Remote Sens. 2012, 4(9), 2530-2553; doi:10.3390/rs4092530
Article

Land Cover and Land Use Classification with TWOPAC: towards Automated Processing for Pixel- and Object-Based Image Classification

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Received: 2 July 2012; in revised form: 23 August 2012 / Accepted: 28 August 2012 / Published: 7 September 2012
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: We present a novel and innovative automated processing environment for the derivation of land cover (LC) and land use (LU) information. This processing framework named TWOPAC (TWinned Object and Pixel based Automated classification Chain) enables the standardized, independent, user-friendly, and comparable derivation of LC and LU information, with minimized manual classification labor. TWOPAC allows classification of multi-spectral and multi-temporal remote sensing imagery from different sensor types. TWOPAC enables not only pixel-based classification, but also allows classification based on object-based characteristics. Classification is based on a Decision Tree approach (DT) for which the well-known C5.0 code has been implemented, which builds decision trees based on the concept of information entropy. TWOPAC enables automatic generation of the decision tree classifier based on a C5.0-retrieved ascii-file, as well as fully automatic validation of the classification output via sample based accuracy assessment.Envisaging the automated generation of standardized land cover products, as well as area-wide classification of large amounts of data in preferably a short processing time, standardized interfaces for process control, Web Processing Services (WPS), as introduced by the Open Geospatial Consortium (OGC), are utilized. TWOPAC’s functionality to process geospatial raster or vector data via web resources (server, network) enables TWOPAC’s usability independent of any commercial client or desktop software and allows for large scale data processing on servers. Furthermore, the components of TWOPAC were built-up using open source code components and are implemented as a plug-in for Quantum GIS software for easy handling of the classification process from the user’s perspective.
Keywords: TWOPAC; land cover and land use; automated processing; supervised; decision tree; web processing service; classification; validation
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MDPI and ACS Style

Huth, J.; Kuenzer, C.; Wehrmann, T.; Gebhardt, S.; Tuan, V.Q.; Dech, S. Land Cover and Land Use Classification with TWOPAC: towards Automated Processing for Pixel- and Object-Based Image Classification. Remote Sens. 2012, 4, 2530-2553.

AMA Style

Huth J, Kuenzer C, Wehrmann T, Gebhardt S, Tuan VQ, Dech S. Land Cover and Land Use Classification with TWOPAC: towards Automated Processing for Pixel- and Object-Based Image Classification. Remote Sensing. 2012; 4(9):2530-2553.

Chicago/Turabian Style

Huth, Juliane; Kuenzer, Claudia; Wehrmann, Thilo; Gebhardt, Steffen; Tuan, Vo Quoc; Dech, Stefan. 2012. "Land Cover and Land Use Classification with TWOPAC: towards Automated Processing for Pixel- and Object-Based Image Classification." Remote Sens. 4, no. 9: 2530-2553.

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