A GEOBIA Methodology for Fragmented Agricultural Landscapes

Authors:
Angel Garcia, Consuelo Gonzalo, David Fonseca-Luengo, Mario Lillo-Saavedra

Abstract:

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.



Published in: Remote Sensing
Year:

2015


Citation

Angel Garcia, Consuelo Gonzalo, David Fonseca-Luengo, Mario Lillo-Saavedra. (2015) "A GEOBIA Methodology for Fragmented Agricultural Landscapes" In Remote Sensing. DOI: 10.3390/RS70100767.