Radar systems for the water resources mission, volume 2

The application of synthetic aperture radar (SAR) in monitoring and managing earth resources was examined. The function of spaceborne radar is to provide maps and map imagery to be used for earth resource and oceanographic applications. Spaceborne radar has the capability of mapping the entire United States regardless of inclement weather; however, the imagery must have a high degree of resolution to be meaningful. Attaining this resolution is possible with the SAR system. Imagery of the required quality must first meet mission parameters in the following areas: antenna patterns, azimuth and range ambiguities, coverage, and angle of incidence

Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping

Accurate mapping of forest aboveground biomass (AGB) is critical for better understanding the role of forests in the global carbon cycle. NASA's current GEDI and ICESat-2 missions as well as the upcoming NISAR mission will collect synergistic data with different coverage and sensitivity to AGB. In this study, we present a multi-sensor data fusion approach leveraging the strength of each mission to produce wall-to-wall AGB maps that are more accurate and spatially comprehensive than what is achievable with any one sensor alone. Specifically, we calibrate a regional L-band radar AGB model using the sparse, simulated spaceborne lidar AGB estimates. We assess our data fusion framework using simulations of GEDI, ICESat-2 and NISAR data from airborne laser scanning (ALS) and UAVSAR data acquired over the temperate high AGB forest and complex terrain in Sonoma County, California, USA. For ICESat-2 and GEDI missions, we simulate two years of data coverage and AGB at footprint level are estimated using realistic AGB models. We compare the performance of our fusion framework when different combinations of the sparse simulated GEDI and ICEsat-2 AGB estimates are used to calibrate our regional L-band AGB models. In addition, we test our framework at Sonoma using (a) 1-ha square grid cells and (b) similarly sized irregularly shaped objects. We demonstrate that the estimated mean AGB across Sonoma is more accurately estimated using our fusion framework than using GEDI or ICESat-2 mission data alone, either with a regular grid or with irregular segments as mapping units. This research highlights methodological opportunities for fusing new and upcoming active remote sensing data streams toward improved AGB mapping through data fusion.</p

An improved airborne multichannel SAR imaging method with motion compensation and range-variant channel mismatch correction

To obtain a high-resolution and wide-swath image, the azimuth multichannel technique has been widely used in synthetic aperture radar (SAR) systems to overcome the contradiction between the wide swath and high pulse repetition frequency. For a high image quality, channel mismatch correction is an essential step in the multichannel SAR data imaging. However, in the case of airborne multichannel SAR, motion errors will severely degrade the performance of channel mismatch correction. To deal with this problem, this article proposes an improved airborne multichannel SAR imaging method with motion compensation, and range-variant channel mismatch correction. First, motion errors are compensated based on resampling and phase compensation. Then, the time-delay and constant gain-phase errors between channels are estimated and corrected, followed by the range-variant phase error correction based on a novel range-down-sampling method, which reduces the influence of motion errors on the channel mismatch correction significantly. Finally, simulated and real data processing results are used to demonstrate the effectiveness of the proposed method

Time-variant TEC estimation with fully polarimetric GEO-SAR data

A time-variant total electron content (TEC) estimation method with fully polarimetric geosynchronous synthetic aperture radar (GEO-SAR) data is proposed based on inner aperture Faraday rotation angle estimation and an accurate TEC inversion model. With a long integration time and sensitivity to ionosphere effects, the fully polarimetric GEO-SAR data are utilised for estimation with high accuracy for both the time-variant TEC and the time interval. Superiority of the proposed method over conventional ionospheric sounding methods is verified by simulation results

Temporal Characteristics of Boreal Forest Radar Measurements

Radar observations of forests are sensitive to seasonal changes, meteorological variables and variations in soil and tree water content. These phenomena cause temporal variations in radar measurements, limiting the accuracy of tree height and biomass estimates using radar data. The temporal characteristics of radar measurements of forests, especially boreal forests, are not well understood. To fill this knowledge gap, a tower-based radar experiment was established for studying temporal variations in radar measurements of a boreal forest site in southern Sweden. The work in this thesis involves the design and implementation of the experiment and the analysis of data acquired. The instrument allowed radar signatures from the forest to be monitored over timescales ranging from less than a second to years. A purpose-built, 50 m high tower was equipped with 30 antennas for tomographic imaging at microwave frequencies of P-band (420-450 MHz), L-band (1240-1375 MHz) and C-band (5250-5570 MHz) for multiple polarisation combinations. Parallel measurements using a 20-port vector network analyser resulted in significantly shorter measurement times and better tomographic image quality than previous tower-based radars. A new method was developed for suppressing mutual antenna coupling without affecting the range resolution. Algorithms were developed for compensating for phase errors using an array radar and for correcting for pixel-variant impulse responses in tomographic images. Time series results showed large freeze/thaw backscatter variations due to freezing moisture in trees. P-band canopy backscatter variations of up to 10 dB occurred near instantaneously as the air temperature crossed 0⁰C, with ground backscatter responding over longer timescales. During nonfrozen conditions, the canopy backscatter was very stable with time. Evidence of backscatter variations due to tree water content were observed during hot summer periods only. A high vapour pressure deficit and strong winds increased the rate of transpiration fast enough to reduce the tree water content, which was visible as 0.5-2 dB backscatter drops during the day. Ground backscatter for cross-polarised observations increased during strong winds due to bending tree stems. Significant temporal decorrelation was only seen at P-band during freezing, thawing and strong winds. Suitable conditions for repeat-pass L-band interferometry were only seen during the summer. C-band temporal coherence was high over timescales of seconds and occasionally for several hours for night-time observations during the summer. Decorrelation coinciding with high transpiration rates was observed at L- and C-band, suggesting sensitivity to tree water dynamics.The observations from this experiment are important for understanding, modelling and mitigating temporal variations in radar observables in forest parameter estimation algorithms. The results also are also useful in the design of spaceborne synthetic aperture radar missions with interferometric and tomographic capabilities. The results motivate the implementation of single-pass interferometric synthetic aperture radars for forest applications at P-, L- and C-band

In-depth verification of Sentinel-1 and TerraSAR-X geolocation accuracy using the Australian Corner Reflector Array

This article shows how the array of corner reflectors (CRs) in Queensland, Australia, together with highly accurate geodetic synthetic aperture radar (SAR) techniques—also called imaging geodesy—can be used to measure the absolute and relative geometric fidelity of SAR missions. We describe, in detail, the end-to-end methodology and apply it to TerraSAR-X Stripmap (SM) and ScanSAR (SC) data and to Sentinel-1interferometric wide swath (IW) data. Geometric distortions within images that are caused by commonly used SAR processor approximations are explained, and we show how to correct them during postprocessing. Our results, supported by the analysis of 140 images across the different SAR modes and using the 40 reflectors of the array, confirm our methodology and achieve the limits predicted by theory for both Sentinel-1 and TerraSAR-X. After our corrections, the Sentinel-1 residual errors are 6 cm in range and 26 cm in azimuth, including all error sources. The findings are confirmed by the mutual independent processing carried out at University of Zurich (UZH) and German Aerospace Center (DLR). This represents an improve�ment of the geolocation accuracy by approximately a factor of four in range and a factor of two in azimuth compared with the standard Sentinel-1 products. The TerraSAR-X results are even better. The achieved geolocation accuracy now approaches that of the global navigation satellite system (GNSS)-based survey of the CRs positions, which highlights the potential of the end-to-end SAR methodology for imaging geodesy

Proceedings of the Third Spaceborne Imaging Radar Symposium

This publication contains summaries of the papers presented at the Third Spaceborne Imaging Radar Symposium held at the Jet Propulsion Laboratory (JPL), California Institute of Technology, in Pasadena, California, on 18-21 Jan. 1993. The purpose of the symposium was to present an overview of recent developments in the different scientific and technological fields related to spaceborne imaging radars and to present future international plans. This symposium is the third in a series of 'Spaceborne Imaging Radar' symposia held at JPL. The first symposium was held in Jan. 1983 and the second in 1986

Menetelmä Suomen vesistöjen jääfenologian määrittämiseen perustuen Sentinel-1 IW -moodin satelliittidatan yhdistämiseen tuulennopeusmittauksiin

The subject of this thesis was to find a method for determining ice phenology, or ice freeze-up and break-up dates, in Finnish waterbodies using Sentinel-1 C-band synthetic aperture radar images. The method should minimize manual steps to make it suitable for automatic processing. Though possibilities for detecting these changes are presented by optical earth observation satellites, optical images are often limited by cloud cover and darkness over autumn-winter months in the northern hemisphere. A great advantage of synthetic aperture radars as active sensors is their capability to penetrate through cloud cover and their independence of sunlight to operate. For specific advantages of the Sentinel-1 constellation, data is gathered with a very high acquisition rate near polar regions and all data is openly accessible since 2014. As this thesis is written, few studies have been conducted on observing inland waterbodies’ ice using Sentinel-1 IW mode radar images. To gather data from local wind conditions, lake water / ice / snow surface and temperatures in preparation for the thesis to determine and develop the final method, an automatic sensor station was built to a lake shoreline in southern Finland. The method developed and presented in this thesis is based on the similarity of Sentinel-1 IW mode radar images produced by water surface waves in similar wind conditions. By classifying radar images using similar wind conditions determined by weather station measurements, then estimating a numerical value for the difference between the radar images, waterbodies with open water will feature higher similarity with each other than frozen waterbodies with open water. The difference in similarity is used to determine the dates when changes in ice phenology, freeze-ups and ice break-ups, occur. Calculated by the method, lake freeze-up and break-up periods were determined to be accurate to within few satellite flyovers for select four lakes of different sizes in southern Finland which included the lake with the sensor station. For river portions few hundred meters wide and long, the method was found to distinguish changes in ice phenology for inland river portions better than portions near the sea discharge location. As the method could be used for estimating ice phenology for a variety of waterbodies in Finland not being routinely observed, it will offer possibilities in expansion of freeze-up and break-up models for such waterbodies. There are also potential applications for other watershed models, as seasonal ice can affect certain types of data used to calibrate these models.Tämän diplomityön aiheena on löytää ja kehittää menetelmä Suomen sisävesistöjen jäätymis- ja sulamisajankohtien määrittämiseen hyödyntämällä Sentinel-1 C-taajuuden tutkasatelliittien keräämää dataa. Optisia satelliittikuvia voidaan käyttää jääfenologian määrittämisessä, mutta ovat pohjoisessa rajoittuneita etenkin loppuvuoden jäätymisajankohtien määrittämisessä johtuen pilvisyydestä sekä pimeydestä. Synteettisen apertuurin tutka (engl. SAR) on aktiivinen sensori mikä kykenee toimimaan ilman auringonvaloa sekä pilvipeitteiden läpi. Jääfenologian määrittämisen osalta Sentinel-1 tutkasatelliitit hyötyvät lisäksi korkeasta ylilentotaajuudesta pohjoisilla alueilla sekä vuodesta 2014 asti kerätystä avoimesti saatavilla olevasta tutkakuva-arkistosta. Työn kirjoitushetkellä tutkimuksia Sentinel-1:n IW -moodin tutkahavaintojen hyödyntämisestä sisävesistöjen jääfenologian tulkinnassa ei ole juurikaan laadittu. Tästä syystä työn yhteydessä on rakennettu mittausasema Etelä-Suomessa sijaitsevan järven rantaan, jonka kautta erilaisten menetelmien kehittämiseen vaadittavaa tietoa on kerätty sekä vaihtoehtoja karsittu johtaen nykyiseen versioon menetelmästä. Tässä diplomityössä esitetty menetelmä hyödyntää vesistöjen aaltojen samankaltaisuutta kun tuuliolosuhteet ovat vesistön osalta liki identtiset. Kun tutkakuvassa sulaa vesistöä samoissa tuuliolosuhteissa verrataan sulaan vesistöön, ne eroavat vain vähän toisistaan ja vastaavasti jäätynyt vesistö eroaa tyypillisesti sulasta vesistöstä. Tuuliolosuhteiden samankaltaisuus määritetään hyödyntämällä Ilmatieteen laitoksen sääasemien tuulihavaintoja. Menetelmällä määritettiin jäätymis- ja sulamisajankohdat neljälle järvelle Etelä-Suomessa mukaanlukien sensoriaseman mittaama järvi. Vertaamalla ajankohtia saatavilla oleviin manuaalisiin havaintoihin, menetelmä määritti ajankohdat oikein muutaman satelliittin ylilennon tarkkuudella. Menetelmän soveltuvuus muutaman sadan metrin pituisille ja leveille jokiosuuksille todettiin olevan parempi sisämaassa kuin sijainnissa jossa joki laskee mereen. Menetelmän todettiin tarjoavan mahdollisuuksia sellaisten sisävesistöjen jääfenologian seurantaan joissa jäätymis- ja sulamisajankohtaa ei mitata, tarjoten dataa kyseisten vesistöjen jääolojen mallintamiseen. On myös mahdollista että vesistömalleissa voidaan hyödyntää tietoa jääfenologiasta, koska kausiluontoinen jää vaikuttaa muunmuassa näiden mallien kalibroinnissa käytettyihin mittauksiin

Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings