Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/34159

Title: CARTOGRAFIA DAS ESPÉCIES FLORESTAIS NA REGIÃO DO ALENTEJO UTILIZANDO IMAGENS DE ALTA RESOLUÇÃO ESPACIAL
Authors: Coelho, Ana Margarida
Sousa, Adélia
Gonçalves, Ana Cristina
Keywords: Multiresolution Segmentation
WorldView-3
Forest Species
Object-Oriented Classification
Issue Date: Sep-2022
Citation: Coelho, A. M., Sousa, A. M. O., Gonçalves, A. C., (2022). CARTOGRAFIA DAS ESPÉCIES FLORESTAIS NA REGIÃO DO ALENTEJO UTILIZANDO IMAGENS DE ALTA RESOLUÇÃO ESPACIAL. Livro de atas do X Congresso da APDEA & IV Encontro Lusófono em Economia, Sociologia, Ambiente e Desenvolvimento Rural, 14-16 setembro de 2022, pp.556-564.
Abstract: In Portugal forest occupies 35,8% of the national territory, 23% corresponding to conifers and 64% to broadleaved species. According to the national forest inventory of 2015, the main forest species are eucaliptus (Eucalyptus spp.) representing 26%, cork oak (Quercus suber) and maritime pine (Pinus pinaster) with 22% of the forest area. The soil land use/cover monitoring has a pivotal role in the natural resource’s management, in the climatic changes study, in the territory and forest planning and in the sustainable development. Currently, the wide range of data sets derived from remote sensing allows the cartography of forest land use at different spatial scales, contributing to the evaluation of the protection and conservation of the forest areas, and the quantification of biomass and carbon. This study objective is the delimitation and identification of the crowns per forest species in Alentejo region, based on satellite images of high spatial resolution 0,50 m (Worldview-3), using the multiresolution segmentation and object-oriented classification. In the multiresolution segmentation several set of input variables were tested (original bands, bands, vegetation indices, principal components), with different threshold parameters values (colour, form and dimension) in order to isolate the objects in the image. After, object-oriented classification was used to isolate the tree crowns from the other classes.
URI: http://hdl.handle.net/10174/34159
Type: article
Appears in Collections:MED - Artigos em Livros de Actas/Proceedings
ERU - Artigos em Livros de Actas/Proceedings
ICT - Artigos em Livros de Actas/Proceedings

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