Evaluation of Sentinel-2 and RapidEye for Retrieval of LAI in a Saltmarsh using Radiative transfer model

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Abstract

A new era in the retrieval of plant traits has started by emerging the new satellites such as the Copernicus Sentinel families. Among these traits, leaf area index (LAI) is a key indicator of vegetation growth and an essential variable in biodiversity studies. Numerous literature has shown that radiative transfer approach has been a successful method to retrieve LAI from remote sensing data. However, suitability and adaptability of this approach largely depend on the type of remote sensing data, and the ecosystem studied. In this regard, the retrieval of leaf area index in a saltmarsh ecosystem is examined in this study using Sentinel-2 and RapidEye data through inversion of PROSAILH radiative transfer model. Field measurements of LAI and a number of other plant traits were obtained during two succeeding field campaigns in July 2015 and 2016 in the saltmarsh of Schiermonnikoog, the Netherlands. Sentinel-2 (2016) and RapidEye (2015) data were acquired concurrent to the time of field campaigns. The broadly employed PROSAILH model was inverted using a look-up table (LUT) which contained 500, 000 records. Different scenarios of band combinations, as well as different solutions, were considered to obtain the LAI estimates. The R2 and RMSE between measured and estimated LAI were used then to evaluate the retrieval accuracy. The removal of dead materials from the measured LAI improved the estimation accuracies. Our results showed that generally the LAI retrieved using the Sentinel-2 data had higher accuracy compared to RapidEye data. In particular, the SWIR bands of Sentinel were modeled best using the PROSAILH. Leaf area index was best retrieved using the NIR and SWIR bands of Sentinel-2 (R2=0.56, RMSE=1.7). Our results highlight the importance of proper parametrization of radiative transfer models and capacity of Sentinel-2 data, with impending high-quality global observation aptitude, for retrieval of plant traits at a global scale.
Original languageEnglish
Number of pages1
Publication statusPublished - 13 May 2019
EventESA Living Planet Symposium 2019 - Milano Congressi, Milan, Italy
Duration: 13 May 201917 May 2019
https://lps19.esa.int/NikalWebsitePortal/living-planet-symposium-2019/lps19

Conference

ConferenceESA Living Planet Symposium 2019
CountryItaly
CityMilan
Period13/05/1917/05/19
Internet address

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saltmarsh
leaf area index
radiative transfer
remote sensing
evaluation
RapidEye
ecosystem
biodiversity
vegetation

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@conference{2861a051f34f46858dfcc3d4827f628c,
title = "Evaluation of Sentinel-2 and RapidEye for Retrieval of LAI in a Saltmarsh using Radiative transfer model",
abstract = "A new era in the retrieval of plant traits has started by emerging the new satellites such as the Copernicus Sentinel families. Among these traits, leaf area index (LAI) is a key indicator of vegetation growth and an essential variable in biodiversity studies. Numerous literature has shown that radiative transfer approach has been a successful method to retrieve LAI from remote sensing data. However, suitability and adaptability of this approach largely depend on the type of remote sensing data, and the ecosystem studied. In this regard, the retrieval of leaf area index in a saltmarsh ecosystem is examined in this study using Sentinel-2 and RapidEye data through inversion of PROSAILH radiative transfer model. Field measurements of LAI and a number of other plant traits were obtained during two succeeding field campaigns in July 2015 and 2016 in the saltmarsh of Schiermonnikoog, the Netherlands. Sentinel-2 (2016) and RapidEye (2015) data were acquired concurrent to the time of field campaigns. The broadly employed PROSAILH model was inverted using a look-up table (LUT) which contained 500, 000 records. Different scenarios of band combinations, as well as different solutions, were considered to obtain the LAI estimates. The R2 and RMSE between measured and estimated LAI were used then to evaluate the retrieval accuracy. The removal of dead materials from the measured LAI improved the estimation accuracies. Our results showed that generally the LAI retrieved using the Sentinel-2 data had higher accuracy compared to RapidEye data. In particular, the SWIR bands of Sentinel were modeled best using the PROSAILH. Leaf area index was best retrieved using the NIR and SWIR bands of Sentinel-2 (R2=0.56, RMSE=1.7). Our results highlight the importance of proper parametrization of radiative transfer models and capacity of Sentinel-2 data, with impending high-quality global observation aptitude, for retrieval of plant traits at a global scale.",
author = "R. Darvishzadeh and A.K. Skidmore and Tiejun Wang and A. Vrieling",
year = "2019",
month = "5",
day = "13",
language = "English",
note = "ESA Living Planet Symposium 2019 ; Conference date: 13-05-2019 Through 17-05-2019",
url = "https://lps19.esa.int/NikalWebsitePortal/living-planet-symposium-2019/lps19",

}

Evaluation of Sentinel-2 and RapidEye for Retrieval of LAI in a Saltmarsh using Radiative transfer model. / Darvishzadeh, R.; Skidmore, A.K.; Wang, Tiejun; Vrieling, A.

2019. Poster session presented at ESA Living Planet Symposium 2019, Milan, Italy.

Research output: Contribution to conferencePosterOther research output

TY - CONF

T1 - Evaluation of Sentinel-2 and RapidEye for Retrieval of LAI in a Saltmarsh using Radiative transfer model

AU - Darvishzadeh, R.

AU - Skidmore, A.K.

AU - Wang, Tiejun

AU - Vrieling, A.

PY - 2019/5/13

Y1 - 2019/5/13

N2 - A new era in the retrieval of plant traits has started by emerging the new satellites such as the Copernicus Sentinel families. Among these traits, leaf area index (LAI) is a key indicator of vegetation growth and an essential variable in biodiversity studies. Numerous literature has shown that radiative transfer approach has been a successful method to retrieve LAI from remote sensing data. However, suitability and adaptability of this approach largely depend on the type of remote sensing data, and the ecosystem studied. In this regard, the retrieval of leaf area index in a saltmarsh ecosystem is examined in this study using Sentinel-2 and RapidEye data through inversion of PROSAILH radiative transfer model. Field measurements of LAI and a number of other plant traits were obtained during two succeeding field campaigns in July 2015 and 2016 in the saltmarsh of Schiermonnikoog, the Netherlands. Sentinel-2 (2016) and RapidEye (2015) data were acquired concurrent to the time of field campaigns. The broadly employed PROSAILH model was inverted using a look-up table (LUT) which contained 500, 000 records. Different scenarios of band combinations, as well as different solutions, were considered to obtain the LAI estimates. The R2 and RMSE between measured and estimated LAI were used then to evaluate the retrieval accuracy. The removal of dead materials from the measured LAI improved the estimation accuracies. Our results showed that generally the LAI retrieved using the Sentinel-2 data had higher accuracy compared to RapidEye data. In particular, the SWIR bands of Sentinel were modeled best using the PROSAILH. Leaf area index was best retrieved using the NIR and SWIR bands of Sentinel-2 (R2=0.56, RMSE=1.7). Our results highlight the importance of proper parametrization of radiative transfer models and capacity of Sentinel-2 data, with impending high-quality global observation aptitude, for retrieval of plant traits at a global scale.

AB - A new era in the retrieval of plant traits has started by emerging the new satellites such as the Copernicus Sentinel families. Among these traits, leaf area index (LAI) is a key indicator of vegetation growth and an essential variable in biodiversity studies. Numerous literature has shown that radiative transfer approach has been a successful method to retrieve LAI from remote sensing data. However, suitability and adaptability of this approach largely depend on the type of remote sensing data, and the ecosystem studied. In this regard, the retrieval of leaf area index in a saltmarsh ecosystem is examined in this study using Sentinel-2 and RapidEye data through inversion of PROSAILH radiative transfer model. Field measurements of LAI and a number of other plant traits were obtained during two succeeding field campaigns in July 2015 and 2016 in the saltmarsh of Schiermonnikoog, the Netherlands. Sentinel-2 (2016) and RapidEye (2015) data were acquired concurrent to the time of field campaigns. The broadly employed PROSAILH model was inverted using a look-up table (LUT) which contained 500, 000 records. Different scenarios of band combinations, as well as different solutions, were considered to obtain the LAI estimates. The R2 and RMSE between measured and estimated LAI were used then to evaluate the retrieval accuracy. The removal of dead materials from the measured LAI improved the estimation accuracies. Our results showed that generally the LAI retrieved using the Sentinel-2 data had higher accuracy compared to RapidEye data. In particular, the SWIR bands of Sentinel were modeled best using the PROSAILH. Leaf area index was best retrieved using the NIR and SWIR bands of Sentinel-2 (R2=0.56, RMSE=1.7). Our results highlight the importance of proper parametrization of radiative transfer models and capacity of Sentinel-2 data, with impending high-quality global observation aptitude, for retrieval of plant traits at a global scale.

UR - https://ezproxy2.utwente.nl/login?url=https://library.itc.utwente.nl/login/2019/pres/darvishzadeh_eva_pos.pdf

M3 - Poster

ER -