Sensitivity of C-Band SAR Polarimetric Variables to the Directionality of Surface Roughness Parameters
Open Access
- 5 June 2021
- journal article
- research article
- Published by MDPI AG in Remote Sensing
- Vol. 13 (11), 2210
- https://doi.org/10.3390/rs13112210
Abstract
Surface roughness is an important factor in many soil moisture retrieval models. Therefore, any mischaracterization of surface roughness parameters (root mean square height, RMSH, and correlation length, ʅ) may result in unreliable predictions and soil moisture estimations. In many environments, but particularly in agricultural settings, surface roughness parameters may show different behaviours with respect to the orientation or azimuth. Consequently, the relationship between SAR polarimetric variables and surface roughness parameters may vary depending on measurement orientation. Generally, roughness obtained for many SAR-based studies is estimated using pin profilers that may, or may not, be collected with careful attention to orientation to the satellite look angle. In this study, we characterized surface roughness parameters in multi-azimuth mode using a terrestrial laser scanner (TLS). We characterized the surface roughness parameters in different orientations and then examined the sensitivity between polarimetric variables and surface roughness parameters; further, we compared these results to roughness profiles obtained using traditional pin profilers. The results showed that the polarimetric variables were more sensitive to the surface roughness parameters at higher incidence angles (θ). Moreover, when surface roughness measurements were conducted at the look angle of RADARSAT-2, more significant correlations were observed between polarimetric variables and surface roughness parameters. Our results also indicated that TLS can represent more reliable results than pin profiler in the measurement of the surface roughness parameters.Funding Information
- Canada First Research Excellence Fund (Food From Thought)
This publication has 51 references indexed in Scilit:
- Assessing the active-passive approach at variant incidence angles for microwave brightness temperature downscalingInternational Journal of Digital Earth, 2021
- ALOS-2 and Sentinel-1 SAR data sensitivity analysis to surface soil moisture over bare and vegetated agricultural fieldsComputers and Electronics in Agriculture, 2020
- The SMAP and Copernicus Sentinel 1A/B microwave active-passive high resolution surface soil moisture productRemote Sensing of Environment, 2019
- Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural NetworksSensors, 2019
- Fine-Scale SAR Soil Moisture Estimation in the Subarctic TundraIEEE Transactions on Geoscience and Remote Sensing, 2019
- Surface Soil Moisture Retrieval Using the L-Band Synthetic Aperture Radar Onboard the Soil Moisture Active–Passive Satellite and Evaluation at Core Validation SitesIEEE Transactions on Geoscience and Remote Sensing, 2017
- Toward an Operational Bare Soil Moisture Mapping Using TerraSAR-X Data Acquired Over Agricultural AreasIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2012
- Mapping Soil Moisture Using RADARSAT-2 Data and Local Autocorrelation StatisticsIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2011
- Measuring Surface Roughness Height to Parameterize Radar Backscatter Models for Retrieval of Surface Soil MoistureIEEE Geoscience and Remote Sensing Letters, 2007
- Backscattering from a randomly rough dielectric surfaceIEEE Transactions on Geoscience and Remote Sensing, 1992