Mapping plant communities in the intertidal zones using Sentinel-2 and Sentinel-1 data

Tiejun Wang; Yansha Luo; Yiwen  Sun; Xinhui Liu

doi:10.1109/IGARSS.2018.8518347

Mapping plant communities in the intertidal zones using Sentinel-2 and Sentinel-1 data

Tiejun Wang, Yansha Luo, Yiwen Sun, Xinhui Liu

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

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Abstract

Intertidal habitats are important not only for the ecosystem services they provide but also because they represent a key ecotone between land and ocean. In this paper we explore the synergistic use of time series Sentinel-1 and Sentinel-2 data for mapping intertidal plant communities, using a Random Forest algorithm. We compare the performances of ten models with different input data. Results showed that the use of multi-seasonal Sentinel-2 images could significantly improve the mapping accuracy compared to the use of any single-season image. There was no statistically significant difference in mapping accuracies between the use of multi-seasonal and time series Sentinel-2 images. However, when combining time series Sentinel-1 data, time series Sentinel-2 data and NDVI statistic metrics, the highest mapping accuracy was achieved with an overall mapping accuracy of 77.7% and the Kappa coefficient of 0.75.

Original language	English
Title of host publication	IGARSS 2018 : IEEE International Geoscience and Remote Sensing Symposium : Observing, Understanding and Forcasting the Dynamics of Our Planet
Publisher	IEEE
Pages	8390-8393
Number of pages	4
ISBN (Electronic)	978-1-5386-7150-4
ISBN (Print)	978-1-5386-7150-4
DOIs	https://doi.org/10.1109/IGARSS.2018.8518347
Publication status	Published - 22 Jul 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/

Keywords

2019 OA procedure

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10.1109/IGARSS.2018.8518347

mappingFinal published version, 254 KBLicence: Taverne

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@inproceedings{72f315955bed4533875333c508b00a78,

title = "Mapping plant communities in the intertidal zones using Sentinel-2 and Sentinel-1 data",

abstract = "Intertidal habitats are important not only for the ecosystem services they provide but also because they represent a key ecotone between land and ocean. In this paper we explore the synergistic use of time series Sentinel-1 and Sentinel-2 data for mapping intertidal plant communities, using a Random Forest algorithm. We compare the performances of ten models with different input data. Results showed that the use of multi-seasonal Sentinel-2 images could significantly improve the mapping accuracy compared to the use of any single-season image. There was no statistically significant difference in mapping accuracies between the use of multi-seasonal and time series Sentinel-2 images. However, when combining time series Sentinel-1 data, time series Sentinel-2 data and NDVI statistic metrics, the highest mapping accuracy was achieved with an overall mapping accuracy of 77.7% and the Kappa coefficient of 0.75.",

keywords = "2019 OA procedure",

author = "Tiejun Wang and Yansha Luo and Yiwen Sun and Xinhui Liu",

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language = "English",

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booktitle = "IGARSS 2018 : IEEE International Geoscience and Remote Sensing Symposium : Observing, Understanding and Forcasting the Dynamics of Our Planet",

publisher = "IEEE",

address = "United States",

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/",

}

Wang, T, Luo, Y, Sun, Y & Liu, X 2018, Mapping plant communities in the intertidal zones using Sentinel-2 and Sentinel-1 data. in IGARSS 2018 : IEEE International Geoscience and Remote Sensing Symposium : Observing, Understanding and Forcasting the Dynamics of Our Planet . IEEE, pp. 8390-8393, 38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, 22/07/18. https://doi.org/10.1109/IGARSS.2018.8518347

Mapping plant communities in the intertidal zones using Sentinel-2 and Sentinel-1 data. / Wang, Tiejun; Luo, Yansha; Sun, Yiwen et al.
IGARSS 2018 : IEEE International Geoscience and Remote Sensing Symposium : Observing, Understanding and Forcasting the Dynamics of Our Planet . IEEE, 2018. p. 8390-8393.

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

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T1 - Mapping plant communities in the intertidal zones using Sentinel-2 and Sentinel-1 data

AU - Wang, Tiejun

AU - Luo, Yansha

AU - Sun, Yiwen

AU - Liu, Xinhui

N1 - Conference code: 38

PY - 2018/7/22

Y1 - 2018/7/22

N2 - Intertidal habitats are important not only for the ecosystem services they provide but also because they represent a key ecotone between land and ocean. In this paper we explore the synergistic use of time series Sentinel-1 and Sentinel-2 data for mapping intertidal plant communities, using a Random Forest algorithm. We compare the performances of ten models with different input data. Results showed that the use of multi-seasonal Sentinel-2 images could significantly improve the mapping accuracy compared to the use of any single-season image. There was no statistically significant difference in mapping accuracies between the use of multi-seasonal and time series Sentinel-2 images. However, when combining time series Sentinel-1 data, time series Sentinel-2 data and NDVI statistic metrics, the highest mapping accuracy was achieved with an overall mapping accuracy of 77.7% and the Kappa coefficient of 0.75.

AB - Intertidal habitats are important not only for the ecosystem services they provide but also because they represent a key ecotone between land and ocean. In this paper we explore the synergistic use of time series Sentinel-1 and Sentinel-2 data for mapping intertidal plant communities, using a Random Forest algorithm. We compare the performances of ten models with different input data. Results showed that the use of multi-seasonal Sentinel-2 images could significantly improve the mapping accuracy compared to the use of any single-season image. There was no statistically significant difference in mapping accuracies between the use of multi-seasonal and time series Sentinel-2 images. However, when combining time series Sentinel-1 data, time series Sentinel-2 data and NDVI statistic metrics, the highest mapping accuracy was achieved with an overall mapping accuracy of 77.7% and the Kappa coefficient of 0.75.

KW - 2019 OA procedure

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DO - 10.1109/IGARSS.2018.8518347

M3 - Conference contribution

SN - 978-1-5386-7150-4

SP - 8390

EP - 8393

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

PB - IEEE

T2 - 38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018

Y2 - 22 July 2018 through 27 July 2018

ER -

Mapping plant communities in the intertidal zones using Sentinel-2 and Sentinel-1 data

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