MONITORING OF IONOSPHERIC SCINTILLATION PHENOMENA USING SYNTHETIC APERTURE RADAR (SAR)

The applications of synthetic aperture radars (SAR) have increased manifold in the past decade, which includes numerous Earth observation applications such as agriculture, forestry, disaster monitoring cryospheric- and atmospheric- studies. Among them, the potential of SAR for ionospheric studies is gaining importance. The susceptibility of SAR to space weather dynamics, and ionosphere in particular, comes at low frequencies of L- and P-bands. This paper discusses one such scintillation event that was observed by L-band Advanced Land Observation Satellite (ALOS)-2 Phased Array L-type SAR (PALSAR) over southern India on March 23, 2015. The sensors also acquired data sets on four other days on which the ionosphere was quiet. Ionospheric parameter measurements of total electron content (TEC) and amplitude scintillation (S4) index from ground-based Global Navigation Satellite System (GNSS) receiver at Tirunelveli was used to establish the ionospheric conditions on the days of SAR acquisition as well as to corroborate the S4 estimated from SAR. Multi-temporal ALOS-2 data sets were utilized to calculate S4 from two separate methods and the results have a good agreement with GNSS receiver measurements. This highlights the potential of SAR as an alternate technique of monitoring ionospheric scintillations that can be utilized as complementary to the highly accurate and dedicated measurements from the GNSS networks

Ionospheric correction of interferometric SAR data with application to the cryospheric sciences

Thesis (Ph.D.) University of Alaska Fairbanks, 2018The ionosphere has been identified as an important error source for spaceborne Synthetic Aperture Radar (SAR) data and SAR Interferometry (InSAR), especially for low frequency SAR missions, operating, e.g., at L-band or P-band. Developing effective algorithms for the correction of ionospheric effects is still a developing and active topic of remote sensing research. The focus of this thesis is to develop robust and accurate techniques for ionospheric correction of SAR and InSAR data and evaluate the benefit of these techniques for cryospheric research fields such as glacier ice velocity tracking and permafrost deformation monitoring. As both topics are mostly concerned with high latitude areas where the ionosphere is often active and characterized by turbulence, ionospheric correction is particularly relevant for these applications. After an introduction to the research topic in Chapter 1, Chapter 2 will discuss open issues in ionospheric correction including processing issues related to baseline-induced spectrum shifts. The effect of large baseline on split spectrum InSAR technique has been thoroughly evaluated and effective solutions for compensating this effect are proposed. In addition, a multiple sub-band approach is proposed for increasing the algorithm robustness and accuracy. Selected case studies are shown with the purpose of demonstrating the performance of the developed algorithm. In Chapter 3, the developed ionospheric correction technology is applied to optimize InSAR-based ice velocity measurements over the big ice sheets in Greenland and the Antarctic. Selected case studies are presented to demonstrate and validate the effectiveness of the proposed correction algorithms for ice velocity applications. It is shown that the ionosphere signal can be larger than the actual glacier motion signal in the interior of Greenland and Antarctic, emphasizing the necessity for operational ionospheric correction. The case studies also show that the accuracy of ice velocity estimates was significantly improved once the developed ionospheric correction techniques were integrated into the data processing flow. We demonstrate that the proposed ionosphere correction outperforms the traditionally-used approaches such as the averaging of multi-temporal data and the removal of obviously affected data sets. For instance, it is shown that about one hundred multi-temporal ice velocity estimates would need to be averaged to achieve the estimation accuracy of a single ionosphere-corrected measurement. In Chapter 4, we evaluate the necessity and benefit of ionospheric-correction for L-band InSAR-based permafrost research. In permafrost zones, InSAR-based surface deformation measurements are used together with geophysical models to estimate permafrost parameters such as active layer thickness, soil ice content, and permafrost degradation. Accurate error correction is needed to avoid biases in the estimated parameters and their co-variance properties. Through statistical analyses of a large number of L-band InSAR data sets over Alaska, we show that ionospheric signal distortions, at different levels of magnitude, are present in almost every InSAR dataset acquired in permafrost-affected regions. We analyze the ionospheric correction performance that can be achieved in permafrost zones by statistically analyzing correction results for large number of InSAR data. We also investigate the impact of ionospheric correction on the performance of the two main InSAR approaches that are used in permafrost zones: (1) we show the importance of ionospheric correction for permafrost deformation estimation from discrete InSAR observations; (2) we demonstrate that ionospheric correction leads to significant improvements in the accuracy of time-series InSAR-based permafrost products. Chapter 5 summarizes the work conducted in this dissertation and proposes next steps in this field of research

Measuring and modelling the impact of the ionosphere on space based synthetic aperture radars

Synthetic aperture radar (SAR) is a technique widely used in applications that require all-weather imaging. The ionosphere affects the operation of these radars, with those operating at L-band (1-2 GHz) and below at risk of being seriously compromised by the ionosphere. A method of using Global Positioning System (GPS) data to synthesize the impact of the ionosphere on SAR systems has been presented. The technique was used to assess the viability of using a signal phase correction derived from a reference location in a SAR image to correct ionospheric effects across the image. A dataset of SAR images and GPS measurements collected simultaneously on Ascension Island were used to test two techniques for deriving ionospheric strength of turbulence (C$_k$L) from SAR images – one using measurements of trihedral corner reflectors (CR) and the other measurements of natural clutter. The CR C$_k$L values showed a correlation of 0.69 with GPS estimates of C$_k$L, whilst the clutter measurements showed a correlation of up to 0.91 with the CR values. Finally, a study of using the effects of intensity scintillation on SAR images to measure the S$_4$ index was performed. The study was not able to reproduce previous results, but produced significant practical conclusions

The SAR Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation

This Synthetic Aperture Radar (SAR) handbook of applied methods for forest monitoring and biomass estimation has been developed by SERVIR in collaboration with SilvaCarbon to address pressing needs in the development of operational forest monitoring services. Despite the existence of SAR technology with all-weather capability for over 30 years, the applied use of this technology for operational purposes has proven difficult. This handbook seeks to provide understandable, easy-to-assimilate technical material to remote sensing specialists that may not have expertise on SAR but are interested in leveraging SAR technology in the forestry sector