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

fYear

2014

fDate

13-18 July 2014

Firstpage

1497

Lastpage

1500

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International

Conference_Location

Quebec City, QC

Type

conf

DOI

10.1109/IGARSS.2014.6946721

Filename

6946721