Potential of multi-temporal Sentinel-1A Dual polarization SAR images for vegetable classification in Indonesia

Mengmeng Li; W. Bijker

Potential of multi-temporal Sentinel-1A Dual polarization SAR images for vegetable classification in Indonesia

Mengmeng Li, W. Bijker

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

7 Citations (Scopus)

20 Downloads (Pure)

Abstract

As part of the G4AW SMARTSeeds project, this study aims to investigate the potential of dense time series of Sentinel-1A dual polarization data for the classification of vegetables that are common in East Java, Indonesia. We first analyzed the temporal behavior of three main types of vegetables (i.e.chili, tomato and cucumber) in terms of backscatter (VH andVV) intensity, and of polarimetric features (i.e. entropy,al-pha and anisotropy) derived from polarization decomposition. We then applied a support vector machine with an intersection kernel to the time series data of vegetable samples collected infield. Our results showed that dense time series Sentinel-1Aimages are of high potential for vegetable classification. Be-sides using backscatter intensity, the polarimetric information can further improve the discrimination between three specific vegetable types.

Original language	English
Title of host publication	IGARSS 2018 : IEEE International Geoscience and Remote Sensing Symposium : Observing, Understanding and Forecasting the Dynamics of Our Planet
Publisher	IEEE
Pages	3828-3831
Number of pages	4
Edition	IEEE Catalog Number: CFP18IGA-ART
ISBN (Electronic)	978-1-5386-7150-4/18
ISBN (Print)	978-1-5386-7150-4/18
Publication status	Published - 2018
Event	38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018: Observing, Understanding and Forcasting the Dynamics of Our Planet - Feria Valencia Convention & Exhibition Center, Valencia, Spain Duration: 22 Jul 2018 → 27 Jul 2018 Conference number: 38 https://www.igarss2018.org/

Conference

Conference	38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Abbreviated title	2018
Country/Territory	Spain
City	Valencia
Period	22/07/18 → 27/07/18
Internet address	https://www.igarss2018.org/

UN SDGs

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

Cite this

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title = "Potential of multi-temporal Sentinel-1A Dual polarization SAR images for vegetable classification in Indonesia",

abstract = "As part of the G4AW SMARTSeeds project, this study aims to investigate the potential of dense time series of Sentinel-1A dual polarization data for the classification of vegetables that are common in East Java, Indonesia. We first analyzed the temporal behavior of three main types of vegetables (i.e.chili, tomato and cucumber) in terms of backscatter (VH andVV) intensity, and of polarimetric features (i.e. entropy,al-pha and anisotropy) derived from polarization decomposition. We then applied a support vector machine with an intersection kernel to the time series data of vegetable samples collected infield. Our results showed that dense time series Sentinel-1Aimages are of high potential for vegetable classification. Be-sides using backscatter intensity, the polarimetric information can further improve the discrimination between three specific vegetable types.",

author = "Mengmeng Li and W. Bijker",

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publisher = "IEEE",

address = "United States",

edition = "IEEE Catalog Number: CFP18IGA-ART",

note = "38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 : Observing, Understanding and Forcasting the Dynamics of Our Planet, 2018 ; Conference date: 22-07-2018 Through 27-07-2018",

url = "https://www.igarss2018.org/",

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Li, M & Bijker, W 2018, Potential of multi-temporal Sentinel-1A Dual polarization SAR images for vegetable classification in Indonesia. in IGARSS 2018 : IEEE International Geoscience and Remote Sensing Symposium : Observing, Understanding and Forecasting the Dynamics of Our Planet. IEEE Catalog Number: CFP18IGA-ART edn, IEEE, pp. 3828-3831, 38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, 22/07/18.

Potential of multi-temporal Sentinel-1A Dual polarization SAR images for vegetable classification in Indonesia. / Li, Mengmeng; Bijker, W.
IGARSS 2018 : IEEE International Geoscience and Remote Sensing Symposium : Observing, Understanding and Forecasting the Dynamics of Our Planet. IEEE Catalog Number: CFP18IGA-ART. ed. IEEE, 2018. p. 3828-3831.

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

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N2 - As part of the G4AW SMARTSeeds project, this study aims to investigate the potential of dense time series of Sentinel-1A dual polarization data for the classification of vegetables that are common in East Java, Indonesia. We first analyzed the temporal behavior of three main types of vegetables (i.e.chili, tomato and cucumber) in terms of backscatter (VH andVV) intensity, and of polarimetric features (i.e. entropy,al-pha and anisotropy) derived from polarization decomposition. We then applied a support vector machine with an intersection kernel to the time series data of vegetable samples collected infield. Our results showed that dense time series Sentinel-1Aimages are of high potential for vegetable classification. Be-sides using backscatter intensity, the polarimetric information can further improve the discrimination between three specific vegetable types.

AB - As part of the G4AW SMARTSeeds project, this study aims to investigate the potential of dense time series of Sentinel-1A dual polarization data for the classification of vegetables that are common in East Java, Indonesia. We first analyzed the temporal behavior of three main types of vegetables (i.e.chili, tomato and cucumber) in terms of backscatter (VH andVV) intensity, and of polarimetric features (i.e. entropy,al-pha and anisotropy) derived from polarization decomposition. We then applied a support vector machine with an intersection kernel to the time series data of vegetable samples collected infield. Our results showed that dense time series Sentinel-1Aimages are of high potential for vegetable classification. Be-sides using backscatter intensity, the polarimetric information can further improve the discrimination between three specific vegetable types.

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BT - IGARSS 2018 : IEEE International Geoscience and Remote Sensing Symposium : Observing, Understanding and Forecasting the Dynamics of Our Planet

PB - IEEE

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Y2 - 22 July 2018 through 27 July 2018

ER -

Potential of multi-temporal Sentinel-1A Dual polarization SAR images for vegetable classification in Indonesia

Abstract

Conference

UN SDGs

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