the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The significance of soil properties to the estimation of soil moisture from C-band synthetic aperture radar
Abstract. Soil Moisture is a key variable in hydrology, weather and climate modelling. Research has been directed to the estimation of soil moisture over wide areas through a combination of modelling, in-situ measurement and remote sensing to improve the accuracy of hydrological and meteorological forecasting. For monitoring and controlling irrigation and other agricultural purposes, there is also a need to capture local variability. Significant soil moisture differences are observed between and within fields due to land use, soil properties, drainage, tillage, vegetation, solar radiation, air temperature, wind, rain and other factors. Taking the United Kingdom as an example, the average area of agricultural fields is about 12 hectares, requiring a mapping resolution of less than 100 m. Satellite-based remote sensing, including the use of C-band SAR (such as on Sentinel-1), has the potential to satisfy this requirement, but many current data products are aggregated to a spatial resolution of at least 1km and/or provide soil moisture in relative units or indices. Both strategies mitigate the uncertainties introduced by field-scale variability in soil hydrological and vegetation properties. Geospatial datasets of soil properties and land use, crop modelling and other remote sensing techniques may provide an alternative approach to mitigating this variability and allow finer scale products to be produced with acceptable errors. This paper looks at the role of soil properties in the estimation of soil moisture from C-band SAR. We show that information on the soil texture, organic matter content, surface temperature, land use and crop modelling should be important inputs to the success of retrieving soil moisture at the field scale. Previously published data provides guidance in setting soil roughness parameters, based on soil properties, following farming operations such as primary tillage. Beyond soil moisture retrieval, there is exciting potential in SAR remote sensing data to improve the spatial resolution and mapping accuracy of some soil properties.
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RC1: 'Review of ‘The significance of soil properties to the estimation of soil moisture from C-band synthetic aperture radar’', Anonymous Referee #1, 19 Jul 2019
- AC1: 'Authors; Response to Referee #1', John Beale, 05 Nov 2019
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RC2: 'Review of Beale et al.', Anonymous Referee #2, 09 Oct 2019
- AC1: 'Authors; Response to Referee #1', John Beale, 05 Nov 2019
-
RC1: 'Review of ‘The significance of soil properties to the estimation of soil moisture from C-band synthetic aperture radar’', Anonymous Referee #1, 19 Jul 2019
- AC1: 'Authors; Response to Referee #1', John Beale, 05 Nov 2019
-
RC2: 'Review of Beale et al.', Anonymous Referee #2, 09 Oct 2019
- AC1: 'Authors; Response to Referee #1', John Beale, 05 Nov 2019
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Cited
9 citations as recorded by crossref.
- Retrieving the Soil Moisture in Bare Farmland Areas Using a Modified Dubois Model T. Ma et al. 10.3389/feart.2021.735958
- Challenges and Opportunities in Remote Sensing for Soil Salinization Mapping and Monitoring: A Review G. Sahbeni et al. 10.3390/rs15102540
- Estimation of High-Resolution Soil Moisture in Canadian Croplands Using Deep Neural Network with Sentinel-1 and Sentinel-2 Images S. Lee et al. 10.3390/rs15164063
- Estimating Soil Moisture by Radar Data Based on Multiple Regression N. Rodionova 10.1134/S0001433823120186
- Soil salinity estimation: Effects of microwave dielectric spectroscopy and important frequencies S. Zhao et al. 10.1002/ldr.4564
- High resolution C-band SAR backscatter response to peatland water table depth and soil moisture: a laboratory experiment L. Toca et al. 10.1080/01431161.2022.2131478
- Sentinel-1 SAR interferometry for agriculture: description of an experiment in Oryol, Russia G. Nico et al. 10.35595/2414-9179-2020-3-26-124-131
- Soil Moisture Estimation by Radar Data Based on Multiple Regression N. Rodionova 10.31857/S0205961423050068
- Very High Spatial Resolution Soil Moisture Observation of Heterogeneous Subarctic Catchment Using Nonlocal Averaging and Multitemporal SAR Data T. Manninen et al. 10.1109/TGRS.2021.3109695