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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.

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Active layer thaw depth

  • 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.