Title: Parcel based classification for agricultural mapping and monitoring using multi-temporal satellite image sequences
Authors: KUSSUL NATALIALEMOINE GUIDOGALLEGO PINILLA FRANCISCOSKAKUN SERGIILAVRENIUK MYKOLA
Citation: INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) p. 165-168
Publisher: INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS
Publication Year: 2015
JRC N°: JRC99016
URI: https://ieeexplore.ieee.org/document/7325725
https://publications.jrc.ec.europa.eu/repository/handle/JRC99016
DOI: 10.1109/IGARSS.2015.7325725
Type: Articles in periodicals and books
Abstract: In this paper, we propose a new approach to pixel and parcel-based classification of multi-temporal optical satellite imagery. We first restore missing data due to clouds and shadows based on vector and raster data fusion in different phases of classification methodology. Pixel-based classification maps are derived from an ensemble of neural networks, in particular multilayer perceptrons (MLPs).. The proposed approach is applied for regional scale crop classification using multi-temporal Landsat-8 images for the JECAM site in the Kyivska oblast of Ukraine in 2013. The obtained results on crop area estimates are also compared to official statistics.
JRC Directorate:Sustainable Resources

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