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

• Type: Article in International Conference Proceedings Book
• Date: 2012

Authors

Ana C Teodoro (Author) FCUP; Dario Ferreira (Author) Other; Neftali Sillero (Author) FCUP

Conference proceedings International

Title: 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

Indexing

ISI Proceedings

ISI Web of Knowledge - 5 Citations

Scopus - 6 Citations

Scientific classification

FOS: Engineering and technology > Environmental engineering

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12