Automatic classification of high resolution land cover using a new data weighting procedure: The combination of k-means clustering algorithm and central tendency measures (KMC-CTM)

Abstract

Information on a well-scale urban land cover is important for a number of urban planning practices involving tree shade mapping, green space analysis, urban hydrologic modeling and urban land use mapping. In this study, an urban land cover dataset received from the database of UCI (University of California at Irvine) machine learning was used as the urban… (More)
DOI: 10.1016/j.asoc.2015.06.025

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Cite this paper

@article{Durduran2015AutomaticCO, title={Automatic classification of high resolution land cover using a new data weighting procedure: The combination of k-means clustering algorithm and central tendency measures (KMC-CTM)}, author={S{\"u}leyman Savas Durduran}, journal={Appl. Soft Comput.}, year={2015}, volume={35}, pages={136-150} }