1,679 research outputs found
Exploitation of SAR data for measurement of ocean currents and wave velocities
Methods of extracting information on ocean currents and wave orbital velocities from SAR data by an analysis of the Doppler frequency content of the data are discussed. The theory and data analysis methods are discussed, and results are presented for both aircraft and satellite (SEASAT) data sets. A method of measuring the phase velocity of a gravity wave field is also described. This method uses the shift in position of the wave crests on two images generated from the same data set using two separate Doppler bands. Results of the current measurements are pesented for 11 aircraft data sets and 4 SEASAT data sets
State-of-the-art in studies of glacial isostatic adjustment for the British Isles: a literature review
Understanding the effects of glacial isostatic adjustment (GIA) of the British Isles is essential for the assessment of past and future sea-level trends. GIA has been extensively examined in the literature, employing different research methods and observational data types. Geological evidence from palaeo-shorelines and undisturbed sedimentary deposits has been used to reconstruct long-term relative sea-level change since the Last Glacial Maximum. This information derived from sea-level index points has been employed to inform empirical isobase models of the uplift in Scotland using trend surface and Gaussian trend surface analysis, as well as to calibrate more theory-driven GIA models that rely on Earth mantle rheology and ice sheet history. Furthermore, current short-term rates of GIA-induced crustal motion during the past few decades have been measured using different geodetic techniques, mainly continuous GPS (CGPS) and absolute gravimetry (AG). AG-measurements are generally employed to increase the accuracy of the CGPS estimates. Synthetic aperture radar interferometry (InSAR) looks promising as a relatively new technique to measure crustal uplift in the northern parts of Great Britain, where the GIA-induced vertical land deformation has its highest rate. This literature review provides an in-depth comparison and discussion of the development of these different research approaches
Application of remote sensors in coastal zone observations
A review of processes taking place along coastlines and their biological consideration led to the determination of the elements which are required in the study of coastal structures and which are needed for better utilization of the resources from the oceans. The processes considered include waves, currents, and their influence on the erosion of coastal structures. Biological considerations include coastal fisheries, estuaries, and tidal marshes. Various remote sensors were analyzed for the information which they can provide and sites were proposed where a general ocean-observation plan could be tested
Morphological Development of the German Wadden Sea from 1996 to 2009 Determined with the Waterline Method and SAR and Landsat Satellite Images
The Dutch, German, and Danish Wadden Sea contains some of the largest undisturbed tidal flats in the world of about 10,000 km2. The research areas covered in this thesis are the North Frisian, Neuwerk, and Cuxhaven regions of the German Wadden Sea. The goal of the thesis is to use the waterline method with SAR and optical images to derive topographic maps in order to analyze the morphological development of this valuable ecological system on large spatial and engineering time scales (90 km and 14 years). Compared to earlier applications, the method is improved with respect to the geocoding step and the data coverage of the complete tidal range. The results also allow analyzing smaller scale s developmental details, such as sandbars and estuaries. Topographical maps from 1996 to 1999, and 2004 to 2009 were generated. The largest morphological differences occurred between 2009 and 1996, also observed in the -2 m isobaths map. The Bed Elevation Range of the tidal flats includes all the elevation information from 1996 to 2009 in order to identify the maximum changes during the investigation period. It shows high morphodynamic regions are outer parts of the tidal flat, sandbars, and estuaries. Vertical nodal linear regression gives the direction of the morphological development (erosion or sedimentation). Our result shows that the rate of change is mostly between -0.1 to 0.1 m/yr. Extreme erosion rate reaches over -0.3 m/yr, while extreme sedimentation rate is up to 0.36 m/yr. The absolute amount of elevation change called turnover height has a growth rate of 8.2 mm/yr, indicating the growing morphodynamic activity over the investigation period. The net balance height of the whole investigation region shows an increasing trend of 6.8 mm/yr, demonstrating an overall sedimentation. According to large-scale analyses, the most dynamic areas are the sandbars. Tertiussand, D-Steert, Gelbsand, and Medemgrund/Medemsand are given detailed discussion in this thesis. The west side of the sandbars except for Medemgrund/Medemsand face the high wave and tidal energy arriving from the open North sea, and cause large erosion towards east, while Medemgrund/Medemsand located in the Elbe estuary show migration in the opposite direction. The three cross sections of Tertiussand, Gelbsand and Medemgrund all show clearly increasing elevation if comparing the average elevation over the years 1996-1999 and 2004-2009. Since the areas of Tertiussand and Gelbsand decreased, their increased elevation might relate to internal sediment redistribution. Medemgrund increasead in area, so its increased elevation could be compensated by the adjacent tidal flat Medemsand which has significant erosion towards the north and the sediment brought from Elbe River
Remote-Sensing Monitoring of Tide Propagation Through Coastal Wetlands
Tide propagation through coastal wetlands is a complex phenomenon affected by vegetation, channels, and tidal conditions. Generally, tidal flow is studied using stage (water level) observations, which provide good temporal resolution, but they are acquired in limited locations. Here, a remote-sensing technique, wetland InSAR (interferometric synthetic aperture radar), is used to detect tidal flow in vegetated coastal environments over broad spatial scales. The technique is applied to data sets acquired by three radar satellites over the western Everglades in south Florida. Interferometric analysis of the data shows that the greatest water-level changes occur along tidal channels, reflecting a high velocity gradient between fast horizontal flow in the channel and the slow flow propagation through the vegetation. The high-resolution observations indicate that the tidal flushing zone extends 2β3 km on both sides of tidal channels and can extend 3β4 km inland from the end of the channel. The InSAR observations can also serve as quantitative constraints for detailed coastal wetland flow models
Retrieval of Ocean Surface Currents and Winds Using Satellite SAR backscatter and Doppler frequency shift
Ocean surface winds and currents play an important role for weather, climate, marine life, ship navigation, oil spill drift and search and rescue. In-situ observations of the ocean are sparse and costly. Satellites provide a useful complement to these observations. Synthetic aperture radar (SAR) is particularly attractive due to its high spatial resolution and its capability to extract both sea surface winds and currents day and night and almost independent of weather.The work in this thesis involves processing of along-track interferometric SAR (ATI-SAR) data, analysis of the backscatter and Doppler frequency shift, and development of wind and current retrieval algorithms. Analysis of the Doppler frequency shift showed a systematic bias. A calibration method was proposed and implemented to correct for this bias. Doppler analysis also showed that the wave contribution to the SAR Doppler centroid often dominates over the current contribution. This wave contribution is estimated using existing theoretical and empirical Doppler models. For wind and current retrieval, two methods were developed and implemented.The first method, called the direct method, consists of retrieval of the wind speed from SAR backscatter using an empirical backscatter model. In order to retrieve the radial current, the retrieved wind speed is used to correct for the wave contribution. The current retrieval was assessed using two different (theoretical and empirical) Doppler models and wind inputs (model and SAR-derived). It was found that the results obtained by combining the Doppler empirical model with the SAR-derived wind speed were more consistent with ocean models.The second method, called Bayesian method, consists of blending the SAR observables (backscatter and Doppler shift) with an atmospheric and an oceanic model to retrieve the total wind and current vector fields. It was shown that this method yields more accurate estimates, i.e. reduces the models biases against in-situ measurements. Moreover, the method introduces small scale features, e.g. fronts and meandering, which are weakly resolved by the models.The correlation between the surface wind vectors and the SAR Doppler shift was demonstrated empirically using the Doppler shift estimated from over 300 TanDEM-X interferograms and ECMWF reanalysis wind vectors. Analysis of polarimetric data showed that theoretical models such as Bragg and composite surface models over-estimate the backscatter polarization ratio and Doppler shift polarization difference. A combination of a theoretical Doppler model and an empirical modulation transfer function was proposed. It was found that this model is more consistent with the analyzed data than the pure theoretical models.The results of this thesis will be useful for integrating SAR retrievals in ocean current products and assimilating SAR observables in the atmospheric, oceanic or coupled models. The results are also relevant for preparation studies of future satellite missions
μκ³μ΄ InSAR κΈ°λ²μ μ¬μ©νμ¬ λΉμ μμ ν΄μλ©΄ μμΉ κΈ°λ‘μ λ³΄μΈ μ‘°μκ΄μΈ‘μμ μμ§μ§λ°λ³μ νκ°
νμλ
Όλ¬Έ(λ°μ¬) -- μμΈλνκ΅λνμ : μμ°κ³Όνλν μ§κ΅¬νκ²½κ³ΌνλΆ, 2021.8. κΉλμ§.Global sea level rise has been a serious threat to the low-lying coasts and islands around the world. It is important to understand the global and regional sea level changes for preventing the coastal zones. Tide gauges are installed around the world, which directly measures the change in sea level relative to the local datum. Sea level in the past three decades has risen to 1.8 mm/year compared to the sea level rise in the 20th century (3.35 mm/year), estimated by the Intergovernmental Panel on Climate Change (IPCC). However, along with the contributors of sea level rise, vertical land motion (VLM) is indeed an essential component for understanding the regional sea level change; however, its contribution remains still unclear. The VLM is referred to as change in elevation of land at tide gauge due to the regional and local processes by both natural and anthropogenic activities can deteriorate the sea level records and lead to spurious sea level acceleration. Assessing the vertical land motion at tide gauges with the accuracy of sub-millimeters is essential to reconstruct the global and regional sea level rise. Previous studies attempt to observe the vertical land movements at sparse locations through Global Positioning System (GPS). However, the VLM observed from the sparse GPS network makes the estimation uncertain. In this study, an alternative approach is proposed in this study to directly measure the relative vertical land motion including spatial and temporal variations through Synthetic Aperture Radar (SAR) data by using time-series SAR interferometric (InSAR) techniques. This work presents a contribution enhancing the estimation of VLM rates with high spatial resolution over large area using time-series InSAR analysis.
First, the C-band Interferometric Wide-swath (IW) mode SAR data from the Sentinel-1 A/B satellite was used in this study to estimate the VLM rates of tide gauges. The Sentinel-1 A/B SAR data were obtained during the period between 2014/10 and 2020/12 (~ 6 years). Stanford Method for Persistent Scatterers β Persistent Scatterer Interferometry (StaMPS-PSI) time-series InSAR algorithm was initially applied to the case study: Pohang tide gauge in the Korean peninsula for monitoring the stability of tide gauge station and its VLM rates during 2014 ~ 2017. For the Pohang tide gauge site, SAR data acquired in both ascending and descending passes and derived the ground movement rates at tide gauge along the line-of-sight direction. The vertical movements from the collocated POHA GPS station were compared with the InSAR derived VLM rates for determining the correlation between the two methods. The VLM rates at the Pohang tide gauge site were -25.5 mm/year during 2014 ~ 2017. This VLM rate at Pohang tide gauge derived by StaMPS-PSI estimates were from the strong dominant scatterers along the coastal regions.
Second, for the terrains, with few dominant scatterers and more distributed scatters, a short temporal InSAR pair selection approach was introduced, referred as Sequential StaMPS-Small baselines subset (StaMPS-SBAS) was proposed in this study. Sequential StaMPS-SBAS forms the interferograms of short temporal sequential order (n = 5) to increase the initial pixel candidates on the natural terrains in the vicinity of tide gauges. Sentinel-1 A/B SAR data over ten tide gauges in the Korean peninsula having different terrain conditions were acquired during 2014 ~ 2020; and employed with sequential StaMPS-SBAS to estimate the VLM rates and time-series displacements. The initial pixel density has been doubled and ~ 1.25 times the final coherent pixels identified over the conventional StaMPS-SBAS analysis.
Third, the potential for the fully automatic estimation of time-series VLM rates by sequential StaMPS-SBAS analysis was investigated. A fully automatic processing module referred to as βSeq-TInSARβ, was developed which has three modules 1) automatically downloads Sentinel-1 Single look complex (SLC) data, precise orbit files, and Digital Elevation Model (DEM); 2) SLC pre-processor: extract bursts, fine Coregistration and stacking and, 3) Sequential StaMPS-SBAS processor: estimates the VLM rates and VLM time-series.
Finally, the Seq-TInSAR module is applied to the 100 tide gauges that exhibit abnormal sea level trend with par global mean sea level average. For each tide gauge site, 60 ~ 70 Sentinel-1 A/B SLC scenes were acquired and 300 ~ 350 sequential interferograms were processed to estimate the VLM at tide gauge stations. The final quantitative VLM rates and time-series VLM are estimated for the selected tide gauges stations. Based on the VLM rates, the tide gauges investigated in this study are categorized into different VLM ranges. The in-situ GPS observations available at 12 tide gauge stations were compared with InSAR VLM rates and found strong agreement, which suggests the proposed approach more reliable in measuring the spatial and temporal variations of VLM at tide gauges.μ μΈκ³μ μΌλ‘ λ°μνλ ν΄μλ©΄ μμΉμ μ μ§λ ν΄μκ³Ό λμ μ§μμ μ¬κ°ν μνμΌλ‘ μμ©νλ€. ν΄μ μ§μμ 보νΈνκΈ° μν΄ μ μ§κ΅¬ λ° ν΄λΉ μ§μμ ν΄μλ©΄ λ³νλ₯Ό μ΄ν΄νλ κ²μ λλ¨ν μ€μνλ€. μ‘°μ κ΄μΈ‘μλ μ μΈκ³μ μ€μΉλμ΄ ν΄λΉ μ§μ κΈ°μ€μ λ°λ₯Έ ν΄μλ©΄ λ³νλ₯Ό μ§μ μΈ‘μ νλ€. μ§λ 30 λ
κ° ν΄μλ©΄μ IPCC (μ λΆ κ° κΈ°ν λ³ν ν¨λ)κ° μΆμ ν 20 μΈκΈ°μ ν΄μλ©΄ μμΉ (3.35mm / λ
)λλΉ 1.8mm / λ
κ°κΉμ΄ μμΉνμλ€. κ·Έλ¬λ ν΄μλ©΄ μμΉμ μμΈκ³Ό ν¨κ» μ°μ§ μ§λ° μ΄λ (VLM)μ μ§μ ν΄μλ©΄ λ³νλ₯Ό μ΄ν΄νλ λ° νμμ μΈ μμμ΄μ§λ§ κ·Έ κΈ°μ¬λλ μ¬μ ν λΆλΆλͺ
νλ€. VLMμ μμ° νλκ³Ό μΈκ° νλ λͺ¨λμ μν μ§μμ λ³νλ‘ μΈν΄ μ‘°μ κ΄μΈ‘μμμ μ§λ°μ κ³ λ λ³νλ‘ μ μλλ©° ν΄μλ©΄ λ³ν μ νλμ μ
νμν€κ³ μ μ¬ ν΄μλ©΄ λ³νμ κ°μμ μ΄λν μ μλ€. μ μΈκ³ λ° μ§μ ν΄μλ©΄ μμΉμ μ¬κ΅¬μ±νλ €λ©΄ 1 λ°λ¦¬λ―Έν° λ―Έλ§μ μ νλλ‘ μ‘°μ κ΄μΈ‘μμμ VLMμ νκ°νλ κ²μ΄ νμμ μ΄λ€. μ΄μ μ°κ΅¬λ GPS (Global Positioning System)λ₯Ό ν΅ν΄ μ νλ μμΉμμ VLM μ κ΄μΈ‘νλ €κ³ μλνμμΌλ κ΅μμ μΈ GPS μ νΈλ€λ‘λΆν° κ΄μΈ‘λ VLMμΌλ‘λ κ·Έ μΆμ μ΄ λΆνμ€νλ€.
λ³Έ μ°κ΅¬μμλ μκ³μ΄ SAR κ°μκ³ (InSAR) κΈ°λ²μ μ΄μ©νμ¬ SAR (Synthetic Aperture Radar) λ°μ΄ν°λ₯Ό ν΅ν΄ 곡κ°μ , μκ°μ λ³νλ₯Ό ν¬ν¨ν μλμ VLMμ μ§μ μΈ‘μ νκΈ° μν λμμ μ κ·Ό λ°©μμ μ μνλ€. μ΄ μμ
μ μκ³μ΄ InSAR λΆμμ μ¬μ©νμ¬ κ΄λμμ κ±Έμ³ λμ κ³΅κ° ν΄μλλ‘ VLM μλμ μΆμ μ ν₯μμν€λ λ° κΈ°μ¬νλ€.
첫째λ‘, Sentinel-1 A / B μμ±μ C-band Interferometric Wide-swath (IW) λͺ¨λ SAR μμμ΄ λ³Έ μ°κ΅¬μμ μ‘°μ κ΄μΈ‘μμ VLM μλλ₯Ό μΆμ νλ λ° μ¬μ©λμλ€. Sentinel-1 A / B SAR μμμ 2014 λ
10 μλΆν° 2020 λ
12 μκΉμ§ (~ 6 λ
) κΈ°κ° λμ μμ§λμλ€. κ³ μ μ°λ체λ₯Ό μν μ€ν ν¬λ κΈ°λ² β κ³ μ μ°λ κ°μκ³ (StaMPS-PSI) μκ³μ΄ InSAR μκ³ λ¦¬μ¦μ΄ νλ°λ ν¬ν μ‘°μ κ΄μΈ‘μμ 2014 ~ 2017 λ
λμμ μ‘°μ κ΄μΈ‘μμ μμ μ±κ³Ό VLM μλλ₯Ό λͺ¨λν°λ§νκΈ° μν΄ μ μ©λμλ€. ν¬ν μ‘°μ κ΄μΈ‘μ λΆμ§μ κ²½μ°, μμ±κΆ€λμ μμΉ λ° νκ° κ²½λ‘λ‘ νλν SAR μμμ ν΅ν΄ μμ λ°©ν₯μ λ°λΌ μ‘°μ κ΄μΈ‘μμμμ μ§λ©΄ μ΄λ μλλ₯Ό λμΆνμλ€. ν¬ν GPS κ΄μΈ‘μμ μ°μ§ μ΄λμ λ κΈ°λ² κ°μ μκ΄μ±λ₯Ό νλ¨νκΈ° μν΄ InSARκΈ°λ²μΌλ‘λΆν° μΆμ λ VLM μλμ λΉκ΅λμλ€. ν¬ν μ‘°μ κ΄μΈ‘μμ VLM μλλ 2014 ~ 2017 λ
μ κΈ°κ° λμ -25.5mm / λ
μΌλ‘ κ΄μΈ‘λμλ€. StaMPS-PSI μΆμ μ μν΄ λμΆ λ ν¬ν μ‘°μ κ΄μΈ‘μμ VLM μλμ ν΄μ μ§μμ κ°ν μ°λ 체μμ κΈ°μΈνλ€.
λμ§Έλ‘, κ°ν μ°λμ²΄κ° μκ° μ κ³ λΆμ°λ μ°λμ²΄κ° λ λ§μ μ§νμ κ²½μ°, λ³Έ μ°κ΅¬μμ Sequential StaMPS-Small baselines (StaMPS-SBAS)μ΄λΌλ νλ λ¨κΈ° InSAR μμ μ νμ μν μ κ·Ό λ°©μμ΄ μ μλμλ€. Sequential StaMPS-SBASλ 짧μ μκ° λ²μ(n = 5)μ κ°μκ³ μμμ νμ±νμ¬ μ‘°μ κ΄μΈ‘μ λΆκ·Όμ μμ° μ§νμμ λ³νκ° μ μ νμ μ νμ μ¦κ°μν¨λ€. Sentinel-1 A / B SAR μμμ 2014 λ
~ 2020 λ
μ¬μ΄μ μλ‘ λ€λ₯Έ μ§ν 쑰건μ κ°μ§ νλ°λμ 10 κ° μ‘°μ κ΄μΈ‘μμμ μμ§λμμΌλ©°, VLM μλ λ° μκ³μ΄ λ³μλ₯Ό μΆμ νκΈ° μν΄ Sequential StaMPS-SBASμ ν¨κ» μ¬μ©λμλ€. μ΄κΈ° νμ λ°λλ κΈ°μ‘΄ StaMPS-SBAS λΆμμ ν΅ν΄ νμΈ λ μ΅μ’
μ μΈ λΆλ³νμ λ°λμ μ½ 1.25 λ°°μ λ λ°°λ‘ λμΆλμλ€.
μ
μ§Έλ‘, Sequential StaMPS-SBAS λΆμμ μν μκ³μ΄ VLM λΉμ¨μ μμ ν μλ μΆμ κ°λ₯μ±μ μ‘°μ¬νμλ€. Seq-TInSARλΌκ³ νλ μμ ν μλ μ²λ¦¬ λͺ¨λμ΄ κ°λ°λμμΌλ©°, 3 κ°μ νμ λͺ¨λλ‘ κ΅¬μ±λμ΄μλ€. 1) Sentinel-1 SLC (Single Look Complex) μμ, μ λ°ν κΆ€λ μ 보 λ° DEM (Digital Elevation Model)μ μλ λ€μ΄λ‘λ 2) SLC μ μ²λ¦¬κΈ° : μμ λ³ Burst μΆμΆ, μ λ°ν ν΅ν© λ° Stacking, 3) Sequential StaMPS-SBAS νλ‘μΈμ : VLM μλ λ° VLM μκ³μ΄ λ³μμ μΆμ
λ§μ§λ§μΌλ‘, Seq-TInSAR λͺ¨λμ λμ νκ· ν΄μλ©΄ νκ· μΌλ‘ λΉμ μμ μΈ ν΄μλ©΄ μΆμΈλ₯Ό 보μ΄λ 100 κ°μ μ‘°μ κ΄μΈ‘μμ μ μ©λλ€. μ‘°μ κ΄μΈ‘μ μ§μ λ³λ‘ 60 ~ 70 κ°μ Sentinel-1 A / B SLC μμμ νλνκ³ 300 ~ 350 κ°μ μκ³μ΄ κ°μκ³ μμμ μ²λ¦¬νμ¬ μ‘°μ κ΄μΈ‘μμμ VLMμ μΆμ νμλ€. μ λμ μΈ VLM μλμ μκ³μ΄ VLMμ μ μ ν μ‘°μ κ΄μΈ‘μμ λν΄ μΆμ νμλ€. VLM μλμ κΈ°λ°μΌλ‘ λ³Έ μ°κ΅¬μμ λμΆν μ‘°μ κ΄μΈ‘μλ λ€μν VLM λ²μλ‘ λΆλ₯λλ€. 12 κ°μ μ‘°μ κ΄μΈ‘μμμ μ·¨λν νμ₯ GPS κ΄μΈ‘ μλ£λ₯Ό InSARλ‘λΆν° μΆμ ν VLM λΉμ¨κ³Ό λΉκ΅νμ¬ κ°λ ₯ν μκ΄μ±μ μ°Ύμκ³ , μ΄λ λ³Έ μ°κ΅¬μμ μ μν μ κ·Ό λ°©μμ΄ μ‘°μ κ΄μΈ‘μμμ VLMμ 곡κ°μ λ° μκ°μ λ³νλ₯Ό μΈ‘μ νλλ° μ λ’°ν μ μλ μλ£λ‘ μ¬μ©λ μ μμμ μμ¬νλ€.Chapter 1. Introduction 1
1.1. Brief overview of sea-level rise 1
1.2. Motivations 4
1.3. Purpose of Research 9
1.4. Outline 12
Chapter 2. Sea Level variations and Estimation of Vertical land motion 14
2.1. Sea level variations 14
2.2. Sea level observations 14
2.3. Long term sea level estimation 19
2.4. Factors contributing tide gauge records: Vertical Land Motion 19
2.5. Brief overview of InSAR and Time-series SAR Interferometry 24
Chapter 3. Vertical Land Motion estimation at Tide gauge using Time-series PS-InSAR technique: A case study for Pohang tide gauge 36
3.1. Background 36
3.2. VLM estimation at Pohang tide gauge using StaMPS-PSI analysis 38
3.3. Development of StaMPS-SBAS InSAR using Sequential InSAR pair selection suitable for coastal environments 55
3.4. Discussion 80
Chapter 4. Application of time-series Sequential-SBAS InSAR for Vertical Land Motion estimation at selected tide gauges around the world using Sentinel-1 SAR data 85
4.1. Description of PSMSL tide gauge data 87
4.2. Sentinel-1 A/B SAR data acquisitions 92
4.3. Automatic Time-series InSAR processing module βSeq-TInSARβ 93
4.4. Results: Estimation of vertical land motions at selected tide gauges 97
4.5. Comparison of InSAR results with GNSS observations 112
4.6. Discussion 125
Chapter 5. Conclusions and Future Perspectives 128
Abstract in Korean 133
Appendix β A 136
Appendix β B 146
Bibliography 151λ°
Technical approaches, chapter 3, part E
Radar altimeters, scatterometers, and imaging radar are described in terms of their functions, future developments, constraints, and applications
Altimetric system: Earth observing system. Volume 2h: Panel report
A rationale and recommendations for planning, implementing, and operating an altimetric system aboard the Earth observing system (Eos) spacecraft is provided. In keeping with the recommendations of the Eos Science and Mission Requirements Working Group, a complete altimetric system is defined that is capable of perpetuating the data set to be derived from TOPEX/Poseidon, enabling key scientific questions to be addressed. Since the scientific utility and technical maturity of spaceborne radar altimeters is well documented, the discussion is limited to highlighting those Eos-specific considerations that materially impact upon radar altimetric measurements
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