
dc.contributor.authorLiesenberg, Veraldoit
dc.contributor.authorCorona, Piermariait
dc.contributor.authorPapale, Darioit
dc.contributor.authorChen, Qiit
dc.contributor.authorValentini, Riccardoit
dc.date.accessioned2022-05-24T12:35:09Z-
dc.date.available2022-05-24T12:35:09Z-
dc.date.issued2016it
dc.identifier.issn0034-4257it
dc.identifier.urihttp://hdl.handle.net/2067/47818-
dc.description.abstractTo answer new scientific and ecological questions and monitor multiple 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 efficiently monitor 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. The imminent Sentinel-2 data could serve to open the road for the development of new concepts and methods in forestry and ecological research.it
dc.titleDiscrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 datait
dc.typearticle*
dc.identifier.doi10.1016/j.rse.2016.01.017it
dc.identifier.scopus2-s2.0-84960458844it
dc.identifier.urlhttps://dspace.unitus.it/handle/2067/2785it
dc.relation.journalREMOTE SENSING OF ENVIRONMENTit
dc.relation.firstpage163it
dc.relation.lastpage176it
dc.relation.volume176it
dc.type.miur262*
item.fulltextWith Fulltext-
item.openairetypearticle-
item.cerifentitytypePublications-
item.grantfulltextrestricted-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.journal.journalissn0034-4257-
crisitem.journal.anceE143409-
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