Advances in Radar Remote Sensing of Agricultural Crops: A Review

There are enormous advantages of a review article in the field of emerging technology like radar remote sensing applications in agriculture. This paper aims to report select recent advancements in the field of Synthetic Aperture Radar (SAR) remote sensing of crops. In order to make the paper comprehensive and more meaningful for the readers, an attempt has also been made to include discussion on various technologies of SAR sensors used for remote sensing of agricultural crops viz. basic SAR sensor, SAR interferometry (InSAR), SAR polarimetry (PolSAR) and polarimetric interferometry SAR (PolInSAR). The paper covers all the methodologies used for various agricultural applications like empirically based models, machine learning based models and radiative transfer theorem based models. A thorough literature review of more than 100 research papers indicates that SAR polarimetry can be used effectively for crop inventory and biophysical parameters estimation such are leaf area index, plant water content, and biomass but shown less sensitivity towards plant height as compared to SAR interferometry. Polarimetric SAR Interferometry is preferable for taking advantage of both SAR polarimetry and SAR interferometry. Numerous studies based upon multi-parametric SAR indicate that optimum selection of SAR sensor parameters enhances SAR sensitivity as a whole for various agricultural applications. It has been observed that researchers are widely using three models such are empirical, machine learning and radiative transfer theorem based models. Machine learning based models are identified as a better approach for crop monitoring using radar remote sensing data. It is expected that the review article will not only generate interest amongst the readers to explore and exploit radar remote sensing for various agricultural applications but also provide a ready reference to the researchers working in this field

Soil permittivity estimation over croplands using full and compact polarimetric SAR data

Soil permittivity estimation using Polarimetric Synthetic Aperture Radar (PolSAR) data has been an extensively researched area. Nonetheless, it provides ample scope for further improvements. The vegetation cover over the soil surface leads to a complex interaction of the incident polarized wave with the canopy and subsequently with the underlying soil surface. This paper introduces a novel methodology to estimate soil permittivity over croplands with vegetation cover using the full and compact polarimetric modes. The proposed method utilizes the full and compact polarimetric scattering-type parameters, θ FP and θ CP , respectively. These scattering type parameters are a function of the soil permittivity and the Barakat degree of polarization. The method considers the X-Bragg scattering model for the soil surface. In particular, these scattering-type parameters explicitly account for the depolarizing structure of the scattered wave while characterizing targets. Thus, the depolarization information in terms of surface roughness in the X-Bragg model gets inherent importance while using θ FP and θ CP , unlike existing scattering-type parameters. Therefore, the proposed technique enhances the expected value of the inversion accuracies. This study validated the major phenology stages of four crops using the UAVSAR full-pol and simulated compact pol SAR data and the ground truth data collected during the SMAPVEX12 campaign over Manitoba, Canada. The proposed method estimated permittivity with an RMSE of 2.2 to 4.69 for FP and 3.28 to 5.45 for CP SAR data along with a Pearson coefficient, r ≥ 0.62.Peer ReviewedPostprint (author's final draft

Study of the speckle noise effects over the eigen decomposition of polarimetric SAR data: a review

This paper is focused on considering the effects of speckle noise on the eigen decomposition of the co- herency matrix. Based on a perturbation analysis of the matrix, it is possible to obtain an analytical expression for the mean value of the eigenvalues and the eigenvectors, as well as for the Entropy, the Anisotroopy and the dif- ferent a angles. The analytical expressions are compared against simulated polarimetric SAR data, demonstrating the correctness of the different expressions.Peer ReviewedPostprint (published version

Polarimetric Synthetic Aperture Radar

This open access book focuses on the practical application of electromagnetic polarimetry principles in Earth remote sensing with an educational purpose. In the last decade, the operations from fully polarimetric synthetic aperture radar such as the Japanese ALOS/PalSAR, the Canadian Radarsat-2 and the German TerraSAR-X and their easy data access for scientific use have developed further the research and data applications at L,C and X band. As a consequence, the wider distribution of polarimetric data sets across the remote sensing community boosted activity and development in polarimetric SAR applications, also in view of future missions. Numerous experiments with real data from spaceborne platforms are shown, with the aim of giving an up-to-date and complete treatment of the unique benefits of fully polarimetric synthetic aperture radar data in five different domains: forest, agriculture, cryosphere, urban and oceans

Quantitative Estimation of Surface Soil Moisture in Agricultural Landscapes using Spaceborne Synthetic Aperture Radar Imaging at Different Frequencies and Polarizations

Soil moisture and its distribution in space and time plays an important role in the surface energy balance at the soil-atmosphere interface. It is a key variable influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Due to their large spatial variability, estimation of spatial patterns of soil moisture from field measurements is difficult and not feasible for large scale analyses. In the past decades, Synthetic Aperture Radar (SAR) remote sensing has proven its potential to quantitatively estimate near surface soil moisture at high spatial resolutions. Since the knowledge of the basic SAR concepts is important to understand the impact of different natural terrain features on the quantitative estimation of soil moisture and other surface parameters, the fundamental principles of synthetic aperture radar imaging are discussed. Also the two spaceborne SAR missions whose data was used in this study, the ENVISAT of the European Space Agency (ESA) and the ALOS of the Japanese Aerospace Exploration Agency (JAXA), are introduced. Subsequently, the two essential surface properties in the field of radar remote sensing, surface soil moisture and surface roughness are defined, and the established methods of their measurement are described. The in situ data used in this study, as well as the research area, the River Rur catchment, with the individual test sites where the data was collected between 2007 and 2010, are specified. On this basis, the important scattering theories in radar polarimetry are discussed and their application is demonstrated using novel polarimetric ALOS/PALSAR data. A critical review of different classical approaches to invert soil moisture from SAR imaging is provided. Five prevalent models have been chosen with the aim to provide an overview of the evolution of ideas and techniques in the field of soil moisture estimation from active microwave data. As the core of this work, a new semi-empirical model for the inversion of surface soil moisture from dual polarimetric L-band SAR data is introduced. This novel approach utilizes advanced polarimetric decomposition techniques to correct for the disturbing effects from surface roughness and vegetation on the soil moisture retrieval without the use of a priori knowledge. The land use specific algorithms for bare soil, grassland, sugar beet, and winter wheat allow quantitative estimations with accuracies in the order of 4 Vol.-%. Application of remotely sensed soil moisture patterns is demonstrated on the basis of mesoscale SAR data by investigating the variability of soil moisture patterns at different spatial scales ranging from field scale to catchment scale. The results show that the variability of surface soil moisture decreases with increasing wetness states at all scales. Finally, the conclusions from this dissertational research are summarized and future perspectives on how to extend the proposed model by means of improved ground based measurements and upcoming advances in sensor technology are discussed. The results obtained in this thesis lead to the conclusion that state-of-the-art spaceborne dual polarimetric L-band SAR systems are not only suitable to accurately retrieve surface soil moisture contents of bare as well as of vegetated agricultural fields and grassland, but for the first time also allow investigating within-field spatial heterogeneities from space

Monitoring Soil Moisture and Freeze/Thaw State Using C-band Imaging Radar

Soil moisture is an important state variable in many hydrological and meteorological applications. This thesis explores the use of the C-band synthetic aperture radar (SAR) parameters to monitor soil moisture and freeze/thaw state in a cold-season hydrologic environment. The circular-linear compact polarimetric (CP) configuration is considered as a possible alternative of the quad polarimetric (QP) system because it acquires images with wider swath and reduced complexity, cost and energy requirement of the radar system while maintaining the information content of the acquired imagery. In this study, 15 RADARSAT-2 QP images were acquired from October 2013 to June 2014 and CP images were simulated from each RADARSAT-2 QP imagery acquired. Field measurements of soil properties were collected along with the radar imagery acquisitions. The backscattering coefficients in all polarizations were able to discriminate frozen and unfrozen soils. But their correlations with soil moisture content were weak if examining frozen or unfrozen soils separately. The Oh et al. (1992) model was implemented in this study to compare with acquired RADARSAT-2 data. A good agreement was found between the linear polarimetric backscattering coefficients simulated by the Oh model and the RADARSAT-2 data, indicating that the study site even with 10 cm tall standing hay was consistent with a bare soil site at C-band and the Oh model can be applied to frozen soils. With respect to CP parameters, the first and fourth Stokes parameters and m-δ surface and volume scattering components can detect soil freeze/thaw state and have potential for frozen/unfrozen soils mapping. The influence of vegetation on selected CP parameters was also evident in this study. Results demonstrated the utility of C-band radar in detecting soil freeze/thaw state rather than monitoring the changes of soil moisture content. More image acquisitions during the freezing and thawing periods, continuous field measurements of soil moisture and state, and ground measurements collected over wider study area can help further develop understanding of the CP parameters and facilitate future use of the CP mode. The contribution of this thesis is to provide better understanding of the CP parameters at a specific site and to demonstrate that CP parameters can replicate QP SAR variables to detect surface soil conditions

Introduction to radar scattering application in remote sensing and diagnostics: Review

The manuscript reviews the current literature on scattering applications of RADAR (Radio Detecting And Ranging) in remote sensing and diagnostics. This paper gives prime features for a variety of RADAR applications ranging from forest and climate monitoring to weather forecast, sea status, planetary information, and mapping of natural disasters such as the ones caused by earthquakes. Both the fundamental parameters involved in scattering mechanisms of RADAR applications and the factors affecting RADAR performances are also discusse

Electromagnetic modeling for SAR polarimetry and interferometry

Investigation of the globe remotely from hundreds of kilometers altitude, and fast growing of environmental and civil problems, triggered the necessity of development of new and more advanced techniques. Electromagnetic modeling of polarimetry and interferometry has always been a key driver in remote sensing research, ever since of the First pioneering sensors were launched. Polarimetric and interferometric SAR (Synthetic Aperture Radar) surveillance and mapping of the Earth surface has been attracting lots of interest since 1970s. This thesis covers two SAR's main techniques: (1) space-borne Interferometric Synthetic Aperture Radar (InSAR), which has been used to measure the Earth's surface deformation widely, and (2) SAR Polarimetry, which has been used to retrieve soil and vegetation physical parameters in wide areas. Time-series InSAR methodologies such as PSI (Permanent Scatterer Interferometry) are designed to estimate the temporal characteristics of the Earth's deformation rates from multiple InSAR images acquired over time. These techniques also enable us to overcome the limitations that conventional InSAR suffer, with a very high accuracy and precision. In this thesis, InSAR time-series analysis and modeling basis, as well as a case study in the Campania region (Italy), have been addressed. The Campania region is characterized by intense urbanization, active volcanoes, complicated fault systems, landslides, subsidence, and hydrological instability; therefore, the stability of public transportation structures is highly concerned. Here Differential Interferometric Synthetic Aperture Radar (DInSAR), and PSI techniques have been applied to a stack of 25 X-band radar images of Cosmo-SkyMed (CSK) satellites collected over an area in Campania (Italy), in order to monitor the railways' stability. The study area was already under investigation with older, low-resolution sensors like ERS1&2 and ENVISAT-ASAR before, but the number of obtained persistent scatterers (PSs) was too limited to get useful results. With regard to SAR polarimetry, in this thesis a fully polarimetirc SAR simulator has been presented, which is based on the use of sound direct electromagnetic models and it is able to provide as output the simulated raw data of all the three polarization channels in such a way as to obtain the correct covariance or coherence matrixes on the final focused polarimetic radar images. A fast Fourier-domain approach is used for the generation of raw signals. Presentation of theory is supplemented by meaningful experimental results, including a comparison of simulations with real polarimetric scattering data