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  • 1
    Publication Date: 2019-04-30
    Description: This dataset provides scaling information applicable to satellite derived coarse resolution surface soil moisture datasets following the approach by Wagner et al. (2008). It is based on ENVISAT ASAR data and can be utilized to apply the Metop ASCAT dataset (25 km) for local studies as well as to assess the representativeness of in-situ measurement sites and thus their potential for upscaling. The approach based on temporal stability (Wagner et al. 2008) consists of the assessment of the validity of the coarse resolution datasets at medium resolution (1 km, product is the so called 'scaling layer').
    Type: Dataset
    Format: text/tab-separated-values, 24 data points
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  • 2
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    PANGAEA
    In:  Supplement to: Widhalm, Barbara; Bartsch, Annett; Heim, Birgit (2015): A novel approach for the characterization of tundra wetland regions with C-band SAR satellite data. International Journal of Remote Sensing, 36(22), 5537-5556, https://doi.org/10.1080/01431161.2015.1101505
    Publication Date: 2019-02-11
    Description: A circumpolar representative and consistent wetland map is required for a range of applications ranging from upscaling of carbon fluxes and pools to climate modelling and wildlife habitat assessment. Currently available data sets lack sufficient accuracy and/or thematic detail in many regions of the Arctic. Synthetic aperture radar (SAR) data from satellites have already been shown to be suitable for wetland mapping. Envisat Advanced SAR (ASAR) provides global medium-resolution data which are examined with particular focus on spatial wetness patterns in this study. It was found that winter minimum backscatter values as well as their differences to summer minimum values reflect vegetation physiognomy units of certain wetness regimes. Low winter backscatter values are mostly found in areas vegetated by plant communities typically for wet regions in the tundra biome, due to low roughness and low volume scattering caused by the predominant vegetation. Summer to winter difference backscatter values, which in contrast to the winter values depend almost solely on soil moisture content, show expected higher values for wet regions. While the approach using difference values would seem more reasonable in order to delineate wetness patterns considering its direct link to soil moisture, it was found that a classification of winter minimum backscatter values is more applicable in tundra regions due to its better separability into wetness classes. Previous approaches for wetland detection have investigated the impact of liquid water in the soil on backscatter conditions. In this study the absence of liquid water is utilized. Owing to a lack of comparable regional to circumpolar data with respect to thematic detail, a potential wetland map cannot directly be validated; however, one might claim the validity of such a product by comparison with vegetation maps, which hold some information on the wetness status of certain classes. It was shown that the Envisat ASAR-derived classes are related to wetland classes of conventional vegetation maps, indicating its applicability; 30% of the land area north of the treeline was identified as wetland while conventional maps recorded 1-7%.
    Type: Dataset
    Format: text/tab-separated-values, 8 data points
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  • 3
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    PANGAEA
    In:  Zentralanstalt für Meteorologie und Geodynamik, Wien
    Publication Date: 2019-04-30
    Description: Vegetation height has been derived from Sentinel-1 satellite data acquired in VV mode. Masking based on Sentinel-2 has been applied. Areas with NDVI 〈 0.4 are excluded for vegetation height retrieval in order to account for effects related to C-band scattering from rough and bare surfaces. Areas with VV 〈 -15.4 dB (and NDVI 〉 0.4) are flagged as well as indicator for anomalous high values in vegetation related indices with at the same time low vegetation height. The remaining land area is assigned vegetation heights up to 160 cm. All heights 〉 160 cm are excluded and labelled as a separate class. Covered areas are: Yamal peninsula (Russia), Usa Basin (Russia), Lena Delta (Russia), Kytalyk (Russia), Mackenzie Delta (Canada), Umiuaq (Canada), Barrow (Alaska), Teshekpuk (Alaska), Toolik (Alaska) and Seward peninsula (Alaska). For more Information see the product documentation.
    Type: Dataset
    Format: text/tab-separated-values, 80 data points
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  • 4
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    PANGAEA
    In:  Supplement to: Widhalm, Barbara; Bartsch, Annett; Roth, Achim; Leibman, Marina O (2018): Classification of Tundra Regions with Polarimetric Terrasar-X Data. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium,22-27 July 2018, Valencia, Spain, 8551-8554, https://doi.org/10.1109/IGARSS.2018.8518283
    Publication Date: 2019-02-23
    Description: Permafrost is an essential element of the cryosphere, which will be strongly affected by global warming. Although permafrost cannot be measured directly with remote sensing, many permafrost features are observable. Polarimetric information can be used in this context. Polarimetric data of TerraSAR-X is the basis for a local landcover classification presented here, which reflects different scattering mechanisms. The resulting classification aims on the identification of process areas and periglacial features such as thaw slumps (bare wet surfaces) and thaw lakes as well as wetland areas. The following regions are covered in the dataset: Barrow (Alaska), Mackenzie Delta (Canada), Kytalyk (Russia), Lena Delta (Russia), Vaskiny Dachi (Russia), Herschel Island (Canada).
    Type: Dataset
    Format: text/tab-separated-values, 30 data points
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  • 5
    Publication Date: 2018-09-27
    Type: Dataset
    Format: text/tab-separated-values, 726 data points
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  • 6
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    PANGAEA
    In:  Supplement to: Bartsch, Annett; Widhalm, Barbara; Kuhry, Peter; Hugelius, Gustaf; Palmtag, Juri; Siewert, Matthias Benjamin (2016): Can C-band synthetic aperture radar be used to estimate soil organic carbon storage in tundra? Biogeosciences, 13(19), 5453-5470, https://doi.org/10.5194/bg-13-5453-2016
    Publication Date: 2018-09-27
    Description: A new approach for the estimation of soil organic carbon (SOC) pools north of the tree line has been developed based on synthetic aperture radar (SAR; ENVISAT Advanced SAR Global Monitoring mode) data. SOC values are directly determined from backscatter values instead of upscaling using land cover or soil classes. The multi-mode capability of SAR allows application across scales. It can be shown that measurements in C band under frozen conditions represent vegetation and surface structure properties which relate to soil properties, specifically SOC. It is estimated that at least 29 Pg C is stored in the upper 30 cm of soils north of the tree line. This is approximately 25 % less than stocks derived from the soil-map-based Northern Circumpolar Soil Carbon Database (NCSCD). The total stored carbon is underestimated since the established empirical relationship is not valid for peatlands or strongly cryoturbated soils. The approach does, however, provide the first spatially consistent account of soil organic carbon across the Arctic. Furthermore, it could be shown that values obtained from 1 km resolution SAR correspond to accounts based on a high spatial resolution (2 m) land cover map over a study area of about 7 × 7 km in NE Siberia. The approach can be also potentially transferred to medium-resolution C-band SAR data such as ENVISAT ASAR Wide Swath with ~120 m resolution but it is in general limited to regions without woody vegetation. Global Monitoring-mode-derived SOC increases with unfrozen period length. This indicates the importance of this parameter for modelling of the spatial distribution of soil organic carbon storage.
    Type: Dataset
    Format: application/zip, 37.0 MBytes
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  • 7
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    PANGAEA
    In:  Zentralanstalt für Meteorologie und Geodynamik, Wien | Supplement to: Widhalm, Barbara; Bartsch, Annett; Goler, Robert (2018): Simplified Normalization of C-Band Synthetic Aperture Radar Data for Terrestrial Applications in High Latitude Environments. Remote Sensing, 10(4), 551, https://doi.org/10.3390/rs10040551
    Publication Date: 2019-04-30
    Description: Synthetic aperture radar (SAR) applications often require normalization to a common incidence angle. Angular signatures of radar backscatter depend on surface roughness and vegetation cover, and thus differ, from location to location. Comprehensive reference datasets are therefore required in heterogeneous landscapes. Multiple acquisitions from overlapping orbits with sufficient incidence angle range are processed in order to obtain parameters of the location specific normalization function. We propose a simpler method for C-band data, using single scenes only. It requires stable dielectric properties (no variations of liquid water content). This method is therefore applicable for frozen conditions. Winter C-band data have been shown of high value for a number of applications in high latitudes before. In this paper we explore the relationship of incidence angle and Sentinel-1 backscatter across the tundra to boreal transition zone. A linear relationship (coefficient of determination R2 = 0.64) can be found between backscatter and incidence angle dependence (slope of normalization function) as determined by multiple acquisitions on a pixel by pixel basis for typical land cover classes in these regions. This allows a simplified normalization and thus reduced processing effort for applications over larger areas. The following regions are covered in the dataset: Yamal peninsula (Russia), Usa Basin (Russia), Lena Delta (Russia), Mackenzie Delta (Canada), Barrow, Toolik and Teshekpuk Lake region (Alaska).
    Type: Dataset
    Format: text/tab-separated-values, 40 data points
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  • 8
    Publication Date: 2019-02-11
    Type: Dataset
    Format: text/tab-separated-values, 33 data points
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  • 9
    Publication Date: 2018-09-27
    Description: Thawing-induced cliff top retreat in permafrost landscapes is mainly due to thermo-erosion. Ground-ice-rich permafrost landscapes are specifically vulnerable to thermo-erosion and may show high degradation rates. Within the HGF Alliance Remote Sensing and the FP7 PAGE21 permafrost programs we investigated how SAR and optical remote sensing can contribute to the monitoring of erosion rates of ice-rich cliffs in Arctic Siberia (Lena Delta, Russia). We produced two different vector products: i) Intra-annual cliff top retreat based on TerraSAR-X (TSX) satellite data (2012-2014): High-temporal resolution time series of TSX satellite data allow the inter-annual and intra-annual monitoring of the upper cliff-line retreat also under bad weather conditions and continuous cloud coverage. This published SAR product contains the retreating upper cliff lines of a 1.5 km long part of eroding ice-rich coast of Kurungnakh Island in the central Lena Delta. The upper cliff line was mapped using a thresholding approach for images acquired in the years 2012, 2013 and 2014 for the months June (2013, 2014), July (2013, 2014), August (2012, 2013, 2014) and September (2013, 2014). The cliff top retreat vector product is called 'upper_cliff_TerraSAR-X'. While the 2014 cliff lines show a clear retreat of 2 to 3 m/month, the cliff top lines for 2012 and 2013 are not chronologically ordered. However, lines from the end of the season of a year are always close to the lines from the beginning of the next summer season, indicating low cliff retreat in winter. ii) 4-year cliff top retreat based on optical satellite data (2010-2014): Long-term cliff top retreat could be assessed with two high-spatial resolution optical satellite images (GeoEye-1, 2010-08-05 and Worldview-1, 2014-08-19). The cliff top retreat vector product is called 'upper_cliff_optical'. Results: The long-term cliff top retreat derived from optical satellite data are 35 m cliff retreat within 4 years. The higher-temporal resolution SAR data equivalently show long-term rates of 18 m within 2 years and nearly now degradation activities in winter but maximum erosion rates in summer months.The Intra-seasonal cliff top retreat lines from 2014 show a rate of 2 to 3 m per month.
    Type: Dataset
    Format: text/tab-separated-values, 6 data points
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  • 10
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    Vienna University of Technology (Institute of Photogrammetry and Remote Sensing)
    Publication Date: 2014-12-08
    Repository Name: EPIC Alfred Wegener Institut
    Type: PANGAEA Documentation , NonPeerReviewed
    Format: application/pdf
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