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Descripción
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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. | |
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Internacional
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Si |
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JCR del ISI
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Si |
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Título de la revista
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Remote Sens-Basel |
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ISSN
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2072-4292 |
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Factor de impacto JCR
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3,18 |
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Información de impacto
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Datos JCR del año 2014 |
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Volumen
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7 |
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DOI
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10.3390/rs70100767 |
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Número de revista
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1 |
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Desde la página
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767 |
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Hasta la página
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787 |
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Mes
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SIN MES |
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Ranking
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