@article {ThoonenHufkensBorreSpanhovepscheund2011,
	title = {Accuracy assessment of contextual classification results for vegetation mapping},
	journal = {International Journal of Applied Earth Observation and Geoinformation},
	volume = {15},
	year = {2012},
	pages = {7 - 15},
	abstract = {A new procedure for quantitatively assessing the geometric accuracy of thematic maps, obtained from classifying hyperspectral remote sensing data, is presented. More specifically, the methodology is aimed at the comparison between results from any of the currently popular contextual classification strategies. The proposed procedure characterises the shapes of all objects in a classified image by defining an appropriate reference and a new quality measure. The results from the proposed procedure are represented in an intuitive way, by means of an error matrix, analogous to the confusion matrix used in traditional thematic accuracy representation. A suitable application for the methodology is vegetation mapping, where lots of closely related and spatially connected land cover types are to be distinguished. Consequently, the procedure is tested on a heathland vegetation mapping problem, related to Natura 2000 habitat monitoring. Object-based mapping and Markov Random Field classification results are compared, showing that the selected Markov Random Fields approach is more suitable for the fine-scale problem at hand, which is confirmed by the proposed procedure.},
	keywords = {Accuracy assessment, Confusion matrix, Contextual classification, Natura 2000},
	issn = {0303-2434},
	doi = {10.1016/j.jag.2011.05.013},
	url = {http://www.sciencedirect.com/science/article/pii/S0303243411000766},
	author = {Guy Thoonen and Koen Hufkens and Jeroen Vanden Borre and Toon Spanhove and Paul Scheunders}
}
@article {Hufkens10,
	title = {Habitat reporting of a heathland site: Classification probabilities as additional information, a case study},
	journal = {Ecological Informatics},
	volume = {5},
	number = {4},
	year = {2010},
	pages = {248 - 255},
	abstract = {Heathlands are man-made habitats and their decline during the last century can be contributed to shifts in both agricultural and management practices as well as to hydrological and atmospheric changes. As a result, many heathland sites, including the Kalmthoutse Heide in Belgium, were included in the European Natura 2000 program, a network of protected areas across the European Union. To assure an accurate mapping of the Kalmthoutse Heide and other Natura 2000 sites in Belgium a classification framework for habitat status reporting with remote sensing data and in particular high resolution hyperspectral imagery was started. In this study we propose a simple and fast context based method for mapping heathland heterogeneity using the intermediate, otherwise redundant, classification probabilities as generated by a hard classification algorithm. Our study proved to be successful in using intermediate classification probabilities as a valuable source of ecological information. The delineated areas have been shown to be statistically sound and robust compared to a neutral model. The technique is not limited to a particular hard classification technique and can easily be adopted into current vegetation monitoring efforts. The resulting maps provided accessible maps which can support management of the protected site and enhance the accuracy of EU reportage as required by the habitat directive.},
	keywords = {Heterogeneity, Hyperspectral, Patch, remote sensing, Uncertainty, Vegetation},
	issn = {1574-9541},
	doi = {10.1016/j.ecoinf.2009.09.002},
	url = {http://www.sciencedirect.com/science/article/pii/S1574954109000740},
	author = {Koen Hufkens and Guy Thoonen and Jeroen Vanden Borre and Paul Scheunders and Reinhart Ceulemans}
}
@inproceedings {Thoonen10b,
	title = {Using patch metrics as validation for contextual classification of heathland vegetation.},
	booktitle = {Proceedings of GEOBIA 2010, the Geographic Object-Based Image Analysis Conference},
	volume = {XXXVIII-4/C7},
	year = {2010},
	month = {July},
	abstract = {This article presents a method to assess the accuracy of vegetation maps for which contextual information has been included in the classification process. It is well known that land use classification may benefit from combining spatial and spectral information. Consequently, many classification techniques incorporating spatial information have been implemented. To compare various contextual classification techniques, the shape of vegetation patches, in the spatially enhanced maps, are statistically linked to their counterparts in the spectral classification result, on which these spatial enhancements are applied. To this end, measures for the change in shape of patches are introduced. The shape of any patch is characterized by the edges between the patch and its neighbors. Therefore, patch shape can be represented by an edge map in which each pixel gets the value of the number of classes that are different from the class label of the central pixel in a four-adjacency neighborhood. Rather than defining a single metric for the edge map difference, an error matrix is used to depict not only how many edges have changed with respect to the reference, but also by how much they have changed. The method is tested on contextual classification results of heathland vegetation.},
	keywords = {Accuracy, Classification, Contextual, Hierarchical, Hyper spectral, Quality, Spatial, Vegetation},
	url = {http://www.isprs.org/proceedings/XXXVIII/4-C7/papers\%20proceedings/Thoonen_44_UsingPatchMetricsAsValidationForContextualClassificationOfHeathlandVegetation.pdf},
	author = {Guy Thoonen and Koen Hufkens and Jeroen Vanden Borre and Paul Scheunders}
}
@article {HufkensCeulemanspscheund2009,
	title = {Ecotones in vegetation ecology: methodology and definitions revisited},
	journal = {Ecological Research},
	volume = {24},
	year = {2009},
	pages = {977-986},
	author = {Koen Hufkens and Reinhart Ceulemans and Paul Scheunders}
}
@article {HufkenspscheundCeulemans2009,
	title = {Validation of the sigmoid wave curve fitting algorithm on a forest-tundra ecotone in the Northwest Territories, Canada},
	journal = {Ecological Informatics},
	volume = {4},
	year = {2009},
	pages = {1-7},
	author = {Koen Hufkens and Paul Scheunders and Reinhart Ceulemans}
}
@article {HufkensCeulemanspscheund2008,
	title = {Estimating the ecotone width in patchy ecotones using a sigmoid wave approach},
	journal = {Ecological Informatics},
	volume = {3},
	year = {2008},
	pages = {97-104},
	author = {Koen Hufkens and Reinhart Ceulemans and Paul Scheunders}
}
