%0 Journal Article
%T A GEOBIA Methodology for Fragmented Agricultural Landscapes
%A Angel Garcia-Pedrero
%A Consuelo Gonzalo-Martin
%A David Fonseca-Luengo
%A Mario Lillo-Saavedra
%J Remote Sensing
%P 767-787
%D 2015
%I MDPI AG
%R 10.3390/rs70100767
%X Very high resolution remotely sensed images are an important tool for monitoring fragmented agricultural landscapes, which allows farmers and policy makers to make better decisions regarding management practices. An object-based methodology is proposed for automatic generation of thematic maps of the available classes in the scene, which combines edge-based and superpixel processing for small agricultural parcels. The methodology employs superpixels instead of pixels as minimal processing units, and provides a link between them and meaningful objects (obtained by the edge-based method) in order to facilitate the analysis of parcels. Performance analysis on a scene dominated by agricultural small parcels indicates that the combination of both superpixel and edge-based methods achieves a classification accuracy slightly better than when those methods are performed separately and comparable to the accuracy of traditional object-based analysis, with automatic approach.
%K remote sensing
%K image analysis
%K GEOBIA
%K superpixels
%U http://www.mdpi.com/2072-4292/7/1/767