Sensors 2009, 9(1), 22-45; doi:10.3390/s90100022
Full Hierarchic Versus Non-Hierarchic Classification Approaches for Mapping Sealed Surfaces at the Rural-Urban Fringe Using High-Resolution Satellite Data
Vrije Universiteit Brussel, Cartography and GIS Research Unit, Department of Geography, Brussels, Belgium
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Received: 4 December 2008 / Revised: 17 December 2008 / Accepted: 23 December 2008 / Published: 5 January 2009
(This article belongs to the Special Issue Remote Sensing of Land Surface Properties, Patterns and Processes)
Abstract
Since 2008 more than half of the world population is living in cities and urban sprawl is continuing. Because of these developments, the mapping and monitoring of urban environments and their surroundings is becoming increasingly important. In this study two object-oriented approaches for high-resolution mapping of sealed surfaces are compared: a standard non-hierarchic approach and a full hierarchic approach using both multi-layer perceptrons and decision trees as learning algorithms. Both methods outperform the standard nearest neighbour classifier, which is used as a benchmark scenario. For the multi-layer perceptron approach, applying a hierarchic classification strategy substantially increases the accuracy of the classification. For the decision tree approach a one-against-all hierarchic classification strategy does not lead to an improvement of classification accuracy compared to the standard all-against-all approach. Best results are obtained with the hierarchic multi-layer perceptron classification strategy, producing a kappa value of 0.77. A simple shadow reclassification procedure based on characteristics of neighbouring objects further increases the kappa value to 0.84.Keywords:
Urban mapping; sealed surfaces; hierarchic classification; multiple layer perceptron; decision trees
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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MDPI and ACS Style
De Roeck, T.; Van de Voorde, T.; Canters, F. Full Hierarchic Versus Non-Hierarchic Classification Approaches for Mapping Sealed Surfaces at the Rural-Urban Fringe Using High-Resolution Satellite Data. Sensors 2009, 9, 22-45.