Impacts of Radiometric Uncertainty and Weather-Related Surface Conditions on Soil Moisture Retrievals with Sentinel-1

H.F. Benninga*, R. van der Velde, Z. Su

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)

Abstract

The radiometric uncertainty of Synthetic Aperture Radar (SAR) observations and weather-related surface conditions caused by frozen conditions, snow and intercepted rain affect the backscatter ( σ0 ) observations and limit the accuracy of soil moisture retrievals. This study estimates Sentinel-1’s radiometric uncertainty, identifies the effects of weather-related surface conditions on σ0 and investigates their impact on soil moisture retrievals for various conditions regarding soil moisture, surface roughness and incidence angle. Masking rules for the surface conditions that disturb σ0 were developed based on meteorological measurements and timeseries of Sentinel-1 observations collected over five forests, five meadows and five cultivated fields in the eastern part of the Netherlands. The Sentinel-1 σ0 observations appear to be affected by frozen conditions below an air temperature of 1 ∘C , snow during Sentinel-1’s morning overpasses on meadows and cultivated fields and interception after more than 1.8 m m of rain in the 12 h preceding a Sentinel-1 overpass, whereas dew was not found to be of influence. After the application of these masking rules, the radiometric uncertainty was estimated by the standard deviation of the seasonal anomalies timeseries of the Sentinel-1 forest σ0 observations. By spatially averaging the σ0 observations, the Sentinel-1 radiometric uncertainty improves from 0.85 dB for a surface area of 0.25 ha to 0.30 dB for 10 ha for the VV polarization and from 0.89 dB to 0.36 dB for the VH polarization, following approximately an inverse square root dependency on the surface area over which the σ0 observations are averaged. Deviations in σ0 were combined with the σ0 sensitivity to soil moisture as simulated with the Integral Equation Method (IEM) surface scattering model, which demonstrated that both the disturbing effects by the weather-related surface conditions (if not masked) and radiometric uncertainty have a significant impact on the soil moisture retrievals from Sentinel-1. The soil moisture retrieval uncertainty due to radiometric uncertainty ranges from 0.01 m3 m−3 up to 0.17 m3 m−3 for wet soils and small surface areas. The impacts on soil moisture retrievals are found to be weakly dependent on the surface roughness and the incidence angle, and strongly dependent on the surface area (or the σ0 disturbance caused by a weather-related surface condition for a specific land cover type) and the soil moisture itself.
Original languageEnglish
Article number2025
Number of pages28
JournalRemote sensing
Volume11
Issue number17
DOIs
Publication statusPublished - 2019

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soil moisture
weather
surface area
surface roughness
meadow
polarization
snow
dew
interception
backscatter
land cover
synthetic aperture radar
air temperature
scattering
anomaly
disturbance
soil

Keywords

  • ITC-ISI-JOURNAL-ARTICLE
  • ITC-GOLD

Cite this

@article{32d9a1ed5c2c4f6c839b457c700fb47a,
title = "Impacts of Radiometric Uncertainty and Weather-Related Surface Conditions on Soil Moisture Retrievals with Sentinel-1",
abstract = "The radiometric uncertainty of Synthetic Aperture Radar (SAR) observations and weather-related surface conditions caused by frozen conditions, snow and intercepted rain affect the backscatter ( σ0 ) observations and limit the accuracy of soil moisture retrievals. This study estimates Sentinel-1’s radiometric uncertainty, identifies the effects of weather-related surface conditions on σ0 and investigates their impact on soil moisture retrievals for various conditions regarding soil moisture, surface roughness and incidence angle. Masking rules for the surface conditions that disturb σ0 were developed based on meteorological measurements and timeseries of Sentinel-1 observations collected over five forests, five meadows and five cultivated fields in the eastern part of the Netherlands. The Sentinel-1 σ0 observations appear to be affected by frozen conditions below an air temperature of 1 ∘C , snow during Sentinel-1’s morning overpasses on meadows and cultivated fields and interception after more than 1.8 m m of rain in the 12 h preceding a Sentinel-1 overpass, whereas dew was not found to be of influence. After the application of these masking rules, the radiometric uncertainty was estimated by the standard deviation of the seasonal anomalies timeseries of the Sentinel-1 forest σ0 observations. By spatially averaging the σ0 observations, the Sentinel-1 radiometric uncertainty improves from 0.85 dB for a surface area of 0.25 ha to 0.30 dB for 10 ha for the VV polarization and from 0.89 dB to 0.36 dB for the VH polarization, following approximately an inverse square root dependency on the surface area over which the σ0 observations are averaged. Deviations in σ0 were combined with the σ0 sensitivity to soil moisture as simulated with the Integral Equation Method (IEM) surface scattering model, which demonstrated that both the disturbing effects by the weather-related surface conditions (if not masked) and radiometric uncertainty have a significant impact on the soil moisture retrievals from Sentinel-1. The soil moisture retrieval uncertainty due to radiometric uncertainty ranges from 0.01 m3 m−3 up to 0.17 m3 m−3 for wet soils and small surface areas. The impacts on soil moisture retrievals are found to be weakly dependent on the surface roughness and the incidence angle, and strongly dependent on the surface area (or the σ0 disturbance caused by a weather-related surface condition for a specific land cover type) and the soil moisture itself.",
keywords = "ITC-ISI-JOURNAL-ARTICLE, ITC-GOLD",
author = "H.F. Benninga and {van der Velde}, R. and Z. Su",
year = "2019",
doi = "10.3390/rs11172025",
language = "English",
volume = "11",
journal = "Remote sensing",
issn = "2072-4292",
publisher = "Multidisciplinary Digital Publishing Institute",
number = "17",

}

Impacts of Radiometric Uncertainty and Weather-Related Surface Conditions on Soil Moisture Retrievals with Sentinel-1. / Benninga, H.F.; van der Velde, R.; Su, Z.

In: Remote sensing, Vol. 11, No. 17, 2025, 2019.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Impacts of Radiometric Uncertainty and Weather-Related Surface Conditions on Soil Moisture Retrievals with Sentinel-1

AU - Benninga, H.F.

AU - van der Velde, R.

AU - Su, Z.

PY - 2019

Y1 - 2019

N2 - The radiometric uncertainty of Synthetic Aperture Radar (SAR) observations and weather-related surface conditions caused by frozen conditions, snow and intercepted rain affect the backscatter ( σ0 ) observations and limit the accuracy of soil moisture retrievals. This study estimates Sentinel-1’s radiometric uncertainty, identifies the effects of weather-related surface conditions on σ0 and investigates their impact on soil moisture retrievals for various conditions regarding soil moisture, surface roughness and incidence angle. Masking rules for the surface conditions that disturb σ0 were developed based on meteorological measurements and timeseries of Sentinel-1 observations collected over five forests, five meadows and five cultivated fields in the eastern part of the Netherlands. The Sentinel-1 σ0 observations appear to be affected by frozen conditions below an air temperature of 1 ∘C , snow during Sentinel-1’s morning overpasses on meadows and cultivated fields and interception after more than 1.8 m m of rain in the 12 h preceding a Sentinel-1 overpass, whereas dew was not found to be of influence. After the application of these masking rules, the radiometric uncertainty was estimated by the standard deviation of the seasonal anomalies timeseries of the Sentinel-1 forest σ0 observations. By spatially averaging the σ0 observations, the Sentinel-1 radiometric uncertainty improves from 0.85 dB for a surface area of 0.25 ha to 0.30 dB for 10 ha for the VV polarization and from 0.89 dB to 0.36 dB for the VH polarization, following approximately an inverse square root dependency on the surface area over which the σ0 observations are averaged. Deviations in σ0 were combined with the σ0 sensitivity to soil moisture as simulated with the Integral Equation Method (IEM) surface scattering model, which demonstrated that both the disturbing effects by the weather-related surface conditions (if not masked) and radiometric uncertainty have a significant impact on the soil moisture retrievals from Sentinel-1. The soil moisture retrieval uncertainty due to radiometric uncertainty ranges from 0.01 m3 m−3 up to 0.17 m3 m−3 for wet soils and small surface areas. The impacts on soil moisture retrievals are found to be weakly dependent on the surface roughness and the incidence angle, and strongly dependent on the surface area (or the σ0 disturbance caused by a weather-related surface condition for a specific land cover type) and the soil moisture itself.

AB - The radiometric uncertainty of Synthetic Aperture Radar (SAR) observations and weather-related surface conditions caused by frozen conditions, snow and intercepted rain affect the backscatter ( σ0 ) observations and limit the accuracy of soil moisture retrievals. This study estimates Sentinel-1’s radiometric uncertainty, identifies the effects of weather-related surface conditions on σ0 and investigates their impact on soil moisture retrievals for various conditions regarding soil moisture, surface roughness and incidence angle. Masking rules for the surface conditions that disturb σ0 were developed based on meteorological measurements and timeseries of Sentinel-1 observations collected over five forests, five meadows and five cultivated fields in the eastern part of the Netherlands. The Sentinel-1 σ0 observations appear to be affected by frozen conditions below an air temperature of 1 ∘C , snow during Sentinel-1’s morning overpasses on meadows and cultivated fields and interception after more than 1.8 m m of rain in the 12 h preceding a Sentinel-1 overpass, whereas dew was not found to be of influence. After the application of these masking rules, the radiometric uncertainty was estimated by the standard deviation of the seasonal anomalies timeseries of the Sentinel-1 forest σ0 observations. By spatially averaging the σ0 observations, the Sentinel-1 radiometric uncertainty improves from 0.85 dB for a surface area of 0.25 ha to 0.30 dB for 10 ha for the VV polarization and from 0.89 dB to 0.36 dB for the VH polarization, following approximately an inverse square root dependency on the surface area over which the σ0 observations are averaged. Deviations in σ0 were combined with the σ0 sensitivity to soil moisture as simulated with the Integral Equation Method (IEM) surface scattering model, which demonstrated that both the disturbing effects by the weather-related surface conditions (if not masked) and radiometric uncertainty have a significant impact on the soil moisture retrievals from Sentinel-1. The soil moisture retrieval uncertainty due to radiometric uncertainty ranges from 0.01 m3 m−3 up to 0.17 m3 m−3 for wet soils and small surface areas. The impacts on soil moisture retrievals are found to be weakly dependent on the surface roughness and the incidence angle, and strongly dependent on the surface area (or the σ0 disturbance caused by a weather-related surface condition for a specific land cover type) and the soil moisture itself.

KW - ITC-ISI-JOURNAL-ARTICLE

KW - ITC-GOLD

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

U2 - 10.3390/rs11172025

DO - 10.3390/rs11172025

M3 - Article

VL - 11

JO - Remote sensing

JF - Remote sensing

SN - 2072-4292

IS - 17

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ER -