Title: Parcel based classification for agricultural mapping and monitoring using multi-temporal satellite image sequence
Authors: KUSSUL NATALIALEMOINE GUIDOGALLEGO PINILLA FRANCISCOSKAKUN SERGIILAVRENIUK MYKOLA
Publisher: IEEE
Publication Year: 2015
JRC N°: JRC97292
ISBN: 978-1-4799-7929-5
ISSN: 2153-7003
URI: http://ieeexplore.ieee.org/document/7325725/
http://publications.jrc.ec.europa.eu/repository/handle/JRC97292
DOI: 10.1109/IGARSS.2015.7325725
Type: Articles in periodicals and books
Abstract: In this paper, we propose a new approach to parcel-based classification of multi-temporal optical satellite imagery with missing data due to clouds and shadows based on vector and raster data fusion in different phase of classification methodology in Ukraine within the JECAM project. For obtaining pixel-based classification map, an ensemble of neural networks, in particular multilayer perceptron (MLPs), is used. The proposed approach is applied for regional scale crop classification using multi-temporal Landsat-8 images for the Kyivska oblast in Ukraine in 2013. The obtained results are also validated through comparison to official statistics
JRC Directorate:Sustainable Resources

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