THE USE OF SATELLITE SAR IMAGERY TO CROP CLASSIFICATION IN UKRAINE WITHIN JECAM PROJECT

被引：32

作者：

Kussul, Nataliia ^{[1
]}

Skakun, Sergii ^{[1
]}

Shelestov, Andrii ^{[1
]}

Kussul, Olga

机构：

[1] NAS Ukraine, Space Res Inst, Kiev, Ukraine

来源：

2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2014年

关键词：

SAR; crop; classification; JECAM; Ukraine; EFFICIENCY ASSESSMENT; BIOPHYSICAL MODELS; EARTH OBSERVATION;

D O I：

10.1109/IGARSS.2014.6946721

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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).

引用

收藏

页码：1497 / 1500

页数：4

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