Title :
The use of satellite SAR imagery to crop classification in Ukraine within JECAM project
Author :
Kussul, Nataliia ; Skakun, Sergii ; Shelestov, Andrii ; Kussul, Olga
Author_Institution :
Space Res. Inst., SSA Ukraine, Kiev, Ukraine
Abstract :
In this paper, we focus on the application of satellite synthetic-aperture radar (SAR) images for discriminating summer crops in Ukraine within the JECAM project. Both optical (EO-1/ALI) and SAR (RADARSAT-2) images are used in order to assess impact adding SAR images for classification purposes. Three different classifiers, in particular neural networks, support vector machine and decision trees, are applied with neural networks giving the best overall accuracy. It is found that major impact of using SAR images is for sunflower and sugar beet classes while there was no gain for other crops (maize and soybeans).
Keywords :
geophysical image processing; image classification; neural nets; radar imaging; remote sensing by radar; support vector machines; synthetic aperture radar; vegetation mapping; ALI images; EO-1 images; JECAM project; RADARSAT-2 image; SAR images; Ukraine; crop classification; decision trees; maize; optical images; particular neural networks; satellite synthetic-aperture radar images; soybeans; sugar beet classes; sunflower; support vector machine; Agriculture; Earth; Monitoring; Optical imaging; Remote sensing; Satellites; Synthetic aperture radar; JECAM; SAR; Ukraine; classification; crop;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6946721
