Topography from land radar altimeter data: Possibilities and restrictions

Topography from land radar altimeter data: Possibilities and restrictions

/‘l?J,S C‘he,tZ .t&/l G/1. VUi. 25. N0 Cc!2000 l’ergamon 1. PI’ 81-88. Elsewer Science All rights 1464-l 895/00/$ 2000 Iid reserved - see fro...

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/‘l?J,S C‘he,tZ .t&/l

G/1. VUi. 25. N0 Cc!2000

l’ergamon

1. PI’ 81-88. Elsewer

Science

All rights 1464-l

895/00/$

2000 Iid

reserved

- see front matter

Pll: S1464-1895(00)00014-4

Topography from Land Radar Altimeter Data: Possibilities and Restrictions P. A. M. Berry Geomatics

Unit, Faculty of Computing

& Engineering,

De Montfort University,

Leicester LE 1 9BH, C K.

Received 23 April 1999: revised 20 October 1999: uccepted 30 October 1999 and the ice mass balance questron. have pushed the techniques of cryospheric altimetry to the limit (Bamtxr et al.. 1997a: Remy &Legresy, 1997). However. the potential of land alhmep has been the Early missions subject of comparatively little study (Seasat and Geosat) were severely iinuted in their samplmg of the earth’s land surfaces bv their inability to maintain lock over significant terrain rehef. the wide track spacing of the Seasat 17 day orbit repeat pattern and the off-ranging and acquisition problems elrperienced by Geosat which drastically curtailed the effectiveness of the Geosat mission datasets for land applications (Guzkowska et al.. 1990. Bremter et al.. 1990). The advent of ERS-1 has therefore had a major impact on land altimetry: the ERS-1 Geodetic Mission has provided a dataset with relatively good spatial coverage and the inclusion of an ice mode has permitted the ERS-1 ammeter to sample the earth’s land surfaces far more effectively than previous missions

AbstractWhiM satellite radar altimetry has been widely utihsed over both ocean and ice surfaces for topographic mapping, applications over land have received relatively little %tention. This is in part due to the complex nature of echoes returned from rapidly varying topographic land surfaces, which can cause an altimeter to generate One approach to improving erroneons range estimates. these data is to retrack using a single retracker, and construct a spatial average of heights obtained to give an estimate of mean orthometric height. This paper presents results obtained using an alternative approach: rm returns at all levels of complexity through an expert system, which chooses one from a series of ten m algorithms based on an analysis of the return waveform shape. The selected algorithm then recalculates the range to surf&e, and hence derives an orthometric height. Utihsing this approach with the geodetic mission dataset from ERS-I has genera&d over 100 million height points with a near-global distribution. This paper presents selected results from this reseat& using ERS-1 geodetic mission CkxtatogetherwithERS-1 arldE%!S-2 35 day data to demonstratethe accumcy to which orthometric heights can be cktermmed, using global crossover analysis and comparison with grotmd truth. The paper illustrates applications of these data mchrcling validation and error correction of Digital Elevation Models. and discusses use and hmitations of direct mapping with altimettv. 0 2000 Elsevier Science Ltd. All rights reserved

2 Background Prior to the launch of ERS-1. two datasets u-ere available for land applications of radar altimetry. The first consisted of three months of data from the Seasat satellite, where the mstrument gathered some land data for those regions where it was able to maintam contact with the vatying topographic surfaces. Geosat data were also collected over land both m the 17 day repeat orbit and during the geodetic mission. Potentially. the latter dataset could have been vev valuable for land altimetry. However. as with the Seasat satellite. the altimeter was optimised for tracking over the ocean and was found to be unable to maintain lock over significant terrain (Guzkowska et al., 1990). In’addition. Geosat data over land were found to exhibit aperiodic changes m returned power on a spatial scale of a few tens of km.. and the consistency of derived height values appeared poor (ibid). These problems were ascribed to a combinatron of mispointing and instrument difficulties. This combination of problems limited the mam applications of these data to flat surfaces. primarily over inland water. wetlands and desert. Valuable information on river and lake heights was extracted (Guzkowska et al.. 1990); preliminary mapping was attempted by several groups over surfaces where the altimeters were able to collect data but due to the Geosat data limitations. the primv source of information remained the Seasat satellite

1. Introduction Satellite radar altimetry has been used for man)- years to map the ocean surface (Lillibridge et al., 1997) with a well developed physical model describing the interaction of the radar pulse with the ocean surface. and interpretation of results from a series of satellites for both oceanographic and geodetic purposes. The capability and limitations of cryospheric altimetn; have also become more clearly defined within the last few years. With the advent of ERS-1 providing the first coverage of part of the Antarctic continent. continued development of mapping capability over land ice surfaces. Correspondence

to: P. A.M Beg

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P. A. M. Berry: Topography from Land Radar Altimeter Data: Possibilities and Restrictions

(e.g. Frey & Brenner. 1990); here, DEM generation was severely constrained by the wide track spacing resulting from the 17 day orbit repeat cycle.

3. Impact of ERS-1 The advent of ERS-1 completely transformed the study of land applications of radar altimetry data, for two main reasons. The Iirst was the inclusion of an Ice Mode on the ERS-1 altimeter. This ackhtional mode, which allowed the altimeter to maimain lock over more rugged terrain was developed, as the name suggests, @marily to f&lit&e cryospheric altimetry. The high inclination of the ERS-1 satellite meant that for the first time data would be collected over a large proportion of Antarcuca; close to the limiting inclination track density increases such that even a 35 day orbit generates relatively good spatial coverage. However, the Ice mode tracker also enabled sampling of much more uneven terrain over land surhxes. The second conttibution of ERS-1 was the orbit repeat cycles which were generally more Cwourable for land applications (except monitoring of inland water levels). In pamcular, the geodetic mission generatedauniquedatasetoflandreturnswithfarbetter spatial eoverage for topographic pmposes than previous missions (20 waveforms for each 7 km along track with maximumtrackrqarationattheequatorofabout9km). The multiple repeat @terns of 35 day data also permitted the cow of heigbting to be veriiied. The haxter&csoftheERS-Isystemaresummarisedin &tbles3.Iaand3.Ib. Table 3.la: ERS-1 Geodetic Mission Grbit Barameters 7147190 km Semi-major axis 98.49 ’ InClilUtiOll 2411 orbitspercycle 168 day repeat cycle

Table 3. lb: ERS-1 Altimeter Characteristics 13.8 GHz FreClWrlCy 33OMh2 Oceanmode Bat&&h 82.5 Mhz Ice mode 1 Echo waveform samples ] 64 x 16 bits at 2OHz

1

3.1 Land Echo F’rocessing The analysis of altimeter echoes over non+cean surfaces has been a subject of research for many years. with the emphasis primarily on data returned from ice surfaces (e.g. Bamber et a& 1997a: Remy & Legresy, 1997). Specific problems have been found to be associated with the attempt to retrieve an accumte range to surface over land ice. the primary problem being off-ranging. Over such surfaces, the high refIectivity to radar. combined with the characteristic of large areas of comparatively low, uniform slope can result in the altimeter echo being received not from the nadir point, but from some other surface closer to

the altimeter. This problem has attracted a great deal of attention. with various approaches being taken to try to recover topographic information. One method involves reprocessing data to obtain a range to surface by using a to generate slope Digital Elevation Model (DEM) information with the DEM and range to surface generally derived by some iterative process: another. approach attempts to relocate the echoes to the surfaces from which they originated (e.g Bamber et al, 1997a: Remy & Legresy, 1997) using a variety of mathematical techniques. Several of the problems associated with ice altimetry are also encountered over land surfaces. As with ice, the altimeter is in general unable to keep the echo returns from the rapidly varying topographic surfaces in the centre of the range window, and the on-board processor therefore cannot calculate an accumte range to surface. Thus, in order to work with these data some form of reprocessing must be employed. analysing the echo shape and attempting to ‘retra& the waveform. Two approaches have been taken to land echo retracking The first is to genera& heights by retracking using a single retracker for all data. typically either an implementation of the Offset Centre of Gravity (OCXX) techniclue (e.g Bamber et al., 1997b) or one optimised for double-peaked waveforms (e.g. Brenner et al.. 1997). Severe editing and filtering criteria may be applied to the dataset (Bamber et al., 1997b). Individual mtmcked ranges to surface are then combined to derive some mean or median height value (Bamber et al, 1997b; Brenner et al., 1997). FolIowing the pattern of Iand ice work slope corrections have also been applied ( ibid). To date, results from this approach have [email protected] been published in the form of very gene&&d representations of land topography, with a ‘mean value’ pixel size ranging from 0.25 o (Brenner et al. 1997) to 5’ @amber et al, 1997b). This genemlisation approach clearly limits the applications of land altimeuy derived damsets severely. An alter&ix techuique has been developed for land waveforms; to sort the waveforms on shape. retain all returns which show a leading edge regardless of complexity and use multiple retrackers to deal with different waveform shapes (Berry et al.. 1997a; Berry & Thornton. 1998). As will be seen later, there are speciIic reasons why a different approach to land altimetry retracking is appropriate. The primary factor is that many shapes of waveform return observed over land are not visible with any significance in data from land ice surfaces (Berry et al.. 1997a): techniques developed for ice retracking may not be appropriate over laud. and this is true in particular when accounting for the effects of off-ranging This paper presents results obtained using an expert system approach, and discusses the applications, potential and limitations of land altimetry when analysed in this way. This approach was initially developed because statistics from a first analysis of ERS-1 data showed that topographic sampling was much better than expected in ice mode over land: hypsographic curves showed data retrieval consistently to high elevations well above 1OOOm.in sharp contrast to the results obtamed from Seasat (Guzkowska et

Zimbabwe

area

&ara&uistics,

Spanlar - adually quasi-sptxular wavcfomx now split h&wccn thrw ~&a&en

Hog - wdland r&a&u

Hor - one ofthe r&rackers dealing with slope-affected waveforms

Figure 3. I .2 shows a selection of individual waveforms of ditktnt

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15SO6OW Bor type 2 Record 54629 waveform 2

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15SO6OW Bor type record 1 waveform 8

lahrlled as follows,

15SGOW Facet type 7 Record 66235 waveform 16

Typical Bog waveform recordnumber 4403 waveform 3, 3OSOl5W brasil region

Bins

15SO6OW Facet type 2 Record 27753 waveform 4

1SSO6OWFacet type 1 Record 20265 waveform 5

3OS6OWSpecular type 4 Record 36661 waveform 2

Bins

3OSBOWSpecular type 3 Record 1 waveform 14

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from Land Radar Altimeter

al, 1990). Figure 3.1.1 shows a hypsographic curve over Africa obtained from the TerrainBase GDEM (Tern&Base. 1995) and from the ERS-1 analysis. The spikes in the TerrainBase histogram are artefacts resulting from wide contour spacing of part of the input data.

Initial comparisolls of derived heights (with the range to surf&mcalculatedusingOCOGmtmcking)withthe Tern&&se GDEIvI showed that for certain waveform types, nzonable agreement could be obtained; however. visual examimmon of these waveforms suggested that OCOG retradring was not well characnzismg the complex waveform shapes. Sets of typical waveform shapes over landaregiveninfi~3.12.Examinationofpmfilesalong altimeter tracks, and a detailed comparison over part of the RiftVaIIeywheregrouudtruthwasav&bleconfhmed tracking wer that the ERS-1 ahimeux’was suaxssNy rapidly varying topographic surbces, even maim&ing lock over the [email protected] edges of the Rift Valley. Accordingly, it wasdecidedtoadoptanexpertsystemapproachto reprocessing the ERS-I waveform set, replacing OCOG retracking with a series of separate algorithms specifically configured for different waveform shapes. Initially, the data werereprocessedovertestareaswith3retmckersusinga spline based retrachr developed to handle retmns from low slope areas, in addition to a quasi-specular retracker and a reimplemenmtion of OCOG (later discarded). Comparison with available grotmd truth confirmed that for those classes of waveform which could be related to the tmderlying terrain characteristics, much improved range estimates could be generated However, it was immediately clear that for this approach to deliver significantly imprwed results, a whole suite of retmckem would have to be developed and a more sophisticated waveform ana.lysis and decision module implemented.

3.2 Expert System Development An essential requirement for system testing is accurate validation data. Statistical anaIysis had already suggested

Data: Possibilities

and Restrictions

variable quality in the TerrainBase dataset over Africa The beta release of the GLOBE GDEM (Figure 3.1.1). (GLOBE dataset version 0.5, 1997) was therefore used initially over a test area in the central USA where data quality was stated as good to f 5m (ibid). The data Over Zimbabwe were also chosen as this region is chamcterised by consistent low to moderate slope areas. thus making a good test area for the effects of slope on land retracker accuracy. The evaluation of the existing system over these areas led to an additional retracker being implemented to interpret slope-affected waveforms, and further tuning of the other retrackers. Finally, a comprehensive analysis of waveform shape and topography was conducted to evaluate the effects of off-ranging on land altimeter returns. This resulted in an expert system containing six retmckers (Beny et al., 1997a. b). which was used globally to reprocess the ERS-1 Geodetic Mission dataset into a geographically. based dataset held in 15 degree squares. Statistics showed that over 80% of ‘valid’ waveforms i.e. waveforms containing a leading edge were successfirhy reprocessed to topographic heights. A global crossover analysis (comparing heights of nearest neighbour points close to satellite arc crossovers) showed that globally over 40% of these land crossovers were within lm vertically (Dowson & Beny, 1997). Retracker analysis by area and type incmding detailed work over the Australiaa Great DividingRangeusinga9”DEM quamifiedtheeffectsof off-ranging in extreme conditions, and allowed the suaxs&l reverse engineering of altimeter derived ranges mauntainousterram Resultswere fiomDEMvahresin fed in to the expert system to form the current implememationwithten~. Onekeyresultofthe detailed comparions with a finer scale DEM (Berry & Thornton 1997) is the d&&ion of the ‘effective footprint’ of the ERS-1 altimeter. i.e. that area within the pulselimited footprint which contributes significantly to the return power. This is found to be as low as 200m in diameter for some classes of terrain type. increasing with ‘the severity of the terrain relief However, the use of retrackers which identify and remove that part of the return echo derived !?om slope components again reduces the effective footprint to somewhere within the range 200 400m. Regional crossover analyses were also performed and sample crossover results over a series of 15 degree squares of the earth’s land surface are included in Figure 3.2 for ill~on. The samples have been selected to demonstrate the over Australia generally good agreement (comparatively flat. dry terrain), lower values Over Siberia ( more rugged [email protected]) and varying agreement over parts of Brazil including the Amazon rainforest (heavily vegetated but fairly flat to heavily vegetated with higher topographic relief). From detailed analysis of all the crossover results, it is clear that the severity of the terrain relief is the dominant cause of crossover differences; the height of the underlying terrain and the degree of vegetation are not found significantIy to innuence the results. This is of particular interest over heavily forested regions such as

I’. A. M. Berry: Topography from Land Radar Altimeter Data: Possibilities and Restrictions

the Amazon basin where profile analysis shows the ERS-1 derived heights to be in excellent agreement across river margms and the surroundmg forest. strongly indicating that the dominant radar return is from the underlying ground rather than the canopy -15-0s 75-60W Crossovers

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Figure 3.2 Crossover statistics for 15 degree squares of geodetic mission data from different terrain types

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3.3 current status The HIS-1 Geodetic mission ice and ocean mode data have just been reprocessed globally using an enhanced preprocessor. The resulting dataset has again been segmented into 15 degree squares. piped through the latest version of the expert system. and stored A global recalculation of crossovers and statistics has ‘also been completed: the results ( Dowson &: Berry. 1999) show almost 50% of crossove)s agreeing to &hin lm for the full global coverage over all land surfaces: excluding Antarctica and Greenland the figure is just under 45%. A series of DEM comparisons is underway; a detailed comparison with GLOBE version 1 (Bastings & Dunbar. 1999). GLOBE-P (ibid) and JGP95E (‘Lemoine et al.. 1998) has been completed for every 15 degree square containing land data. Sample rest&s are presented here: further analysis is given elsewhere (e.g. Berry et al.. 1999). A detailed validation of the Australian 9” DEM is ongoing: following on from the initii3J validation of the altimeter derived heights using a portion of this DEM generated tiom survey results accurate to *2m (Berry & Thornton. 1997). Differences are detected over the majority of Uris DEM at a level typically of only a few metres, confirming the generally high quality of the Australian DEM compared with the global models’ representation of Australian topography (Berry et al., 1999). A series of DEM-Altimeter intercomparisons over a demonstration sqnare of Africa is shown in figure 3.3.1. This area was chosen as it iUu.stmtes many of the generic results from the near global ana&sis of these DEMs (ibid). This figure shows a four may intercomparison: the results are summarised below: a) Altimeter - JGP95E artefacts seen: edges correspond to GLOBE-p coverage (seeFig. 3.3.1.~) b) Altimeter - GLOBE v 1 artefacts seen: corresponding to GLOBE-P coverage limitations (see Fig 3.3.1.~). CjAltimeter - GLOBE2 partial coverage illustrated: Note that missing alnmeter data pixels also shown as white. d) GLOBE vl - JGP 95E mi.. of error signatures from a) & b) apparent Figure 3.3.2 shows the height difference histograms of the altimeter- GLOBE and altimeter - JGP95E comparisons illustrated in Figure 3.3.1, shown over two ranges to demonstrate the scale of the offsets observed. Note the large relative offsets of the ground truth datasets, and the very different distributions of these differences in the two sets of histograms, confirming that in this area the performance of GLOBE is significantly better than that of JGP95E. Figure 3.3.3 shows a mosaic over South America of difference maps of altimeter - JGP95E results. Note the data loss over the Andes where the altimeter was unable to mamtain lock on the rapidly varying topography: elsewhere. huge offsets and rectangular artefacts are clearly

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P. A. M. Berry: Topography from Land Radar Altimeter Data: Possibilities and Restrictions

a) Altimeter - JGP95E differences. Scale is <-80m (white) to >80m (dark grey)

Scale is i-80m

c) Altimeter - GLOBE-0 partial coverage Nodata pixels plotted as white

d) GLOBE vl - JGP95E differences Scale is <-80m (white) to >80m (dark grey)

Figure 3.3.1: Difference

(white) to >80m (dark grey)

greyscale maps of area 15-30N, 15-30E

- GLOBE dlfference hntogam

to +40m

Altimeter - GLOBE difference hntogam

,.

.,

to *ZOOan

Height (251x1bins)

Altimeter

Figure 3.3.2 Height histograms

-

KiF’95E difference hlstogam to +2OOm

of the difference maps shown in figure 3.3.1

.,

P. A. M. Berry: Topography

from Land Radar Altimeter

visible in the difference map. Further examples are presented elsewhere (Berry et al., 1999). From this global intercomparison it appears probable that all available GDEMs share common error datasets: these datasets are now being identified, studied and improved using the altimeter derived heights.

Figure 3.3.3 Difference map of Altimeter - GLOBE v-1 over South America. Scale is 0 (pale grey) through to x 120m (dark grey). Missing altimeter data over Andes showu as white. 4 Discussion With the inclusion of an ice mode on the ERS-1 and ERS-2 altimeters, land altimetry is able to make a real impact on global Land height detemu~tion By usiug an expert system approach to retrack iudividual waveforms. land altimetry is capable of far more accurate he&hung over land than was previously considered. There is no need to average many values to remove outliers and improve height accuracy from individual retracked height estimates if individual waveforms are reprocessed using a series of retrackers specifically configured for the complex waveform shapes returned from land surfaces: in fact much valuable topographic information is lost by averaging. In addition it is found that the echo shape over land is frequently dominated by a return from a small ‘effective footprint’ only a few hundred metres in extent: this greatly extends the potential applications of these land [email protected] data. Many shapes of return are encountered over land which are absent or only occasionally present. in returns from ice surfaces. For these classes of wavefotms. OCOG

Data: Possibilities and Restrictions

87

retracking is not appropriate. and will in general give a poor range esti&te. In addition to detecting and correcting errors in existing DEMs. these data can also be combined with other space based techniques (e.g. stereo SAR) to produce validated. accurate finer scale DEMs (for example. SAR based DEMs can be generated with a pixel size of 30 s 30m); radar altimetry- can validate/correct over relatively flat terrain (where the effective footprint does not degrade the comparison accuracy) to l-2m vertically. With current datasets, the spatial orbit pattern constraints limit the extent to which altimetry alone can be used to generate DEMs. However. land altimetry offers a very good method for height determination in other than extreme terram. In fact. this technique remains highly accurate in terms of vertical precision compared with other currently existing remotel> applied space datasets which have near-global distribution. with accuracies as good as a few ems. in flat tenain (under these cir cumstances. the primary error cause becomes mismodelling of the geoid used to estimate mean sea level). Even within extreme terrain. altimeter derived heights are generally accurate to a few metres vertically for those echoes where the waveform type falls into a category w-hich allows an appmpriate retracker to be selected. Where the topographic range over the 200 - 4OOm effective footprint is many tens of metres. a less accurate result will be obtained with the altimeter derived value generally lying within the range of heights represented within the actual topograhy but not always precisely at the mean height, Additionally, sampling of extreme terram will be highly non-uniform with the lower elevations and interleaving valley systems well sampled. and more extreme parts of the topographic variation either not sampled at all or returning one of a class of ‘facet’ returns. which are obsen;ed in a few percent of mountain echoes. Here. multiple surfaces can be identified as contributing to the return echo. and a single range to surface cannot be ascertained

5 Fhlture work There is a contimring role for these data in vahdation of DEMs. and removal of distortions caused by data and/or processing effects. patticularly where satellite based or airborne data were used for DEM generation. Altimetry also provides an excellent medium for the correction of datum errors. Additionally, altimeter derived heights from the ERS-I Geodetic Mission can produce right now- a significantly better representation of terrain than existing public domam GDEMs over an appreciable extent of the earth‘s land surfaces. Other information is also hidden in altimeter returns: with a physical model for the interaction of the signal with the land surface. it is now becoming possible to [email protected] additional parameters. both as terrain related information. and in the form of environmental signals. This latter discovery opens the door to a whole new application area of land radar altimetry in the determination of climate related

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P. A. M. Berry: Topography from Land Radar Altimeter Data: Possibilities and Restrictions

parameters. With an existing time series of over 9 years of data. the potential of altimetry in this field is considerable. Overall. few satellite instruments have given as good a return on the investment as radar altimetry: with a pivotal role in ocean surface studies and ocean geodesy, a continuing role in cryospheric studies and now existing and developing applications in both land surface mapping and enviromnemal monitoring, the information from ERS-1 and ERS-2 forms a very valuable dataset. With the planned latmch of Envisat. this valuable datastream is set to continue into the millennium.

6 Acknowledgements The author would like to acknowledge the support of the European Space Agency in providing data for this research programme, and thank Dr. M. Dowson for supplying the crossover statistics used in this paper.

7 References

Bamber,J.L., Ekholm,S. & Krabill W,B.. 1997. A Digital Elevation Model of the Greenland Ice Sheet and Validation with Airborne Laser Altimeter Dam Space at the Service of Envimnmem ESA Pub. SP-414, Vol.II, May 1997. i:ber, J.L., Muller, J.P. & Mandayake, A, 1997. A Global 5’ Digital Elevation Model from the Geodetic Phase of ERS-1. Space at the Service of our Enviromnent, ESA Pub. SP-414, Vo1.B May 1997. Berry, P.AM, Bra&e, H., & Jasper? A, 1997a Retmckmg ERS-1 Altimeter Waveforms over Land for Topographic Height -on: an Expert Systems Approach. Space at the Service of our Emiromnent, ESA Pub. SP-114. vo1.1, May 1997. Berry, P.A.M., Bran, E., Sanders R.F. & Leenmans C., 1997b. Use of ERS-1 Land Altimetry to Validate the GLOBE Global Digital Elevation Model. LAG. N, Brazil 1997. Berry, P.AM & Thornton. S.R, 1998. Accuracy Assessment of Altimeter Derived Orthometric Heights using Regional Digital Elevation Models. E.G.S. XXIII General Assembly, Nice, France, 20-24 April 1998. Berry, P.AM., Hoogerboord, J.E. % Pinnock. RA., 1999.

Identification of Common Error Signatures in Global Digital Elevation Models. This issue. Brenner, A.C., Frey, H., DiMaizio, J. & Tsaoussi, L., 1997. Topography over South America from ERS Altimetry. Space at the Service of our Enviromnem, ESA Pub. SP414. vo1.1, May 1997. Brenner AC., Frey, H.V. & Zwally. J., 1990 Comparisons between GEOSAT and SEASAT over non ocean surfaces. Geophysical Research Letters, ~17. ~1537. Dowson, M. & Berry, P.A.M., 1997. Potential of ERS-1 derived Grthometric Heights to Generate Ground Control Points. Space at the Service of our Environment ESA Pub. SP-414. vo1.1. May 1997 Dowson. M. & Berry. P.A.M.. 1999. Assessment of Techniques’ for Correction of Global Digital Elaation Models. RJGG XXII General Assembly. Birmingham. July 1999 Frey, H.V. Ce Brenner. A.C.. 1990 Australian Topography from SEASAT overland altimetry. Geophysical research L letters. v17. 1533. GLOBE dataset version 0.5, 1997. National Geophysical Data Center. Boulder, Co.. USA. Guzkowska. M.A. Rapley, C.G.. Ridley. J.K.. Cudlip. W.. Birkett. C.M. & Scott. R.F., 1990. Developments in Inland Water and Land Altimetry. ESA Report CR7839/88/F/l% Hastings D. A. & Dunbar P. K.. 1999. Global Land GneKilometer Base Elevation (GLOBE) Digital Elevation Model, Documentation. Vol 1.0. Key to Geophysical Records Documentation (KGRD) 34. NOAA. NGDC. Boulder Co. 80303. USA Lemoine, F.G. et al., 1998. The Development of the Joint NASA GSFC anf the National Imagery and Mapping Agency (NlMA) Geopotential Model EGM96. NASQTP1998-20686 1. Lillibridge. J.. Leben. R B Vossepoel. F.. 1997. Real Time Altimetry from ERS-2. Space at the Service of our Enviromnem. ESA Pub. SP-414. Vol.IIl. May 1997. Remy. F. & Legresy. B., 1997. Antarctica Ice Sheet Dynamics Derived from ERS-1 Precise Topography. Space at the Service of our Environment ESA Pub. SPAlJ, Vol.Ir, May 1997. TerrainBaSe Worldwide Digital Terrain Data Documentation Manual. 1995. NGDC Key to Geophysical Records Documentation No. 30. NOAA. Boulder. Colorado 80303-3328. USA.