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.

Description

Title: A GEOBIA methodology for fragmented agricultural landscapes
Author/s:
  • 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
Subjects:
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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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.

More information

Item ID: 40657
DC Identifier: http://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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