Remote Sensing Applications and Decision Support

Comparison of performance of object-based image analysis techniques available in open source software (Spring and Orfeo Toolbox/Monteverdi) considering very high spatial resolution data

[+] Author Affiliations
Ana C. Teodoro

Earth Sciences Institute (ICT), FCUP-University of Porto, Rua Campo Alegre, 4169-007 Porto, Portugal

University of Porto, Department of Geosciences, Environment and Land Planning, Faculty of Sciences, Porto, Portugal

Ricardo Araujo

University of Porto, Department of Geosciences, Environment and Land Planning, Faculty of Sciences, Porto, Portugal

J. Appl. Remote Sens. 10(1), 016011 (Feb 15, 2016). doi:10.1117/1.JRS.10.016011
History: Received June 1, 2015; Accepted January 19, 2016
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Abstract.  The use of unmanned aerial vehicles (UAVs) for remote sensing applications is becoming more frequent. However, this type of information can result in several software problems related to the huge amount of data available. Object-based image analysis (OBIA) has proven to be superior to pixel-based analysis for very high-resolution images. The main objective of this work was to explore the potentialities of the OBIA methods available in two different open source software applications, Spring and OTB/Monteverdi, in order to generate an urban land cover map. An orthomosaic derived from UAVs was considered, 10 different regions of interest were selected, and two different approaches were followed. The first one (Spring) uses the region growing segmentation algorithm followed by the Bhattacharya classifier. The second approach (OTB/Monteverdi) uses the mean shift segmentation algorithm followed by the support vector machine (SVM) classifier. Two strategies were followed: four classes were considered using Spring and thereafter seven classes were considered for OTB/Monteverdi. The SVM classifier produces slightly better results and presents a shorter processing time. However, the poor spectral resolution of the data (only RGB bands) is an important factor that limits the performance of the classifiers applied.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Ana C. Teodoro and Ricardo Araujo
"Comparison of performance of object-based image analysis techniques available in open source software (Spring and Orfeo Toolbox/Monteverdi) considering very high spatial resolution data", J. Appl. Remote Sens. 10(1), 016011 (Feb 15, 2016). ; http://dx.doi.org/10.1117/1.JRS.10.016011


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