Performance of commercial and open source remote sensing/image processing software for land cover/use purposes

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2012

Autores

Ana C Teodoro (Autor) FCUP; Dario Ferreira (Autor) Outra; Neftali Sillero (Autor) FCUP

Ata de Conferência Internacional

Título: EARTH RESOURCES AND ENVIRONMENTAL REMOTE SENSING/GIS APPLICATIONS III

Conference on Earth Resources and Environmental Remote Sensing/GIS Applications III

Edinburgh, SCOTLAND, SEP 24-26, 2012

Indexação

ISI Proceedings

ISI Web of Knowledge - 5 Citações

Scopus - 6 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia do ambiente

Outras Informações

ID Authenticus: P-002-E8X

DOI: 10.1117/12.974577

Abstract (EN): We aim to compare the potentialities of four remote sensing/image processing software: PCI Geomatica V8.2, ENVI 4.7, SPRING 5.1.8, and ORFEO toolbox integrated in Monteverdi 1.11. We listed and assessed the performance of several classification algorithms. PCI Geomatica and ENVI are commercial/proprietary software and SPRING and ORFEO are open source software. We listed the main classification algorithms available in these four software, and divided them by the different types/approaches of classification (e. g., pixel-based, object-oriented, and data mining algorithms). We classified using these algorithms two images covering the same area (Porto-Vila Nova de Gaia, Northern Portugal): one Landsat TM image from October 2011 and one IKONOS image from September 2005. We compared time of performance and classification results using the confusion matrix (overall accuracy) and Kappa statistics. The algorithms tested presented different classification results according to the software used. In Landsat image, differences are greater than IKONOS image. This work could be very important for other researchers as it provides a qualitative and quantitative analysis of different image processing algorithms available in commercial and open source software.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12