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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Object-oriented and pixel-based classification approaches to classify tropical successional stages using airborne high-spatial resolution images

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Autor(es):
Piazza, Gustavo Antonio [1] ; Vibrans, Alexander Christian [1] ; Liesenberg, Veraldo [2] ; Refosco, Julio Cesar [1]
Número total de Autores: 4
Afiliação do(s) autor(es):
[1] Reg Univ Blumenau FURB, Dept Forest Engn, BR-89030000 Blumenau, SC - Brazil
[2] Santa Catarina State Univ UDESC, Dept Forest Engn, BR-88520000 Lages, SC - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: GIScience & Remote Sensing; v. 53, n. 2, p. 206-226, MAR 3 2016.
Citações Web of Science: 15
Resumo

Airborne high-spatial resolution images were evaluated for mapping purposes in a complex Atlantic rainforest environment in southern Brazil. Two study sites, covered predominantly by secondary evergreen rainforest, were surveyed by airborne multispectral high-resolution imagery. These aerophotogrammetric images were acquired at four spectral bands (visible to near-infrared) with spatial resolution of 0.39m. We evaluated different data input scenarios to suit the object-oriented classification approach. In addition to the four spectral bands, auxiliary products such as band ratios and digital elevation models were considered. Comparisons with traditional pixel-based classifiers were also performed. The results showed that the object-based classification approach yielded a better overall accuracy, ranging from 89% to 91%, than the pixel-based classifications, which ranged from 62% to 63%. The individual classification accuracy of forest-related classes, such as young successional forest stages, benefits the object-based approach. These classes have been reported in the literature as the most difficult to map in tropical environments. The results confirm the potential of object-based classification for mapping procedures and discrimination of successional forest stages and other related land use and land cover classes in complex Atlantic rainforest environments. The methodology is suggested for further SAAPI acquisitions in order to monitor such endangered environment as well as to support National Land and Environmental Management Protocols. (AU)

Processo FAPESP: 13/05081-9 - Caracterização de estádios sucessionais em distintos ambientes de floresta tropical sob a recente perspectiva REDD+: um experimento com múltiplos dados de sensoriamento remoto
Beneficiário:Veraldo Liesenberg
Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado