Exploiting the Sentinel-3 tandem phase dataset and azimuth oversampling to better characterize the sensitivity of SAR altimeter sea surface height to long ocean waves

Being the very first SAR mode altimeter tandem phase, the Sentinel-3 A/B tandem phase has provided an unprecedented opportunity to better characterize the sensitivity of SAR altimetry retrievals to high-frequency processes, such as long ocean waves. In this paper, we show that for some sea-state conditions, that are still to be precisely characterized, long ocean waves are responsible for high-frequency (spatial and temporal) coherent Sea Level Anomaly (SLA) signals. It is found that the peak wavelength corresponds to the dominant swell wavelength. Furthermore, the short time lag between S3-A and S3-B acquisitions allows performing cross-spectral analyses that reveal phase shifts consistent with waves travelling according to the wave dispersion relation. It is also demonstrated that the classical 20 Hz sampling frequency is insufficient to properly sample most swell-induced SLA signals and that aliasing can generate errors over the entire frequency spectrum, including at long wavelengths. These results advocate for the use of azimuth oversampling (40 Hz or 80 Hz). Low-pass filtering should be applied prior to any down-sampling to 20 Hz, in order to prevent long-wavelength errors induced by spectral leakage.     

Exploring the potential of Sentinel-3 delay Doppler altimetry for enhanced detection of coastal currents along the Northwest Atlantic shelf

In this study, we evaluate Sentinel-3A satellite synthetic aperture radar (SAR) altimeter observations along the Northwest Atlantic coast, spanning the Nova Scotian Shelf, Gulf of Maine, and Mid-Atlantic Bight. Comparisons are made of altimeter sea surface height (SSH) measurements from three different altimeter data processing approaches: fully-focused synthetic aperture radar (FFSAR), un-focused SAR (UFSAR), and conventional low-resolution mode (LRM). Results show that fully-focused SAR data always outperform LRM data and are comparable or slightly better than the nominal un-focused SAR product. SSH measurement noise in both SAR-mode datasets is significantly reduced compared to LRM. FFSAR SSH 20-Hz noise levels, derived from 80-Hz FFSAR data, are lower than 20-Hz UFSAR SSH with 25% noise reduction offshore of 5 km, and 55–70% within 5 km of the coast. The offshore noise improvement is most likely due to the higher native along-track data posting rate (80 Hz for FFSAR, and 20 Hz for UFSAR), while the large coastal improvement indicates an apparent FFSAR data processing advantage approaching the coastlines. FFSAR-derived geostrophic ocean current estimates exhibit the lowest bias and noise when compared to in situ buoy-measured currents. Assessment at short spatial scales of 5–20 km reveals that Sentinel-3A SAR data provide sharper and more realistic measurement of small-scale sea surface slopes associated with expected nearshore coastal currents and small-scale gyre features that are much less well resolved in conventional altimetric LRM data.     

Preliminary gravity recovery from CryoSat-2 data in the Baffin Bay

A number of geophysical phenomenons in the open ocean are still unresolved by conventional altimetry, but could be resolved through the potential improvements offered by Synthetic Aperture Radar (SAR), also called Delay-Doppler, altimetry. The SAR altimeter offers the following benefits with respect to conventional satellite altimetry: factor of 20 improvements in the along-track resolution, the along-track footprint length which does not vary with wave height (sea state), and improved precision in sea surface height measurements or sea surface slope measurements.     

High-performance altimeter Doppler processing for measuring sea level height under varying sea state conditions

This paper describes an innovative method for processing nadir altimeter data acquired in Synthetic Aperture Radar (SAR) mode, enhancing the system performances over open ocean. Similarly to the current SAR data processing scheme, the so-called LR-RMC (Low Resolution with Range Migration Correction) method, originally designed by Phalippou and Demeester (2011), includes Doppler beam forming, Doppler shift correction and range correction. In LR-RMC, however, an alternative and less complex averaging (stacking) operation is used so that all the Doppler beams produced in a radar cycle (4 bursts of 64 beams for the open-burst Sentinel-3-mode altimeter) are incoherently combined to form a multi-beam echo. In that manner, contrarily to the narrow-band SAR technique, the LR-RMC processing enlarges the effective footprint to average out the effects of surface waves and particularly those from small sub-mesoscale structures (<1 km) that are known to impact SAR-mode performances. On the other hand, the number of averaged beams is as high as in current SAR-mode processing, thus providing a noise reduction at least equally good. The LR-RMC method has the added benefit of reducing the incoherent integration time with respect to the SAR-mode processing (50 ms compared to 2.5 s) limiting possible surface movement effects. By processing one year of Sentinel-3A SRAL SAR-mode data using the LR-RMC method, it is shown that the swell impact on the SAR altimeter performances is totally removed and that an improvement of 10–50% is obtained in the measurement noise of the sea surface height and significant wave height with respect to SAR mode. Additionally, observational capabilities over the middle scales are enhanced potentially allowing the ocean mesoscale features to be retrieved and observations assimilated more usefully in ocean models.     

Mapping mean lake surface from satellite altimetry and GPS kinematic surveys

Lake water height is a key variable in water cycle and climate change studies, which is achievable using satellite altimetry constellation. A method based on data processing of altimetry from several satellites has been developed to interpolate mean lake surface (MLS) over a set of 22 big lakes distributed on the Earth. It has been applied on nadir radar altimeters in Low Resolution Mode (LRM: Jason-3, Saral/AltiKa, CryoSat-2) in Synthetic Aperture Radar (SAR) mode (Sentinel-3A), and in SAR interferometric (SARin) mode (CryoSat-2), and on laser altimetry (ICESat). Validation of the method has been performed using a set of kinematic GPS height profiles from 18 field campaigns over the lake Issykkul, by comparison of altimetry’s height at crossover points for the other lakes and using the laser altimetry on ICESat-2 mission. The precision reached ranges from 3 to 7 cm RMS (Root Mean Square) depending on the lakes. Currently, lake water level inferred from satellite altimetry is provided with respect to an ellipsoid. Ellipsoidal heights are converted into orthométric heights using geoid models interpolated along the satellite tracks. These global geoid models were inferred from geodetic satellite missions coupled with absolute and regional anomaly gravity data sets spread over the Earth. However, the spatial resolution of the current geoid models does not allow capturing short wavelength undulations that may reach decimeters in mountaineering regions or for rift lakes (Baikal, Issykkul, Malawi, Tanganika). We interpolate in this work the geoid height anomalies with three recent geoid models, the EGM2008, XGM2016 and EIGEN-6C4d, and compare them with the Mean Surface of 22 lakes calculated using satellite altimetry. Assuming that MLS mimics the local undulations of the geoid, our study shows that over a large set of lakes (in East Africa, Andean mountain and Central Asia), short wavelength undulations of the geoid in poorly sampled areas can be derived using satellite altimetry. The models used in this study present very similar geographical patterns when compared to MLS. The precision of the models largely depends on the location of the lakes and is about 18 cm, in average over the Earth. MLS can serve as a validation dataset for any future geoid model. It will also be useful for validation of the future mission SWOT (Surface Water and Ocean Topography) which will measure and map water heights over the lakes with a high horizontal resolution of 250 by 250 m.     

Detection of Envisat RA2/ICE-1 retracked radar altimetry bias over the Amazon basin rivers using GPS

Altimetry is now routinely used to monitor stage variations over rivers, including in the Amazon basin. It is desirable for hydrologic studies to be able to combine altimetry from different satellite missions with other hydrogeodesy datasets such as leveled gauges and watershed topography. One requirement is to accurately determine altimetry bias, which could be different for river studies from the altimetry calibrated for deep ocean or lake applications. In this study, we estimate the bias in the Envisat ranges derived from the ICE-1 waveform retracking, which are nowadays widely used in hydrologic applications. As a reference, we use an extensive dataset of altitudes of gauge zeros measured by GPS collocated at the gauges. The thirty-nine gauges are spread along the major tributaries of the Amazon basin. The methodology consists in jointly modeling the vertical bias and spatial and temporal slope variations between altimetry series located upstream and downstream of each gauge. The resulting bias of the Envisat ICE-1 retracked altimetry over rivers is 1.044 ± 0.212 m, revealing a significant departure from other Envisat calibrations or from the Jason-2 ICE-1 calibration.     

Conditional sea surface statistics and their impact on geophysical sea surface parameters retrieved from SAR altimetry signals

In this study we present an analytical formulation of synthetic-aperture radar (SAR) altimetry signals including narrow banded nonlinear wave fields and conditional statistics between wave elevation displacements, horizontal wave slopes and vertical wave particle velocities. Considering the wave elevation displacements coskewness with respect to horizontal slopes leads to an analytical formulation of the electromagnetic bias within a SAR-mode altimeter stack. This formulation can be either parametrized by the significant wave height (SWH) and mean wave steepness, or in terms of the variance of vertical wave velocities. The effect of conditional vertical wave particle velocity variances with respect to the observed horizontal wave slopes close to nadir incidence angles leads to an effective reduction of the azimuth blurring of SAR-mode stacks. We present here a formulation of this effect by examining JONSWAP ocean wave spectra. In most cases this effect reduces the azimuth blurring by 10% to 30%. Additionally we investigate the effect of a nonlinear wave elevation displacement probability density function (PDF) on estimated geophysical parameters. We were able to show that including an elevation displacement skewness of 0.13 improves significantly the SWH consistency between altimetry and ECMWF Reanalysis v5 ERA5 results.All of these effects are validated with respect to ERA5 model data in the North East Atlantic region and in situ data located in the German Bight and Baltic Sea.The developed model can be used in both SAR and conventional altimetry retrackers.     

Design of an end-to-end demonstration mission of a Formation-Flying Synthetic Aperture Radar (FF-SAR) based on microsatellites

The paper focuses on space system design aspects related to an end-to-end demonstration mission, aiming at showing the feasibility of a Formation Flying Synthetic Aperture Radar (FF-SAR) with microsatellite class platforms (~100 kg). Trajectory design approaches that can fulfil payload requirements are addressed to enable selected FF-SAR applications. The exploitation of these applications relies on suitable combinations of FF-SAR techniques like Signal-to-Noise Ratio (SNR) enhancement, High-Resolution Wide Swath (HRWS) SAR imaging, and Coherence Resolution Enhancement (CRE). In this framework, a cluster of 3 micro-satellites, working in X-band, flying in a Low Earth Orbit (LEO) close-formation, has been designed as a candidate end-to-end system demonstration mission. One satellite embarks a Transmitting-Receiving (Tx/Rx) radar, i.e. it is a monostatic SAR. The other two satellites are Receiving-only platforms. Critical design aspects related to spacecraft subsystems and formation-flying analysis are addressed to confirm the technical feasibility of the spaceborne distributed system implementing the FF-SAR principle.     

The X-TRACK/ALES multi-mission processing system: New advances in altimetry towards the coast

In the context of the ESA Climate Change Initiative project, a new coastal sea level altimetry product has been developed in order to support advances in coastal sea level variability studies. Measurements from Jason-1,2&3 missions have been retracked with the Adaptive Leading Edge Subwaveform (ALES) Retracker and then ingested in the X-TRACK software with the best possible set of altimetry corrections. These two coastal altimetry processing approaches, previously successfully validated and applied to coastal sea level research, are combined here for the first time in order to derive a 16-year-long (June 2002 to May 2018), high-resolution (20-Hz), along-track sea level dataset in six regions: Northeast Atlantic, Mediterranean Sea, West Africa, North Indian Ocean, Southeast Asia and Australia. The study demonstrates that this new coastal sea level product called X-TRACK/ALES is able to extend the spatial coverage of sea level altimetry data ~3.5 km in the land direction, when compared to the X-TRACK 1-Hz dataset. We also observe a large improvement in coastal sea level data availability from Jason-1 to Jason-3, with data at 3.6 km, 1.9 km and 0.9 km to the coast on average, for Jason-1, Jason-2 and Jason-3, respectively. When combining measurements from Jason-1 to Jason-3, we reach a distance of 1.2–4 km to the coast. When compared to tide gauge data, the accuracy of the new altimetry near-shore sea level estimations also improves. In terms of correlations with a large set of independent tide gauge observations selected in the six regions, we obtain an average value of 0.77. We also show that it is now possible to derive from the X-TRACK/ALES product an estimation of the ocean current variability up to 5 km to the coast. This new altimetry dataset, freely available, will provide a valuable contribution of altimetry in coastal marine research community.     

Analysis of coastal altimetry in the Mexican Caribbean

A reprocessing of sea-level anomalies (SLA) resulting from X-TRACK coastal altimetry was carried out for the ENVISAT (2002–2010) and TOPEX/POSEIDON-Jason (1992–2019) satellite missions in the coastal area of the Mexican Caribbean. This consisted of applying a tidal correction to coastal altimetry sea level observations. Harmonic analysis of five coastal tide gauge records was performed to estimate the most important tidal components of the area, resulting on M2, N2, O1, S2, K1, MF, and MM. The tidal signal was reconstructed with the seven tidal components using the TPXO9 model. The SLA signals corrected with the seven tidal components were validated with in situ data from coastal tide gauges. The validation showed that the TPXO9 tidal barotropic model (1/30° grid) used to reconstruct the tidal signal with the seven representative tidal components performed better than the FES2012 global model (1/16° grid) that uses 33 tidal components. The reprocessed SLAs showed clear seasonality with significant signals at 4, 6, and 12 months, with the annual signal being the dominant one. In the Mexican Caribbean coastal zone, oceanographic processes with different scales (from coastal to mesoscale) converge, showing their complexity in the different SLA signals observed. The aim of this work is to contribute to the analysis of coastal altimetry data and understanding the sea level variations in the Mexican Caribbean. This work is the first step in the implementation of methodologies that take advantage of coastal satellite altimetry in the Caribbean Sea.     

基于半无码的P(Y)码自相关GNSS-R海面测高方法

针对传统GPS C/A码延迟测高方法测高精度低和互相关测高方法时延波形信噪比低的问题,研究了基于半无码的P（Y）码自相关海面测高方法。首先,通过理论测高精度模型,对比分析了C/A码和P（Y）码的测高精度;然后,描述了L1、L2双频反射信号基于半无码的P（Y）码自相关处理架构,并论述了测高模型和L1、L2双频电离层时延误差修正方法;最后,利用模拟的L1、L2反射信号对比分析了基于半无码的P（Y）码自相关、C/A码自相关以及信号互相关方法的海面测高精度。结果表明:相比于C/A码自相关和信号互相关测高精度,基于半无码的P（Y）码自相关的测高精度分别提高了3.97倍和1.47倍。      

一种基于北斗三号系统的GNSS-R海面干涉测高技术

GNSS-R干涉测高技术可用于中尺度海面高度观测，具有空间分辨率高、测量精度高等优势。与传统的GNSS-R本地码测高技术相比，GNSS-R干涉测高技术可以有效提升高度测量精度。虽然GNSS-R干涉测高技术已有一些研究，但是基于北斗三号的干涉测高应用还很少。本文根据GNSS-R干涉测高技术优势，针对北斗三号系统在干涉测高技术上的应用，研发了支持北斗三号的GNSS-R干涉测高接收机并描述了整体架构及实现。利用所研发的接收机进行水面干涉测高试验，首次获取了北斗三号B1和B2干涉测高波形，与传统GPS L1和北斗B1本地码测高波形进行对比。对两种方法计算出的水面高度进行对比，结果显示北斗三号干涉测高精度明显优于GPS L1和北斗B1传统本地码测高精度。      

Impact of rain on wave retrieval from Sentinel-1 synthetic aperture radar images in tropical cyclones

The main objective of our work was to investigate the impact of rain on wave observations from C-band (~5.3 GHz) synthetic aperture radar (SAR) in tropical cyclones. In this study, 10 Sentinel-1 SAR images were available from the Satellite Hurricane Observation Campaign, which were taken under cyclonic conditions during the 2016 hurricane season. The third-generation wave model, known as Simulating WAves Nearshore (SWAN) (version 41.31), was used to simulate the wave fields corresponding to these Sentinel-1 SAR images. In addition, rainfall data from the Tropical Rainfall Measuring Mission satellite passing over the spatial coverage of the Sentinel-1 SAR images were collected. The simulated results were validated against significant wave heights (SWHs) from the Jason-2 altimeter and European Centre for Medium-Range Weather Forecasts data, revealing a root mean square error (RMSE) of ~0.5 m with a 0.25 scatter index. Winds retrieved from the VH-polarized Sentinel-1 SAR images using the Sentinel-1 Extra Wide-swath Mode Wind Speed Retrieval Model after Noise Removal were taken as prior information for wave retrieval. It was discovered that rain did indeed affect the SAR wave retrieval, as evidenced by the 3.21-m RMSE of SWHs between the SAR images and the SWAN model, which was obtained for the ~1000 match-ups with raindrops. The raindrops dampened the wave retrieval when the rain rate was < ~5 mm/hr; however, they enhanced wave retrieval for higher rain rates. It was also found that the portion of the rain-induced ring wave with a wave number > 0.05 rad/m (~125 m wavelength) was clearly observed in the SAR-derived wave spectra.     

Calibration of Envisat radar altimeter over Lake Issykkul

This study presents the results of calibration/validation (C/V) of Envisat satellite radar altimeter over Lake Issykkul located in Kyrgyzstan, which was chosen as a dedicated radar altimetry C/V site in 2004. The objectives are to estimate the absolute altimeter bias of Envisat and its orbit based on cross-over analysis with TOPEX/Poseidon (T/P), Jason-1 and Jason-2 over the ocean. We have used a new method of GPS data processing in a kinematic mode, developed at the Groupe de Recherche de Geodesie Spatiale (GRGS), which allows us to calculate the position of the GPS antenna without needing a GPS reference station. The C/V is conducted using various equipments: a local GPS network, a moving GPS antenna along the satellites tracks over Lake Issykkul, In Situ level gauges and weather stations. The absolute bias obtained for Envisat from field campaigns conducted in 2009 and 2010 is between 62.1 and 63.4 ± 3.7 cm, using the Ice-1 retracking algorithm, and between 46.9 and 51.2 cm with the ocean retracking algorithm. These results differ by about 10 cm from previous studies, principally due to improvement of the C/V procedure. Apart from the new algorithm for GPS data processing and the orbit error reduction, more attention has been paid to the GPS antenna height calculation, and we have reduced the errors induced by seiche over Lake Issykkul. This has been assured using cruise data along the Envisat satellite track at the exact date of the pass of the satellite for the two campaigns. The calculation of the Envisat radar altimeter bias with respect to the GPS levelling is essential to allow the continuity of multi-mission data on the same orbit, with the expected launch of SARAL/Altika mission in 2012. Implications for hydrology in particular, will be to produce long term homogeneous and reliable time series of lake levels worldwide.     

Influence of time variable geopotential models on precise orbits of altimetry satellites,global and regional mean sea level trends

During the last decade a significant progress has been reached in the investigation of the gravity field of the Earth. Besides static, also time variable geopotential models have been recently created. In this paper we investigate the impact of the recent time variable geopotential models on altimetry satellite orbits and such altimetry products based on these orbits, as global and regional mean sea level trends. We show that the modeling of time variable gravity improves the orbit solutions, at least for the GRACE period where time variable gravity is sufficiently accurately observed by this mission. Our analysis includes six geopotential models jointly developed by GFZ German Research Centre for Geosciences and Space Geodesy Research Group (CNES/GRGS) Toulouse: the stationary model EIGEN-GL04S, a stationary version of EIGEN-6S (EIGEN-6S_stat), a corrected version of EIGEN-6S and three enhanced versions of EIGEN-6S called EIGEN-6S2, EIGEN-6S2A and EIGEN-6S2B. By “stationary” we mean “containing periodic parameters such as annual and semi-annual variations, but no secular (drift) terms”. We computed precise orbits for the radar altimetry satellites ERS-1, ERS-2, TOPEX/Poseidon, and Envisat over 20 years between 1991 and 2011. The orbit, single-mission and multi-mission altimetry crossover analyses show that the time variable models EIGEN-6S_corrected, EIGEN-6S2 and its two precursors EIGEN-6S2A/B perform notably better than the stationary models for the GRACE period from 2003 onwards. Thus, using EIGEN-6S2 and EIGEN-6S2A/B we have got 3.6% smaller root mean square fits of satellite laser ranging observations for Envisat, as when using EIGEN-GL04S. However, for the pre-GRACE period 1991–2003, the stationary geopotential models EIGEN-GL04S and EIGEN-6S_stat as well as EIGEN-6S2 having no drift terms for degree 3–50 at this time interval perform superior compared to EIGEN-6S_correct and EIGEN-6S2A/B which contain drifts for this period. We found, that the time variable geopotential models have a low (0.1–0.2 mm/yr) impact on our results for the global mean sea level trend. However, we found strong East/West differences up to 3 mm/yr in the regional mean sea level trends when using orbits of all four satellites based on time variable and stationary geopotential models. We show that these differences are related to the relative drifts of the centers-of-origin between the orbit solutions based on the time variable and stationary geopotential models. From the results of our detailed study, we conclude that the final version of the time variable gravity field model EIGEN-6S2 performs best for the four satellites tested. This model provides the most reliable and mission-consistent sea level estimates for the whole time period from 1992 to 2010. This model is of maximum spherical harmonic degree and order 260 and contains time series for drifts as well as annual and semiannual variations of the spherical harmonic coefficients for degree 2–50.     

Validation of non-linear split window algorithm for land surface temperature estimation using Sentinel-3 satellite imagery: Case study; Tehran Province,Iran

In recent years, land surface temperature (LST) has become critical in environmental studies and earth science. Remote sensing technology enables spatiotemporal monitoring of this parameter on large scales. This parameter can be estimated by satellite images with at least one thermal band. Sentinel-3 SLSTR data provide LST products with a spatial resolution of 1 km. In this research, direct and indirect validation procedures were employed to evaluate the Sentinel-3 SLSTR LST products over the study area in different seasons from 2018 to 2019. The validation method was based on the absolute (direct) evaluation of this product with field data and comparison (indirect) evaluation with the MODIS LST product and the estimated LST using the non-linear split-window (NSW) algorithm. Also, two emissivity estimation methods, (1) NDVI thresholding method (NDVI-THM) and (2) classification-based emissivity method (CBEM), were used to estimate the LST using the NSW method according to the two thermal bands of Sentinel-3 images. Then, the accuracy of these methods in estimating LST was evaluated using field data and temporal changes of vegetation, which the NDVI-THM method generated better results. For indirect evaluation between the Sentinel-3 LST product, MODIS LST product, and LST estimated using NSW, four filters based on spatial and temporal separates between pairs of pixels and pixel quality were used to ensure the accuracy and consistency of the compared pairs of a pixel. In general, the accuracy results of the LST products of MODIS and Sentinel-3, and LST estimated using NSW showed a similar trend for LST changes during the seasons. With respect to the two absolute and comparative validations for the Sentinel-3 LST products, summer with the highest values of bias (?1.24 K), standard deviation (StDv = 2.66 K), and RMSE (2.43 K), and winter with the lowest ones (bias of 0.14 K, StDv of 1.13 K, and RMSE of 1.12 K) provided the worst and best results for the seasons in the period of 2018–2019, respectively. According to both absolute and comparative evaluation results, the Sentinel-3 SLSTR LST products provided reliable results for all seasons on a large temporal and spatial scale over our studied area.     

Sea state parameters retrieval from cross-polarization Gaofen-3 SAR data

Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) acquired in wave mode (WV) and quad-polarization stripmap (QPS) mode default operates in quad-polarization (vertical–vertical (VV), vertical-horizontal (VH), horizontal-horizontal (HH) and horizontal-vertical (HV)) modes. To date, more than GF-3 SAR vignettes following about 110 orbits acquired in WV and QPS mode have been recorded during the mission from April 2016 to December 2017. In the vignettes, ocean surface waves signatures, that are wave-look patterns, are visible in cross-polarization (basically VH). These vignettes are collocated with surface sea state parameters simulated from numerical WAVEWATCH-III (WW3) wave model using a 0.1° grid. There are 11,269 matchups available for studying the relation between sea state parameters and SAR-derived parameters in VH-polarization. A well-known empirical CWAVE model, herein renamed as CPCWAVE_GF3, is adopted for sea state parameter retrieval from GF-3 SAR vignettes with the SAR parameters in the cross-polarization channel. The method yielded a significant correlation coefficient (COR) of 0.79 for wave height (SWH) and 0.72 for second-order cross-zero mean wave period (MWP). Validation against 76 moored buoys resulted in a 0.49 m RMSE of SWH with a 0.21 m scatter index (SI) and validation against 71 moored buoys resulted in a 1.01 s RMSE of MWP with a 0.13 s SI. The comparison of SWH with 116 footprints from the altimeter of Jason-2 also shows a 0.46 m RMSE of SWH with a 0.19 m SI. Our work demonstrates the feasibility of wave retrieval from GF-3 SAR using cross-polarization channels parameters.     

An improved focusing method for geosynchronous SAR

More and more attention is paid to Geosynchronous Orbit (GEO) Synthetic Aperture Radar (SAR) in recent years due to its fine temporal resolution and large coverage, so that GEO SAR will play an important role in monitoring natural disasters, but its imaging is more difficult compared to lower Earth orbit (LEO) SAR because of the increase of orbit height. This paper mainly studies the coverage property and focusing method in GEO SAR. As is known to us, the coverage of a GEO SAR satellite can reach 1/3 of the whole Earth, and the revisiting time can reduce to 2 h, which will remarkably improve the capability in ocean applications, earth dynamics and natural hazards management and so on. Compared with the imaging in LEO SAR, a problem in GEO SAR is that the linear trajectory model can bring a big error due to the long synthetic aperture time, so that the classical imaging algorithms in LEO SAR cannot be directly applied in GEO SAR. Using the Norm method and Taylor expansion method, this paper gains an accurate slant range model, which can resolve the big error of the linear trajectory at perigee and collapse of the linear trajectory at apogee. Furthermore, this paper deduces a novel imaging algorithm for GEO SAR by means of series reversion, which realizes the focusing on large scene under the synthetic aperture time of 100 s. Finally, the simulation results at apogee and perigee prove the correction of the slant range model and imaging algorithm.     

Classification of multitemporal Sentinel-2 data for field-level monitoring of rice cropping practices in Taiwan

Cadastral information of rice fields is important for monitoring cropping practices in Taiwan due to official initiatives. Remote sensing based rice monitoring has been a challenge for years because the size of rice fields is small, and crop mapping requires information of crop phenology, relating to spatiotemporal resolution of satellite data. This study aims to develop an approach for mapping rice-growing areas at field level using multi-temporal Sentinel-2 data in Taiwan. The data were processed for 2018, following four main steps: (1) construct time-series Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI), (2) noise filtering of the time-series data using wavelet transform, (3) rice crop classification using information of crop phenology, and (4) parcel-based accuracy assessment of the mapping results. The parcel-to-parcel comparisons between mapping results and ground reference data indicated satisfactory results. These findings were confirmed by close agreement between satellite-derived rice area and government’s statistics. Although some factors, including mixed-pixel issues and cloud-cover effects, lowered the mapping accuracies of townships along the coastline, this study has demonstrated the efficacy of using multitemporal Sentinel-2 data to create a reliable database of rice-growing areas over a large and heterogeneous region. Such a quantitative information was important for updating rice crop maps and monitoring cropping practices.