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The accuracy of supervised image classification is highly dependent upon several factors such as the design of training set (sample selection, composition, purity and size), resolution of input imager...
In this study, a land cover classification method based on multi-class Support Vector Machines (SVM) is presented to predict the types of land cover in Miyun area. The obtained backscattered full-wave...
This paper reports on research analysing the potential of Support Vector Machines (SVMs) for mapping vegetation from high spatial resolution Ikonos imagery. The work investigated the utility of SVMs f...
Due to its various negative consequences impervious surface is increasingly recognized as a key issue in assessing the sustainability of land use - particularly in urban environments. In Germany, a re...
Remote sensing techniques have been commonly used to map land cover and land use types. For many applications, users may only be interested in a specific land class in an image such as extracting urba...
A combination of the two remote sensing systems, imaging spectrometry (IS) and Light Detection And Ranging (LiDAR), is well suited to map fuel types, especially within the complex wildland urban inte...

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