Tek ve Çok Hedefli Regresyon Analizi ile Ekinlerin Biyofiziksel Parametrelerinin Tahmini

Z. Meltem Sahin; Esra Erten; Nebiye Musaoglu; D. Ekin Canbay; Gulsen Kaya

doi:10.1109/SIU.2018.8404409

Tek ve Çok Hedefli Regresyon Analizi ile Ekinlerin Biyofiziksel Parametrelerinin Tahmini

Translated title of the contribution: Using single-and multi-target regression to estimate biophysical parameters of crops

Z. Meltem Sahin, Esra Erten, Nebiye Musaoglu, D. Ekin Canbay, Gulsen Kaya

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Estimation of biophysical parameters based on regression models is of interest for the remote sensing community since it is one of the key elements for agricultural purposes. Numerically, this problem is solved separately for each biophysical parameter such as Leaf Area Index-LAI, soil moisture, crop height and etc. However, this approach ignores tight relationship among the biophysical parameters, which is essential for driving estimation performance with a limited number of in-situ measurements. As an alternative strategy, a multi-target regression, which also learns the relationship among biophysical parameters in regression model, is considered. In order to see how multitarget regression models capture plausible physical relationship between crop's biophysical parameters and polarimetric features, RadarSAT-2 images acquired over agriculture fields in the context of AgriSAR 2009 campaign were used.

Translated title of the contribution	Using single-and multi-target regression to estimate biophysical parameters of crops
Original language	Turkish
Title of host publication	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-4
Number of pages	4
ISBN (Electronic)	9781538615010
DOIs	https://doi.org/10.1109/SIU.2018.8404409
Publication status	Published - 5 Jul 2018
Event	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 - Izmir, Turkey Duration: 2 May 2018 → 5 May 2018

Publication series

Name	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

Conference

Conference	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Country/Territory	Turkey
City	Izmir
Period	2/05/18 → 5/05/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/SIU.2018.8404409

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Sahin, Z. M., Erten, E., Musaoglu, N., Canbay, D. E., & Kaya, G. (2018). Tek ve Çok Hedefli Regresyon Analizi ile Ekinlerin Biyofiziksel Parametrelerinin Tahmini. In 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 (pp. 1-4). (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2018.8404409

Sahin, Z. Meltem ; Erten, Esra ; Musaoglu, Nebiye et al. / Tek ve Çok Hedefli Regresyon Analizi ile Ekinlerin Biyofiziksel Parametrelerinin Tahmini. 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-4 (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018).

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title = "Tek ve {\c C}ok Hedefli Regresyon Analizi ile Ekinlerin Biyofiziksel Parametrelerinin Tahmini",

abstract = "Estimation of biophysical parameters based on regression models is of interest for the remote sensing community since it is one of the key elements for agricultural purposes. Numerically, this problem is solved separately for each biophysical parameter such as Leaf Area Index-LAI, soil moisture, crop height and etc. However, this approach ignores tight relationship among the biophysical parameters, which is essential for driving estimation performance with a limited number of in-situ measurements. As an alternative strategy, a multi-target regression, which also learns the relationship among biophysical parameters in regression model, is considered. In order to see how multitarget regression models capture plausible physical relationship between crop's biophysical parameters and polarimetric features, RadarSAT-2 images acquired over agriculture fields in the context of AgriSAR 2009 campaign were used.",

keywords = "Biophysical parameter estimation, Multi-output SVM, Polarimetry, Precision agriculture, RadarSAT-2, SAR",

author = "Sahin, {Z. Meltem} and Esra Erten and Nebiye Musaoglu and Canbay, {D. Ekin} and Gulsen Kaya",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 ; Conference date: 02-05-2018 Through 05-05-2018",

year = "2018",

month = jul,

day = "5",

doi = "10.1109/SIU.2018.8404409",

language = "T{\"u}rk{\c c}e",

series = "26th IEEE Signal Processing and Communications Applications Conference, SIU 2018",

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Sahin, ZM, Erten, E , Musaoglu, N, Canbay, DE & Kaya, G 2018, Tek ve Çok Hedefli Regresyon Analizi ile Ekinlerin Biyofiziksel Parametrelerinin Tahmini. in 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, Institute of Electrical and Electronics Engineers Inc., pp. 1-4, 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, Izmir, Turkey, 2/05/18. https://doi.org/10.1109/SIU.2018.8404409

Tek ve Çok Hedefli Regresyon Analizi ile Ekinlerin Biyofiziksel Parametrelerinin Tahmini. / Sahin, Z. Meltem; Erten, Esra ; Musaoglu, Nebiye et al.
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-4 (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Tek ve Çok Hedefli Regresyon Analizi ile Ekinlerin Biyofiziksel Parametrelerinin Tahmini

AU - Sahin, Z. Meltem

AU - Erten, Esra

AU - Musaoglu, Nebiye

AU - Canbay, D. Ekin

AU - Kaya, Gulsen

PY - 2018/7/5

Y1 - 2018/7/5

N2 - Estimation of biophysical parameters based on regression models is of interest for the remote sensing community since it is one of the key elements for agricultural purposes. Numerically, this problem is solved separately for each biophysical parameter such as Leaf Area Index-LAI, soil moisture, crop height and etc. However, this approach ignores tight relationship among the biophysical parameters, which is essential for driving estimation performance with a limited number of in-situ measurements. As an alternative strategy, a multi-target regression, which also learns the relationship among biophysical parameters in regression model, is considered. In order to see how multitarget regression models capture plausible physical relationship between crop's biophysical parameters and polarimetric features, RadarSAT-2 images acquired over agriculture fields in the context of AgriSAR 2009 campaign were used.

AB - Estimation of biophysical parameters based on regression models is of interest for the remote sensing community since it is one of the key elements for agricultural purposes. Numerically, this problem is solved separately for each biophysical parameter such as Leaf Area Index-LAI, soil moisture, crop height and etc. However, this approach ignores tight relationship among the biophysical parameters, which is essential for driving estimation performance with a limited number of in-situ measurements. As an alternative strategy, a multi-target regression, which also learns the relationship among biophysical parameters in regression model, is considered. In order to see how multitarget regression models capture plausible physical relationship between crop's biophysical parameters and polarimetric features, RadarSAT-2 images acquired over agriculture fields in the context of AgriSAR 2009 campaign were used.

KW - Biophysical parameter estimation

KW - Multi-output SVM

KW - Polarimetry

KW - Precision agriculture

KW - RadarSAT-2

KW - SAR

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M3 - Konferans katkısı

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BT - 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

Y2 - 2 May 2018 through 5 May 2018

ER -

Sahin ZM, Erten E , Musaoglu N, Canbay DE, Kaya G. Tek ve Çok Hedefli Regresyon Analizi ile Ekinlerin Biyofiziksel Parametrelerinin Tahmini. In 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-4. (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018). doi: 10.1109/SIU.2018.8404409

Tek ve Çok Hedefli Regresyon Analizi ile Ekinlerin Biyofiziksel Parametrelerinin Tahmini

Abstract

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Bibliographical note

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