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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.)

Statistical Evaluation and Analysis of Road Extraction Methodologies Using a Unique Dataset from Remote Sensing

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Autor(es):
Pina Cardim, Guilherme [1, 2] ; da Silva, Erivaldo Antonio [1] ; Dias, Mauricio Araujo [1] ; Bravo, Ignacio [2] ; Gardel, Alfredo [2]
Número total de Autores: 5
Afiliação do(s) autor(es):
[1] Sao Paulo State Univ UNESP, Sch Sci & Technol, BR-19060900 Presidente Prudente - Brazil
[2] Univ Alcala UAH, Politech Sch, Alcala De Henares 28805 - Spain
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: REMOTE SENSING; v. 10, n. 4 APR 2018.
Citações Web of Science: 3
Resumo

In the scientific literature, multiple studies address the application of road extraction methodologies to a particular cartographic dataset. However, it is difficult for any study to perform a more reliable comparison among road extraction methodologies when their results come from different cartographic datasets. Therefore, aiming to enable a more reliable comparison among different road extraction methodologies from the scientific literature, this study proposed a statistical evaluation and analysis of road extraction methodologies using a common image dataset. To achieve this goal, we setup a dataset containing remote sensing images of three different road types, highways, cities network and rural paths, and a group of images from the ISPRS (International Society for Photogrammetry and Remote Sensing) dataset. Furthermore, three road extraction methodologies were selected from the literature, in accordance with their availability, to be processed and evaluated using well-known statistical metrics. The achieved results are encouraging and indicate that the proposed statistical evaluation and analysis can allow researchers to evaluate and compare road extraction methodologies using this common dataset extracting similar characteristics to obtain a more reliable comparison among them. (AU)

Processo FAPESP: 16/04553-2 - Proposição de plataforma co-design para processamento de imagens de sensoriamento remoto
Beneficiário:Guilherme Pina Cardim
Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Doutorado
Processo FAPESP: 14/24392-8 - Proposição de plataforma co-design para processamento de imagens de sensoriamento remoto
Beneficiário:Guilherme Pina Cardim
Modalidade de apoio: Bolsas no Brasil - Doutorado