A GEOBIA methodology for fragmented agricultural landscapes

García Pedrero, Ángel Mario and Gonzalo Martín, Consuelo and Fonseca Luengo, David and Lillo Saavedra, Mario (2015). A GEOBIA methodology for fragmented agricultural landscapes. "Remote sensing", v. 7 (n. 1); pp. 767-787. ISSN 2072-4292. https://doi.org/10.3390/rs70100767.


Title: A GEOBIA methodology for fragmented agricultural landscapes
  • García Pedrero, Ángel Mario
  • Gonzalo Martín, Consuelo
  • Fonseca Luengo, David
  • Lillo Saavedra, Mario
Item Type: Article
Título de Revista/Publicación: Remote sensing
Date: 2015
ISSN: 2072-4292
Volume: 7
Freetext Keywords: Remote sensing; Image analysis; GEOBIA; Superpixels
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Arquitectura y Tecnología de Sistemas Informáticos
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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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.

More information

Item ID: 40657
DC Identifier: https://oa.upm.es/40657/
OAI Identifier: oai:oa.upm.es:40657
DOI: 10.3390/rs70100767
Official URL: http://www.mdpi.com/2072-4292/7/1/767
Deposited by: Memoria Investigacion
Deposited on: 26 Oct 2016 15:11
Last Modified: 26 Oct 2016 15:11
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