Object-Based Greenhouse Horticultural Crop Identification from Multi-Temporal Satellite Imagery: A Case Study in Almeria, Spain
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Aguilar Torres, Manuel Ángel![Autoridad Universidad de Almería Autoridad Universidad de Almería](/themes/Mirage2/images/autoridades/autoridad.png)
![Autoridad Universidad de Almería Autoridad Universidad de Almería](/themes/Mirage2/images/autoridades/autoridad.png)
![Autoridad Universidad de Almería Autoridad Universidad de Almería](/themes/Mirage2/images/autoridades/autoridad.png)
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2015-06-03Resumen
Greenhouse detection and mapping via remote sensing is a complex task, which has already been addressed in numerous studies. In this research, the innovative goal relies on the identification of greenhouse horticultural crops that were growing under plastic coverings on 30 September 2013. To this end, object-based image analysis (OBIA) and a decision tree classifier (DT) were applied to a set consisting of eight Landsat 8 OLI images collected from May to November 2013. Moreover, a single WorldView-2 satellite image acquired on 30 September 2013, was also used as a data source. In this approach, basic spectral information, textural features and several vegetation indices (VIs) derived from Landsat 8 and WorldView-2 multi-temporal satellite data were computed on previously segmented image objects in order to identify four of the most popular autumn crops cultivated under greenhouse in Almería, Spain (i.e., tomato, pepper, cucumber and aubergine). The best classification accuracy (81.3% o...
Palabra/s clave
Landsat 8
WorldView-2
time series
object-based classification
greenhouse crops
decision tree