CO-POLAR SAR data classification as a tool for real time paddy-rice monitoring

Caglar Kucuk; Gulsen Taskin Kaya; Esra Erten

doi:10.1109/IGARSS.2015.7326737

CO-POLAR SAR data classification as a tool for real time paddy-rice monitoring

Caglar Kucuk, Gulsen Taskin Kaya, Esra Erten

Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

8 Atıf (Scopus)

Özet

The crop phenology retrieval on precision agriculture has been an important research area with the increasing demand on crops. Remotely sensed Synthetic Aperture Radar (SAR) data provides a simple possibility for automatic monitoring of agricultural fields due to the its inherit all-weather monitoring capability. Most of the studies rely on morphology based modelling of the electromagnetic backscattering which requires Monte Carlo simulations. In this paper, instead of modelling the backscattering of the signals for monitoring the crop fields, a classification scheme was implemented on the data acquired by TerraSAR-X by using the features extracted from backscattering coefficients with the machine learning algorithms which are Support Vector Machines, k-Nearest Neighbor and Regression Tree.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	4141-4144
Sayfa sayısı	4
ISBN (Elektronik)	9781479979295
DOI'lar	https://doi.org/10.1109/IGARSS.2015.7326737
Yayın durumu	Yayınlandı - 10 Kas 2015
Etkinlik	IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Milan, Italy Süre: 26 Tem 2015 → 31 Tem 2015

Yayın serisi

Adı	International Geoscience and Remote Sensing Symposium (IGARSS)
Hacim	2015-November

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???event.eventtypes.event.conference???	IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
Ülke/Bölge	Italy
Şehir	Milan
Periyot	26/07/15 → 31/07/15

Bibliyografik not

Publisher Copyright:
© 2015 IEEE.

BM SKH

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Belgeye Erişim

10.1109/IGARSS.2015.7326737

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Kucuk, C., Kaya, G. T., & Erten, E. (2015). CO-POLAR SAR data classification as a tool for real time paddy-rice monitoring. In 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings (pp. 4141-4144). Makale 7326737 (International Geoscience and Remote Sensing Symposium (IGARSS); Hac. 2015-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2015.7326737

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title = "CO-POLAR SAR data classification as a tool for real time paddy-rice monitoring",

abstract = "The crop phenology retrieval on precision agriculture has been an important research area with the increasing demand on crops. Remotely sensed Synthetic Aperture Radar (SAR) data provides a simple possibility for automatic monitoring of agricultural fields due to the its inherit all-weather monitoring capability. Most of the studies rely on morphology based modelling of the electromagnetic backscattering which requires Monte Carlo simulations. In this paper, instead of modelling the backscattering of the signals for monitoring the crop fields, a classification scheme was implemented on the data acquired by TerraSAR-X by using the features extracted from backscattering coefficients with the machine learning algorithms which are Support Vector Machines, k-Nearest Neighbor and Regression Tree.",

keywords = "classification, machine learning, Precision agriculture, synthetic aperture radar (SAR)",

author = "Caglar Kucuk and Kaya, {Gulsen Taskin} and Esra Erten",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 ; Conference date: 26-07-2015 Through 31-07-2015",

year = "2015",

month = nov,

day = "10",

doi = "10.1109/IGARSS.2015.7326737",

language = "English",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

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booktitle = "2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings",

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}

Kucuk, C, Kaya, GT & Erten, E 2015, CO-POLAR SAR data classification as a tool for real time paddy-rice monitoring. in 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings., 7326737, International Geoscience and Remote Sensing Symposium (IGARSS), hac. 2015-November, Institute of Electrical and Electronics Engineers Inc., pp. 4141-4144, IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015, Milan, Italy, 26/07/15. https://doi.org/10.1109/IGARSS.2015.7326737

CO-POLAR SAR data classification as a tool for real time paddy-rice monitoring. / Kucuk, Caglar; Kaya, Gulsen Taskin ; Erten, Esra.
2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. p. 4141-4144 7326737 (International Geoscience and Remote Sensing Symposium (IGARSS); Hac. 2015-November).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - CO-POLAR SAR data classification as a tool for real time paddy-rice monitoring

AU - Kucuk, Caglar

AU - Kaya, Gulsen Taskin

AU - Erten, Esra

PY - 2015/11/10

Y1 - 2015/11/10

N2 - The crop phenology retrieval on precision agriculture has been an important research area with the increasing demand on crops. Remotely sensed Synthetic Aperture Radar (SAR) data provides a simple possibility for automatic monitoring of agricultural fields due to the its inherit all-weather monitoring capability. Most of the studies rely on morphology based modelling of the electromagnetic backscattering which requires Monte Carlo simulations. In this paper, instead of modelling the backscattering of the signals for monitoring the crop fields, a classification scheme was implemented on the data acquired by TerraSAR-X by using the features extracted from backscattering coefficients with the machine learning algorithms which are Support Vector Machines, k-Nearest Neighbor and Regression Tree.

AB - The crop phenology retrieval on precision agriculture has been an important research area with the increasing demand on crops. Remotely sensed Synthetic Aperture Radar (SAR) data provides a simple possibility for automatic monitoring of agricultural fields due to the its inherit all-weather monitoring capability. Most of the studies rely on morphology based modelling of the electromagnetic backscattering which requires Monte Carlo simulations. In this paper, instead of modelling the backscattering of the signals for monitoring the crop fields, a classification scheme was implemented on the data acquired by TerraSAR-X by using the features extracted from backscattering coefficients with the machine learning algorithms which are Support Vector Machines, k-Nearest Neighbor and Regression Tree.

KW - classification

KW - machine learning

KW - Precision agriculture

KW - synthetic aperture radar (SAR)

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U2 - 10.1109/IGARSS.2015.7326737

DO - 10.1109/IGARSS.2015.7326737

M3 - Conference contribution

AN - SCOPUS:84962481010

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 4141

EP - 4144

BT - 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015

Y2 - 26 July 2015 through 31 July 2015

ER -

Kucuk C, Kaya GT , Erten E. CO-POLAR SAR data classification as a tool for real time paddy-rice monitoring. In 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2015. p. 4141-4144. 7326737. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS.2015.7326737

CO-POLAR SAR data classification as a tool for real time paddy-rice monitoring

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

BM SKH

Belgeye Erişim

Diğer Dosyalar ve Linkler

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