A GEOBIA Methodology for Fragmented Agricultural Landscapes

Remote Sensing

Angel Garcia-Pedrero¹  Consuelo Gonzalo-Martin¹  David Fonseca-Luengo³  Mario Lillo-Saavedra³  Ioannis Gitas² 

[1] Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Campus de Montegancedo, Pozuelo de Alarcón 28233, Spain; E-Mail:;Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Campus de Montegancedo, Pozuelo de Alarcón 28233, Spain; E-Mail;Facultad de Ingeniería Agrícola, Universidad de Concepción, Av. Vicente Méndez 595, Casilla 537, Chillán, Octava Región, Chile; E-Mails:

关键词: remote sensing;    image analysis;    GEOBIA;    superpixels;   

DOI  :  10.3390/rs70100767

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.