SPOT 5 HRS geometric performances: Using block adjustment as a key issue to improve quality of DEM generation

Bouillon, A.; Bernard, Marc; Gigord, Patrick; Orsoni, A.; Rudowski, Véronique; Baudoin, A.

doi:10.1016/j.isprsjprs.2006.03.002

Cited by 85 publications

(72 citation statements)

References 3 publications

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“…21.6 m). If we assume that the SRTM-DEM is well geolocated, the total horizontal shift of the SPOT5 reference scene is 23.7 m, within the specification of the sensor (Bouillon et al, 2006). This reduced shift is also an a posteriori verification of our methodology to extract GCPs: a limited error in the geolocation of the SPOT5 reference scene is required to avoid large errors in the GCP elevations extracted from the SRTM-DEM.…”

Section: Planimetric Adjustment Of the Demsmentioning

confidence: 87%

“…Instead, we automatically generate GCPs by taking advantage of the accurate geolocation of the SPOT5 images and the availability of the SRTM topography (Figure 3). Indeed, thanks to precise onboard measurements of satellite positions and attitudes, the orbit of the SPOT5 satellite is wellknown, so that each pixel in a SPOT5 image can be located on the ground with an accuracy of +/-25 m at the 66% confidence level (Bouillon et al, 2006 ;Reinartz et al, 2006). The automatic extraction of GCPs starts with the relative orientation of the two SPOT5 images.…”

Section: Production Of the Spot5-demmentioning

confidence: 99%

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Remote sensing estimates of glacier mass balances in the Himachal Pradesh (Western Himalaya, India)

Berthier¹,

Arnaud

Kumar

et al. 2007

Remote Sensing of Environment

500

350

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Although they correspond to an important fraction of the total area of mountain glaciers (33000 km 2 out of 546000 km 2 ), Himalayan glaciers and their mass balance are poorly sampled. For example, between 1977 and1999, the average area surveyed each year on the field was 6.8 km 2 only. No direct mass balance measurement is available after 1999. To contribute to fill this gap, we use remote sensing data to monitor glacier elevation changes and mass balances in the Spiti/Lahaul region (32.2°N, 77.6°E, Himachal Pradesh, Western Himalaya, India). The 2004 DEM is derived from two SPOT5 satellite optical images without any ground control points. This is achieved thanks to the good on-board geolocation of SPOT5 scenes and using SRTM elevations as a reference on the ice-free zones. Before comparison on glaciers, the two DEMs are analyzed on the stable areas surrounding the glaciers where no elevation change is expected. Two different biases are detected. A long wavelength bias affects the SPOT5 DEM and is correlated to an anomaly in the roll of the SPOT5 satellite. A bias is also observed as a function of altitude and is attributed to the SRTM dataset. Both biases are modeled and removed to permit unbiased comparison of the two DEM on the 915 km 2 ice-covered area digitized from an ASTER image.On most glaciers, a clear thinning is measured at low elevations, even on debris-covered tongues. Between 1999 and 2004, we obtain an overall specific mass balance of -0.7 to -0.85 m/a (water equivalent) depending on the density we use for the lost (or gained) material in the accumulation zone. This rate of ice loss is twice higher than the long-term (1977 to 1999) mass balance record for Himalaya indicating an increase in the pace of glacier wastage. To assess whether these ice losses are size-dependant, all glaciers were classified into three samples according to their areal extent. All three samples show ice loss, the loss being higher for glaciers larger than 30 km 2 . In the case of the benchmark Chhota Shigri glacier, a good agreement is found between our satellite observations and the mass balances measured on the field during hydrological years 2002-2003 and 2003-2004. Future studies using a similar methodology could determine whether similar ice losses have occurred in other parts of the Himalaya and may allow evaluation of the contribution of this mountain range to ongoing sea level rise.

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Section: Planimetric Adjustment Of the Demsmentioning

confidence: 87%

Section: Production Of the Spot5-demmentioning

confidence: 99%

Remote sensing estimates of glacier mass balances in the Himachal Pradesh (Western Himalaya, India)

Berthier¹,

Arnaud

Kumar

et al. 2007

Remote Sensing of Environment

500

350

View full text Add to dashboard Cite

show abstract

“…pointing information, auxiliary and ancillary data) (for more details, see Schenk, 1999). The latter is the approach for both satellite stereo DEMs used in the this study: the ASTER DEMs produced by LPDAAC using the SilcAst software (product AST14) and the SPOT5-HRS DEMs (Bouillon et al, 2006;Korona et al, 2009) The stereoscopic ASTER instrument, in orbit since 1999 aboard the Terra platform, contains a nadir and backward VNIR sensor (0.76-0.86 µm) separated by ≈30 • corresponding to a B/H ratio of 0.6 (ERSDAC, 2005;. The ground swath is 60 km while the image and reported DEM ground resolution is 15 and 30 m, respectively.…”

Section: Stereoscopic Demsmentioning

confidence: 99%

“…ASTER DEM uncertainty is reported to be typically within 15-60 m RMSE in the vertical depending upon terrain type (Toutin, 2002Kääb et al, 2002;Hirano et al, 2003;Kääb, 2005;Fujisada et al, 2005) and between 15 and 50 m horizontally Iwasaki and Fujisada, 2005). SPOT5 uncertainty is reported to be between 10-25 m vertically (Berthier and Toutin, 2008;Korona et al, 2009) and greater than 15 m in the horizontal (Bouillon et al, 2006;Berthier and Toutin, 2008). In relationship to pushbroom sensors (e.g.…”

Section: Stereoscopic Demsmentioning

confidence: 99%

Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

2011

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Abstract.There are an increasing number of digital elevation models (DEMs) available worldwide for deriving elevation differences over time, including vertical changes on glaciers. Most of these DEMs are heavily post-processed or merged, so that physical error modelling becomes difficult and statistical error modelling is required instead. We propose a three-step methodological framework for assessing and correcting DEMs to quantify glacier elevation changes: (i) remove DEM shifts, (ii) check for elevation-dependent biases, and (iii) check for higher-order, sensor-specific biases. A simple, analytic and robust method to co-register elevation data is presented in regions where stable terrain is either plentiful (case study New Zealand) or limited (case study Svalbard). The method is demonstrated using the three global elevation data sets available to date, SRTM, ICESat and the ASTER GDEM, and with automatically generated DEMs from satellite stereo instruments of ASTER and SPOT5-HRS. After 3-D co-registration, significant biases related to elevation were found in some of the stereoscopic DEMs. Biases related to the satellite acquisition geometry (along/cross track) were detected at two frequencies in the automatically generated ASTER DEMs. The higher frequency bias seems to be related to satellite jitter, most apparent in the backlooking pass of the satellite. The origins of the more significant lower frequency bias is uncertain. ICESat-derived elevations are found to be the most consistent globally available elevation data set available so far. Before performing regional-scale glacier elevation change studies or mosaicking DEMs from multiple individual tiles (e.g. ASTER GDEM), we recommend to co-register all elevation data to ICESat as a global vertical reference system.

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“…The HRS sensor onboard SPOT 5 acquires high-resolution along-track stereoscopic images (pixel size of 5 m along track and 10 m across track) with 9208 forward and backward viewing angles (Bouillon et al 2006;Berthier & Toutin 2008). The August 2004 HRS DEM was obtained from the SPOT 5 Stereoscopic Survey of Polar Ice: Reference Images and Topographies (SPIRIT) project (Korona et al 2009).…”

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confidence: 99%

Response of Eyjafjallajökull, Torfajökull and Tindfjallajökull ice caps in Iceland to regional warming, deduced by remote sensing

et al. 2011

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We assess the volume change and mass balance of three ice caps in southern Iceland for two periods, 1979–1984 to 1998 and 1998 to 2004, by comparing digital elevation models (DEMs). The ice caps are Eyjafjallajökull (ca. 81 km2), Tindfjallajökull (ca. 15 km2) and Torfajökull (ca. 14 km2). The DEMs were compiled using aerial photographs from 1979 to 1984, airborne Synthetic Aperture Radar (SAR) images obtained in 1998 and two image pairs from the SPOT 5 satellite's high-resolution stereoscopic (HRS) instrument acquired in 2004. The ice-free part of the accurate DEM from 1998 was used as a reference map for co-registration and correction of the vertical offset of the other DEMs. The average specific mass balance was estimated from the mean elevation difference between glaciated areas of the DEMs. The glacier mass balance declined significantly between the two periods: from −0.2 to 0.2 m yr−1 w. eq. during the earlier period (1980s through 1998) to −1.8 to −1.5 m yr−1 w. eq. for the more recent period (1998–2004). The declining mass balance is consistent with increased temperature over the two periods. The low mass balance and the small accumulation area ratio of Tindfjallajökull and Torfajökull indicate that they will disappear if the present-day climate continues. The future lowering rate of Eyjafjallajökull will, however, be influenced by the 2010 subglacial eruption in the Eyjafjallajökull volcano

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SPOT 5 HRS geometric performances: Using block adjustment as a key issue to improve quality of DEM generation

Cited by 85 publications

References 3 publications

Remote sensing estimates of glacier mass balances in the Himachal Pradesh (Western Himalaya, India)

Remote sensing estimates of glacier mass balances in the Himachal Pradesh (Western Himalaya, India)

Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

Response of Eyjafjallajökull, Torfajökull and Tindfjallajökull ice caps in Iceland to regional warming, deduced by remote sensing

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