Aplin, Paul and Atkinson, Peter M. and Curran, Paul J. (1999) Fine spatial resolution satelite sensor imagery for land cover mapping in the United Kingdom. Remote Sensing of Environment, 68 (3). pp. 206-216. ISSN 0034-4257
Full text not available from this repository.Abstract
This article presents a set of techniques developed to classify land cover on a per-parcel (herein termed per-field) basis by integrating fine spatial resolution simulated satellite sensor imagery with digital vector data. Classification, based on the spectral and spatial properties of the imagery, was carried out on a per-pixel basis. The resulting classified images were then integrated with vector data to classify on a per-field basis. Four tools were adopted or developed to increase the accuracy and utility of the per-field classification and a fifth was proposed. The spectral variability within agricultural fields resulted in misclassification within the per-pixel classification, and this was overcome using a per-field classification. Mixed land cover in urban areas also resulted in misclassification. A low pass smoothing filter and a “texture” filter applied to the per-pixel classified image increased the classification accuracy of this land cover prior to per-field classification. The flexibility of the integration process enabled the exploitation of spectral and spatial variation between pixels within individual parcels to produce new classes during per-field classification and to identify fields with a high likelihood of misclassification.