1) A field study was conducted in Adventdalen valley, Svalbard to measure active layer thaw depth across ice-wedge polygon networks of varying sizes. 2) Over 120 measurements of active layer depth were taken and GPS coordinates were recorded. A digital elevation model was also constructed. 3) Kriging geostatistical analysis showed active layer was on average 0.41m deep and depth varied somewhat with polygon size, being slightly shallower under larger polygons. Vegetation cover influences thaw depth but water infiltration into ice wedges may also impact the process.

1. ICE-WEDGE POLYGONAL NETWORKS AND DEPTH OF ACTIVE LAYER THAW,
A CASE STUDY IN SVALBARD, NORWAY
IVCONFERENCIA
LOUSADA M. (1,3), CARDOSO M. (2) , SARAIVA J. (1,3), PINA P. (1), VIEIRA G. (2) CHRISTIANSEN H. H. (3) PORTUGUESA
(1) Instituto Superior Técnico, Lisboa, Portugal, (2) CEG / IGOT, Lisboa, Portugal, (3) UNIS, Longyearbyen, Norway. CIENCIAS
POLARES
1.INTRODUCTION
The Adventdalen valley in Svalbard contains approximately 5 km2 of complex formations of thermal contraction polygon networks.
To test an eventual relation between the active layer thaw depth and polygon size, a field campaign was made in Adventdalen, on
August 2012. The aim was to obtain measurements of thaw depth in several transects on a network with a range of different
polygon sizes and obtain from Kriging, a geostatistical interpolation method, a model of the lower surface of the active layer below
this network.
2.METHODS
In the framework of the ANAPOLIS project [1], 120 networks along the Adventdalen valley were SURVEY A 87 points with coordinates (x,y,Z)
digitized in a GIS over images from the Norwegian Polar Institute (NPI), with 4bands, (RGB-NIR) and 20 obtained with a DGPS along several transects. On
cm/pixel of spatial resolution. One network with easy accessibility and considerably varied polygon each coordinated point a measurement of the active
sizes was chosen to conduct a field survey of the active layer depth. On these data, geostatistics layer depth was made.
models of interpolation by kriging were applied to obtain a surface the active layer depth.
SURVEY B Several transects were made with a
SURVEY A SURVEY B DGPS, resulting in 937 coordinated points (x,y,z), to
construct a topographic grid and generate an accurate
Digital Terrain Model of this network.
EQUIPMENT:
A B C
Digitized Polygons, ArcGis© Desktop Active Layer Depth and geolocation (DGPS) Surface topographyy geolocation (DGPS)
10.0, over NPI Images A-Active layer probe B- Trimble® base antenna C-Trimble® GPS receptor
3.RESULTS Trend projections of SURVEY A on the Surface (Z) elevation (m) SURVEY A
DTM Generated from SURVEY B, (2m/ pixel) a.s.l.
Profile cuts on active layer depth kriging surface Trend projections of SURVEY A on the active layer depth
measurements (Cm) Ground surface (topography) modeled through ordinary kriging, using the same points of the
C figure below, but using the elevation a.s.l. coordinate (Z) from DGPS. The left image shows the
East–West trend line
A polygons on the network, the image on the right shows the locations of the measurements.
SURVEY A
D B
A Gaussian model on a variogram of the active layer depth data
showed an isotropic trend at 320 degrees.
Areas (m2)of polygons intersecting profiles A.L. Depths (Cm) extracted from kriging along
the profiles
MIN : 20 MIN : -0.487
MAX: 336 320o MAX: -0.367 Mean Line
Count:118
Count:74 MEAN:89.7 MEAN: -0.410
STD: 51.3 STD: 0.025
Profile AB
50o
MIN : 33 MIN : -0.655 Profile CD
MAX: 1203 Count:118 MAX: -0.359
Count:36 MEAN:205.3 MEAN: -0.457
STD: 226.6 STD: 0.073 Surface of active layer thaw depth, modeled through kriging, with input of survey A,
measurements of depth. The left image shows the polygons on the network, the image on
the right, with shading, is superimposed with the location of the measurements.
4. CONCLUSIONS Some authors sustain that vegetation cover protects active layer from
thawing [2]. Vegetation mapping and ground–truth (geolocation), were also obtained in this
campaign to construct training areas and perform supervised classifications, these data are still under
analysis. Nevertheless on the field, with a printed unsupervised classification, similar vegetation was References:
identified in polygons with different sizes. Major differences were found inside ice-wedges where [1] Pina P., Vieira G., Christiansen H.H., Barata T., Saraiva J., Bandeira L., Lira C., Benavente N., Mora C., Neves
M., Jorge M., Ferreira A., 2010, Analysis of polygonal terrains on Mars based on Svalbard analogues, LPSC2010-
liquid water was abundant. Vegetation cover on ice-wedge polygons has its influence, nonetheless it’s Lunar and Planetary Science XLI, Abs #1372, Lunar and Planetary Institute, Houston, TX, USA.
also conceivable there’s a feedback in this process. The time the water takes to infiltrate ice wedges [2] Tolgensbakk J., Sørbel L., Høgvard K., 2000, Adventdalen, Geomorphological and Quarternary Geological
map, Svalbard 1:100,000, Spitsbergen sheet C9Q, Norsk Polarinstitutt, Temakart nr. 32.
in the permafrost with a thinner active layer depth must be considerably less than in cases where this
layer is thicker. Meanwhile during the process (thicker layer), more water is retained in the thawed Acknowledgments: Caixa Geral de Depósitos, Professor Hanne H. Christiansen, The University Centre in
Svalbard (UNIS) and FCT, ANAPOLIS project PTDC/CTE-SPA/099041/2008.
soil and less water infiltrates in the frost wedge, thus leading to a slower process of contraction.