Potential of Sentinel-1 Radar Data for the Assessment of Soil and Cereal Cover Parameters

The main objective of this study is to analyze the potential use of Sentinel-1 (S1) radar data for the estimation of soil characteristics (roughness and water content) and cereal vegetation parameters (leaf area index (LAI), and vegetation height (H)) in agricultural areas. Simultaneously to several radar acquisitions made between 2015 and 2017, using S1 sensors over the Kairouan Plain (Tunisia, North Africa), ground measurements of soil roughness, soil water content, LAI and H were recorded. The NDVI (normalized difference vegetation index) index computed from Landsat optical images revealed a strong correlation with in situ measurements of LAI. The sensitivity of the S1 measurements to variations in soil moisture, which has been reported in several scientific publications, is confirmed in this study. This sensitivity decreases with increasing vegetation cover growth (NDVI), and is stronger in the VV (vertical) polarization than in the VH cross-polarization. The results also reveal a similar increase in the dynamic range of radar signals observed in the VV and VH polarizations as a function of soil roughness. The sensitivity of S1 measurements to vegetation parameters (LAI and H) in the VV polarization is also determined, showing that the radar signal strength decreases when the vegetation parameters increase. No vegetation parameter sensitivity is observed in the VH polarization, probably as a consequence of volume scattering effects.

[1]  Anthi-Eirini K. Vozinaki,et al.  Soil Moisture Content Estimation Based on Sentinel-1 and Auxiliary Earth Observation Products. A Hydrological Approach , 2017, Sensors.

[2]  Thuy Le Toan,et al.  The effect of surface roughness on multifrequency polarimetric SAR data , 1997, IEEE Trans. Geosci. Remote. Sens..

[3]  Hari Shanker Srivastava,et al.  Use of multiincidence angle RADARSAT-1 SAR data to incorporate the effect of surface roughness in soil moisture estimation , 2003, IEEE Trans. Geosci. Remote. Sens..

[4]  Rajat Bindlish,et al.  Parameterization of vegetation backscatter in radar-based, soil moisture estimation , 2001 .

[5]  D. Lawrence,et al.  Regions of Strong Coupling Between Soil Moisture and Precipitation , 2004, Science.

[6]  N. Baghdadi,et al.  Microwave Remote Sensing of Land Surfaces: Techniques and Methods , 2016 .

[7]  Gérard Dedieu,et al.  Combined use of FORMOSAT-2 images with a crop model for biomass and water monitoring of permanent grassland in Mediterranean region , 2010 .

[8]  Mehrez Zribi,et al.  Mapping of surface soil parameters (roughness, moisture and texture) using one radar X-band SAR configuration over bare agricultural semi-arid region , 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[9]  Li Li,et al.  Advances in estimation methods of vegetation water content based on optical remote sensing techniques , 2010 .

[10]  Mehrez Zribi,et al.  Operational performance of current synthetic aperture radar sensors in mapping soil surface characteristics in agricultural environments: application to hydrological and erosion modelling , 2008 .

[11]  Bernard De Baets,et al.  Error in Radar-Derived Soil Moisture due to Roughness Parameterization: An Analysis Based on Synthetical Surface Profiles , 2009, Sensors.

[12]  Emanuele Santi,et al.  Soil Moisture Estimates From AMSR-E Brightness Temperatures by Using a Dual-Frequency Algorithm , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[13]  Kamal Sarabandi,et al.  An empirical model and an inversion technique for radar scattering from bare soil surfaces , 1992, IEEE Trans. Geosci. Remote. Sens..

[14]  Jiancheng Shi,et al.  A Comparison of Soil Moisture Retrieval Models Using SIR-C Measurements over the Little Washita River Watershed , 1997 .

[15]  Dharrnendra Singh.  A simplistic incidence angle approach to retrieve the soil moisture and surface roughness at X-band , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[16]  Jiancheng Shi,et al.  Estimation of bare surface soil moisture and surface roughness parameter using L-band SAR image data , 1997, IEEE Trans. Geosci. Remote. Sens..

[17]  Pascale C. Dubois,et al.  Measuring soil moisture with imaging radars , 1995, IEEE Trans. Geosci. Remote. Sens..

[18]  Claudia Notarnicola,et al.  Soil moisture retrieval from remotely sensed data: Neural network approach versus Bayesian method , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[19]  Nicolas Baghdadi,et al.  Multitemporal Observations of Sugarcane by TerraSAR-X Images , 2010, Sensors.

[20]  Emanuele Santi,et al.  pplication of artificial neural networks for the soil moisture retrieval rom active and passive microwave spaceborne sensors , 2015 .

[21]  Xin Wang,et al.  First Assessment of Sentinel-1A Data for Surface Soil Moisture Estimations Using a Coupled Water Cloud Model and Advanced Integral Equation Model over the Tibetan Plateau , 2017, Remote. Sens..

[22]  Simonetta Paloscia,et al.  The potential of C- and L-band SAR in estimating vegetation biomass: the ERS-1 and JERS-1 experiments , 1999, IEEE Trans. Geosci. Remote. Sens..

[23]  W. Wagner,et al.  A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data , 1999 .

[24]  Niko E. C. Verhoest,et al.  Effective roughness modelling as a tool for soil moisture retrieval from C-and L-band SAR , 2010 .

[25]  Hari Shanker Srivastava,et al.  Large-Area Soil Moisture Estimation Using Multi-Incidence-Angle RADARSAT-1 SAR Data , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[26]  A. Chehbouni,et al.  Soil surface moisture estimation over a semi-arid region using ENVISAT ASAR radar data for soil evaporation evaluation , 2011 .

[27]  Adrian K. Fung,et al.  Backscattering from a randomly rough dielectric surface , 1992, IEEE Trans. Geosci. Remote. Sens..

[28]  C. Ottlé,et al.  Water and energy budgets simulation over the AMMA-Niger super-site spatially constrained with remote sensing data , 2009 .

[29]  George P. Petropoulos,et al.  Surface soil moisture retrievals from remote sensing: Current status, products & future trends , 2015 .

[30]  B. Duchemin,et al.  Combined use of optical and radar satellite data for the monitoring of irrigation and soil moisture of wheat crops , 2011 .

[31]  Claire Marais-Sicre,et al.  Monitoring Wheat and Rapeseed by Using Synchronous Optical and Radar Satellite Data—From Temporal Signatures to Crop Parameters Estimation , 2013 .

[32]  Mehrez Zribi,et al.  Influence of Radar Frequency on the Relationship Between Bare Surface Soil Moisture Vertical Profile and Radar Backscatter , 2014, IEEE Geoscience and Remote Sensing Letters.

[33]  Tingting Zhang,et al.  Modeling and Mapping Soil Moisture of Plateau Pasture Using RADARSAT-2 Imagery , 2015, Remote. Sens..

[34]  Mehrez Zribi,et al.  Evaluation of a rough soil surface description with ASAR-ENVISAT radar data , 2005 .

[35]  F. Yu,et al.  A new semi-empirical model for soil moisture content retrieval by ASAR and TM data in vegetation-covered areas , 2011 .

[36]  Dawei Han,et al.  The Relevance of Soil Moisture by Remote Sensing and Hydrological Modelling , 2016 .

[37]  Mehrez Zribi,et al.  Soil moisture mapping based on ASAR/ENVISAT radar data over a Sahelian region , 2007 .

[38]  Hao Wang,et al.  Investigation of Rainfall-Runoff Processes and Soil Moisture Dynamics in Grassland Plots under Simulated Rainfall Conditions , 2014 .

[39]  Mehrez Zribi,et al.  A new soil roughness parameter for the modelling of radar backscattering over bare soil , 2014, 2014 IEEE Geoscience and Remote Sensing Symposium.

[40]  F. Ulaby,et al.  Vegetation modeled as a water cloud , 1978 .

[41]  G. Asrar,et al.  Estimating Absorbed Photosynthetic Radiation and Leaf Area Index from Spectral Reflectance in Wheat1 , 1984 .

[42]  M. Weissa,et al.  Review of methods for in situ leaf area index ( LAI ) determination Part II . Estimation of LAI , errors and sampling , 2003 .

[43]  Mehrez Zribi,et al.  Coupling SAR C-Band and Optical Data for Soil Moisture and Leaf Area Index Retrieval Over Irrigated Grasslands , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[44]  N. Baghdadi,et al.  Estimation of soil parameters over bare agriculture areas from C-band polarimetric SAR data using neural networks , 2012 .

[45]  Simonetta Paloscia,et al.  Sensitivity analysis of X-band SAR to wheat and barley leaf area index in the Merguellil Basin , 2013 .

[46]  Frédéric Baup,et al.  A New Empirical Model for Radar Scattering from Bare Soil Surfaces , 2016, Remote. Sens..

[47]  Benoît Duchemin,et al.  A simple algorithm for yield estimates: Evaluation for semi-arid irrigated winter wheat monitored with green leaf area index , 2008, Environ. Model. Softw..

[48]  A. Fung.  Microwave Scattering and Emission Models and their Applications , 1994 .

[49]  Mehrez Zribi,et al.  Irrigated Grassland Monitoring Using a Time Series of TerraSAR-X and COSMO-SkyMed X-Band SAR Data , 2014, Remote. Sens..

[50]  D. Vidal-Madjar,et al.  Backscattering behavior and simulation comparison over bare soils using SIR-C/X-SAR and ERASME 1994 data over Orgeval , 1997 .

[51]  Mehrez Zribi,et al.  Potential of ASAR/ENVISAT for the characterization of soil surface parameters over bare agricultural fields , 2005 .

[52]  Qi Gao,et al.  Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at 100 m Resolution , 2017, Sensors.

[53]  Kalifa Goita,et al.  Evaluation of Simplified Polarimetric Decomposition for Soil Moisture Retrieval over Vegetated Agricultural Fields , 2016, Remote. Sens..