DEM generation and velocity mapping

On the use of Pléiades imagery in glaciology.
DEM generation and velocity mapping
Etienne Berthier (LEGOS) with colleagues from
Univ. Iceland / IANIGLA-Mendoza / LGGE-LTHE-France
Pléiades 3D view of the Tungnafellsjökull (Iceland). © CNES 2013, Distribution Airbus D&S
Scientific context. Glaciers as indicators of climate change,
contributor to sea level rise and water resources
Hausse observée
+3.2 mm/a
Dilatation thermique
+1.0 mm/a
Observed SLR
~3.2 0.4
Calottes Polaires
+0.6 mm/a
Ocean warming
+1.1 0.3
Glaciers
+0.9 mm/a
Land water
+0.4 0.2
Ice Sheets
+0.6 0.2
Glaciers
+0.8 0.4
Sea Level Budget between 1993 and 2010
From IPCC, 2014; Meyssignac & Cazenave, 2012
Sea level rise since 1900 (Meyssignac &
Cazenave, 2012)
Strong but still uncertain
contribution, our goal is to better
constrain their mass balance
Glaciers: what/where are they?
Alaskan Icefields
20 km
Vatnajökull (Iceland)
Zuo & Oerlemans (1998)
Total area = 730 000 km2
Sea Level equivalent (SLE) = 0.5 m
Number : >250 000
Mer de Glace
Glacier volume changes
Berthier et al., Nat Geo, 2010
300 m
Retreat and thinning of Columbia Glacier (Alaska) between 1980 (Landsat +
USGS DEM) and 2007 (SPOT5)




Need for high resolution and accurate DEM to map glacier elevation changes
Need for velocity fields to better understand how mountain glaciers are
reacting to climate change
Pléiades 1A & 1B provide potentially suitable data to accurately estimate
topography and velocity
Pléiades is also an excellent analog of a future satellite mission (Z-Earth)
recommended during the last CNES prospective seminar in La Rochelle
Outline of the talk
1.
Study sites
2.
Radiometric performance over glaciers
3.
Accuracy of Pleaides DEMs
4.
Velocity mapping from multi-temporal
Pléiades images
1. Pléiades data used in this assessment
 Mostly stereo pairs for DEM generation
 Also monoscopic acquisitions for velocity mapping (Andes, Alps, Antarctica)
 Processing with a commercial software (PCI Geomatica 2013)
Iceland
Univ Iceland,
Magnusson, Palson, Gunnlaugsonn
Andes
IANIGLA, Mendoza
Masiokas, Ruiz, Pitte
Alpes
LGGE
Vincent, Rabatel
Nepal
LGGE
Wagnon, Vincent
Astrolabe Glacier
LGGE
Le Meur
1. Pléiades data used in this assessment
2. Radiometric performance
 Digitization and consequence for the archive
SPOT5: 8 bits digitization, DN ranging from 0 to 255. Low gains had to be defined to
avoid saturation on snow/ice (high reflectance). Another issue was the limited
dynamic of the radiometry in bright homogeneous area of glaciers = narrow histogram
of the DN.
Consequence : Very few useful data in the archive.
Pléiades: 12 bits, DN ranging 0 to 4095. No saturation should occur (gains cannot be
tuned).
+++ Each image from the catalog is now potentially suitable for glaciology. Our dream?
A massive acquisition strategy to populate a vast archive of imagery. (example of
ASTER ~20 to 40 DEMs per sites since 2000)
 Radiometric performance
generally excellent.
But saturation on the slopes facing the sun and when fresh snow covers the ground
Everest (25 November 2012): 3%
Mont-Blanc: Between 0.2 and 10% of saturation
Iceland: no saturation DN max = 3703 (low sun angles)
2. Radiometric performance
t
Mont Blanc
Mont Blanc
Summit
Summit
Busy on
19
Busy
on! 19
August
2012
August 2012 !
2. Radiometric performance
t+32s
Mont Blanc
Summit
Busy on 19
August 2012 !
Radiometric performance
Trail to Mont Blanc
Summit
2 m accumulation stake
Radiometric performance. Saturation
Pléiades images of the Mont Blanc on 5 July 2013. Fresh snow and high sun
angle lead to 10% saturation (mostly Southeast facing slopes)
3. Vertical accuracy of Pléiades DEM
Wagnon et al.
The Cryosphere
Nov. 2013
 First published Pléiades DEM for glaciology
(Mera Glacier, Nepal)
No accurate ground control points (GCPs). So GCPs
derived from coarser resolution SPOT5 DEM and 2.5
m imagery (vertically and horizontally adjusted on
kinematic GPS measurements).
DGPS measurements performed within +/- 3 days of
the acquisitions of the Pléiades stereo-pair:
Mean/median dh ( , bias) = -0.93 m
Standard deviation ( dh = 1.02 m (N=445)
Pléiades images of Mera Glacier and,
in blue, location of the GPS
measurements acquired to assess the
vertical accuracy of the DEM
 Other similar assessments (with 5-10 accurate
GCPs)
Andes. Agua Negra. = -0.03 m ( =1.13 m,
N>5000)
Andes. Tronador. = 0.15 m ( =1.07 m, N=2301)
Mont Blanc-2012. = 0.97 m ( =0.67 m, N=491)
Mont Blanc-2013. = 0.08 m ( =0.55 m, N=460)
Comparison to Lidar data. Case study in Iceland
LIDAR data: acquired in August 2011 on Tungnafellsjökull (Iceland). Lidar
campaigns to provide a snapshot of the topography all Icelandic ice masses
(total area > 10000 km²). Campaigns during 2007-2012. 2 m by 2 m DEMs.
Johannesson et al.
Annals Glaciol.
2013
Pléiades stereo-pair : 10 October 2013. B/H = 0.45
Processing: 19 GCPs off glacier extracted from a shaded relief image of Lidar DEM
Statistics off glaciers (pixels for which dh exceed +/- 10 m are excluded)
= -0.3 m ; =1.2 m ; N=3 754 635
Pléiades 10 October 2013
Elevation changes between
August 2011 (Lidar) and October
2013 (Pléiades).
(on glaciers) = -1.65 m
Pléiades DEMs vs. Lidar. Iceland.
Necessity of ground control points?
Pléiades Shift
Shift
Mean dh
DEM
Easting Northing OFF ice
(m)
(m)
(m)
Std dev
OFF ice
(m)
Mean dh
ON ice
19 GCPs
1.8
-0.7
-0.2
1.1
-1.55
No GCP
2.9
-1.3
2.9
1.1
-1.55
1 GCP
2.0
-0.7
-0.1
1.1
-1.56
Statistics on the horizontal shift and the elevation difference (off and on glaciers)
between different Pléiades DEM and the Lidar DEM
- Larger horizontal shift without GCP + Mean vertical bias of about 3 m.
- One good GCP is sufficient to remove most of the horizontal and vertical biases
- After horizontal and vertical adjustment all DEM lead to very similar elevation
changes on glaciers
Thinning of Mont Blanc glaciers 2003-2012
About 60 m of
thinning for the tongue
of Mer de Glace and
Argentière glaciers
Maximun thinning of 110
m in only 9 years!
Glacier outlines are from Paul
et al., AoG, 2009
Mean ice thinning -10.6 m
Mass balance -1 m w.e./a
Elevation differences between 21 August 2003 (SPOT5) and 19 August 2012 (Pléiades)
Thinning of Mont Blanc glaciers 2003-2012
GPS: -14.4
SAT: -15.9
GPS: -33.4
SAT: -32.6
GPS: -14.9
SAT: -16.2
GPS: -37.0
SAT: -36.5
GPS: -17.0
SAT: -16.0
GPS: -38.6
SAT: -40.0
GPS: -27.8
SAT: -33.3
GPS: -49.2
SAT: -47.0
SPOT5 image of the Mer de Glace (left) and Argentière (right) glaciers and location of the
transverse profiles where GPS data are repeated every year by LGGE.
GPS: field data; SAT = satellite-derived elevation changes.
Mean difference = -0.6 m; stddev = 2.4 m
4. Glacier velocity mapping using repeat Pléiades
2 avril 2012
Animation showing the displacements of surface features on glaciers of the Tronador volcano
4. Glacier velocity mapping using repeat Pléiades
21 avril 2012
Animation showing the displacements of surface features on glaciers of the Tronador volcano
4. Glacier velocity mapping using repeat Pléiades
Cartographie des vitesses des glaciers sur le Volcan Tronador (Ruiz et al., in prep) entre le 7 mars et
le 2 avril 2012
Pléiades in glaciology: first conclusions
 Radiometry
12 bits encoding is key for glaciologists
 Data availability
We hope a large archive of Pléiades images will be built
We look forward to test SPOT6/SPOT7 stereo data!
 Vertical accuracy
vs DGPS and Lidar data = error of about 1 m (at 1-sigma) with good GCPs
Vertical bias can be larger without GCPs, at least with our commercial software.
Comparison are underway with soft from IGN and CMLA/CNES.
Strong interest of the community to receive DEMs and not raw images (see the SPIRIT
project for SPOT5, now more than 80 publications).
The scientific community has expressed during the recent CNES prospective the need for a
continuous topographic scanning of the Earth surface. Z-Earth is one possible solution
 Acknowledgments




Recette Thématique Utilisateur from CNES
Pléiades User group from Astrium Geo-information Service (IANIGLA data)
ISIS program from CNES (Icelandic and Astrolabe data)
Fundings from TOSCA and from the Pirletta fundation
Elevation changes between April 2013 (GPS) – October 2013 (Pléiades)
Summer elevation changes vs.
Altitude. White dot = field data
 We are now in position to
Map of summer glacier elevation changes
Mean dh = -3.1 m (standard deviation = 0.9 m)
map the pattern of snow
thickness. If the density of the
snow layer can be inferred we
will be able to measure the
seasonal mass balance of
glaciers
Polar Ice Sheets: Greenland and Antarctica
Peninsula
Antarctic Ice Sheet :
Area = 12 * 106 km2
Mean thickness = 2200 m
SLE = ~60 m
View of the Arctic region.
Greenland ice sheet: SLE = 7 m
Ice sheet volume changes
Map of surface elevation changes for
Antarctica 2002-2010. Flament & Remy,
2012
ERS, ENVISAT, ICESAT altimetry
Very weak signal (2 cm/a = .3mm/a
SLE) and lack of coverage toward to
coast where most of the losses are
concentrated
Map of surface elevation changes for
glaciers of the Larsen B area of the
Antarctic Peninsula. Differencing of ASTER
and SPOT5 DEMs. Berthier et al., 2012
This small region (about 3000 km²
or 1/5000 of the ice sheet) is
responsible for 5% of the losses

Download Report