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
KUSSUL Natalia;
LEMOINE Guido;
GALLEGO PINILLA Francisco;
SKAKUN Sergii;
LAVRENIUK Mykola;
2017-12-04
IEEE
JRC97292
978-1-4799-7929-5,
2153-7003,
http://ieeexplore.ieee.org/document/7325725/,
https://publications.jrc.ec.europa.eu/repository/handle/JRC97292,
10.1109/IGARSS.2015.7325725,
| Name | Country | City | Type |
|---|
This document is only visible at the Commission level.
You are not authorized to publish or distribute it outside the European Commission.
This is a public document. You can share this publication.
Datasets
| ID | Title | Public URL |
|---|
Dataset collections
| ID | Acronym | Title | Public URL |
|---|
Scripts / source codes
| Description | Public URL |
|---|
Additional supporting files
| File name | Description | File type |
|---|