Description: Permafrost thaw has been observed at several locations across the pan-Arctic in recent decades, yet the pan-Arctic extent and potential spatial-temporal variations in thaw are poorly constrained. Thawing of ice-rich permafrost can be inferred and quantified with satellite imagery due to the subsequent differential ground subsidence and erosion that in turn affects land surface cover. Information contained within existing and rapidly growing collections of high-resolution satellite imagery (Big Imagery) is here extracted across the Arctic region through a collaboration between software engineers, computer- and earth scientists. More specifically, we are a) developing geospatial data down to sub-meter resolution, and also b) enabling discovery and knowledge-generation through visualization tools. This cyberinfrastructure platform, the Permafrost Discovery Gateway (PDG), is being designed with input from users of the PDG, e.g. primarily the Arctic earth science community but also the general public. The PDG builds upon other NSF supported data management resources (Arctic Data Center and Clowder) and the Fluid Earth Viewer. The Fluid Earth Viewer, which is the first visualization tool implemented into the PDG, was initially created for the public to explore atmospheric and oceanographic visualizations and is here modified to support permafrost geospatial products, and a number of community built analytic tools to identify permafrost artifacts within satellite imagery. The effort also includes workflow optimization of remote sensing code for pan-Arctic sub-meter scale mapping of ice-wedge polygons from optical imagery. We are additionally actively engaging with the user-community to ensure that the PDG becomes useful, both in terms of the type of data contained within the PDG and the design of the visualization tools. The PDG has the potential to fill key Arctic science gaps, such as bridging plot to pan-Arctic scale findings, while also serving as a resource informing decisions regarding the economy, security, and resilience of the Arctic region.

Description: Permafrost thaw has been observed at several locations across the pan-Arctic in recent decades, yet the pan-Arctic extent and potential spatial-temporal variations in thaw are poorly constrained. Thawing of ice-rich permafrost can be inferred and quantified with satellite imagery due to the subsequent differential ground subsidence and erosion that also affects land surface cover, storage and flow of water, sediment, and nutrients. However, a lack of supporting cyberinfrastructure necessary to harness information from the existing and rapidly growing collection of high-resolution satellite imagery (Big Imagery) has limited our advances in understanding the nature of pan-Arctic permafrost degradation. In the coming four years, we will empower the broader Arctic community with a cyberinfrastructure platform, the Permafrost Discovery Gateway (PDG), aimed at making Big Imagery permafrost information accessible and discoverable through novel visualization and analysis tools designed with input from users of the PDG, e.g. the diverse peoples living, working, and/or studying in the Arctic. From the start of the project, we will engage the user-community through in-person and online meetings to ensure effective development of permafrost Big Imagery products for archiving, processing, analyzing, and visualizing. The framework will utilize existing resources, such as the (1) NSF supported data management resources the Arctic Data Center and Clowder, (2) web application visualization tools (Fluid Earth Viewer, Google Earth, and Gapminder Foundation), (3) high performance computing resources (XSEDE, Google Earth Engine etc.), and (4) and satellite imagery (Polar Geospatial Center, Landsat, Sentinel, and Planet). The PDG will include the management of ingesting remote sensing big data into machine and deep learning models. We welcome collaborations with national and international Native, industry, and academic organizations and individuals to ensure broad community engagement and dissemination. The PDG will enable diverse peoples to contribute to and have access to pan-Arctic permafrost knowledge, which can immediately inform the economy, security, and resilience of the Nation, the Arctic region, and the globe with respect to pan-Arctic change.

Description: The task of the ESA Data User Element DUE PERMAFROST project is to build-up an Earth Observation service for permafrost applications with extensive involvement of the permafrost research community. The DUE PERMAFROST remote sensing products are ‘Land Surface Temperature’ (LST), ‘Surface Soil Moisture’ (SSM), ‘Frozen/ Thawed Surface Status’ (Freeze/Thaw), ‘Terrain’, ‘Land Cover’ (LC), and ‘Surface Waters’. A major component is the evaluation of the DUE PERMAFROST products to test their scientific validity for high-latitude permafrost landscapes. There are no standard evaluation methods for this range of remote sensing products, specifically not for these latitudes. Evaluation experiments and intercomparison is done on a case-by-case basis, adding value and experience in validating products for these regions. A significant challenge in the evaluation of remote sensing products for high-latitude permafrost landscapes are the very sparse ground data. We relay on ground data provided by the Users and by international programmes. The primary international programme is the Global Terrestrial Network for Permafrost (GTN-P) initiated by the International Permafrost Association (IPA). Leading projects are the networks of the 'Circumpolar Active Layer Monitoring' (CALM) and the 'Thermal State of Permafrost' (TSP). Prime sites for testing methods and scaling are the long-term Russian-German Samoylov Station in the Lena River Delta (Arctic Siberia), and the tundra and taiga-tundra transition region in Western Siberia (RU). The results of the first evaluations of LST, SSM and Freeze/ Thaw using GTN-P and User’s data show the usability of the DUE PERMAFROST products for high-latitude permafrost landscapes.

Description: The task of the ESA Data User Element (DUE) Permafrost project is to build up an Earth Observation service for permafrost applications with extensive involvement of the permafrost research community. The DUE Permafrost remote sensing products are ‘Land Surface Temperature’ (LST), ‘Surface Soil Moisture’ (SSM), ‘Frozen/ Thawed Surface Status’ (Freeze/Thaw), ‘Terrain’, ‘Land Cover’ (LC), and ‘Surface Waters’. A major component is the evaluation of the DUE Permafrost products to test their scientific validity for high-latitude permafrost landscapes. There are no standard evaluation methods for this range of remote sensing products, specifically not for these latitudes. Evaluation experiments and inter-comparison is done on a case-by-case basis, adding value and experience in validating products for these regions. A significant challenge in the evaluation of remote sensing products for high-latitude permafrost landscapes are the very sparse ground data. We rely on ground data provided by the Users and by international programmes. The primary international programme is the Global Terrestrial Network for Permafrost (GTN-P) initiated by the International Permafrost Association (IPA). Leading projects are the networks of the ‘Circumpolar Active Layer Monitoring’ (CALM) and the ‘Thermal State of Permafrost’ (TSP). Prime sites for testing methods and scaling are the long-term Russian-German Samoylov Station in the Lena River Delta (Arctic Siberia), and the tundra and taiga-tundra transition regions in Western Siberia (RU). The results of the first evaluations of LST, SSM and Freeze/ Thaw using GTN-P and User’s data show the usability of the DUE Perma-frost products for high-latitude permafrost landscapes. The DUE Permafrost remote sensing products will be adapted as drivers, validation data and as newly available external input data for permafrost and climate models.

Description: The ESA DUE Permafrost project (2009-2011) is developing a suite of parameters indicative of the subsurface phenomenon permafrost using satellite remote sensing: Land Surface Temperature (LST), Surface Soil Moisture (SSM), Surface Frozen and Thawed State (Freeze/Thaw), Terrain, Land Cover (LC), and Surface Water (SW). Snow parameters (Snow Extent and Snow Water Equivalent) are being developed through the DUE GlobSnow project, Global Snow Monitoring for Climate Research (2008-2011). The final DUE Permafrost remote sensing products cover the years 2007 to 2011 with a circumpolar coverage that will soon be released (early 2012), and then be used to analyze the temporal dynamics and map the spatial patterns of indicators. Further information is available at www.ipf.tuwien.ac.at/ permafrost. Since the beginning, scientific stakeholders and the International Permafrost Association (IPA) have been involved in the science and implementation plan. Interactive international user workshops took place in 2010 at the Technical University of Vienna, Vienna (AT), and in 2011 at the International Arctic Research Center (IARC), Fairbanks, Alaska (US). This involvement and the ongoing evaluation of the indicators derived from remote sensing for the high-latitude permafrost regions make the DUE Permafrost products trustworthy for the permafrost and the climate research community. The adaption of the remote sensing products for the permafrost and climate modelling is experimental and highly dependent on the users’ involvement. For a few years already, the Geophysical Institute Permafrost Laboratory (GIPL), University of Alaska Fairbanks, US, (http://www.gi.alaska.edu/research/snowicepermafrost/Permafrost) has successfully demonstrated the value of using LST derived from remote sensing data for driving its permafrost models. Further experimental testing of the DUE Permafrost products for use by the modeling community (permafrost and climate) will range from (i) the evaluation of external data of the models, with modifying or providing new external data (e.g. tundra land cover, surface water ratio, soil distribution), to (ii) new drivers for regional models derived from remote sensing (e.g., LST), to (iii) the evaluation of the output data from the models (e.g. spatial patterns of moisture and temperature).

Description: The ESA Data User Element (DUE) Permafrost project provides a mid-to-long-term Earth observation service for permafrost remote sensing derived applications for Northern high-latitudinal permafrost areas. The DUE Permafrost remote sensing products are land surface temperature, surface soil moisture, frozen/thawed surface status, elevation, land cover and surface waters. A major component is the evaluation of the DUE Permafrost products to test their scientific validity for high-latitude permafrost landscapes. These case studies evaluate two DUE Permafrost products (MODIS Land Surface Temperature and ASCAT Surface State Flag) by comparing the results with field-based data obtained by the Global Terrestrial Network of Permafrost (GTN-P). First results showed good correlation which suggests that the DUE Permafrost approach is a promising one for long-term monitoring of permafrost surface conditions. Furthermore it demonstrates the great benefit of freely available ground truth databases for the evaluation of remote sensing derived products.

Description: The task of the ESA DUE Permafrost project is to build up an Earth observation service for high-latitudinal permafrost applications with extensive involvement of the permafrost research community. The DUE Permafrost products derived from remote sensing are land surface temperature (LST), surface soil moisture (SSM), surface frozen and thawed state (freeze/ thaw), terrain, land cover, and surface waters. Weekly and monthly averages for most of the DUE Permafrost products will be made available for the years 2007-2010. The DUE Permafrost products are provided for the circumpolar permafrost area (north of 55°N) with 25 km spatial resolution. In addition, regional products with higher spatial resolution (300-1000 m/ pixel) were developed for five case study regions. These regions are: (1) the Laptev Sea and Eastern Siberian Sea Region (RU, continuous very cold permafrost/ tundra), (2) the Yakutsk Region (RU, continuous cold permafrost/ taiga), (3) the Western Siberian transect including Yamal Peninsula and Ob Region (RU, continuous to discontinuous/ taiga-tundra), (4) the Alaska Highway Transect (US, continuous to discontinuous/ taiga-tundra), and (5) the Mackenzie Delta and Valley Transect (CA, continuous to discontinuous/ taiga-tundra). The challenge of the programme is to adapt remote sensing products that are well established and tested in agricultural low and mid-latitudinal areas for highly heterogeneous taiga/ tundra permafrost landscapes in arctic regions. Ground data is essential for the evaluation of DUE Permafrost products and is provided by user groups and global networks. A major part of the DUE Permafrost core user group is contributing to GTN-P, the Global Terrestrial Network of Permafrost. Its main programmes, the Circumpolar Active Layer Monitoring (CALM) and the Thermal State of Permafrost (TSP) have been thoroughly overhauled during the last International Polar Year (2007-2008). Their spatial coverage has been extended to provide a true circumpolar network. Ground data ranges from active layer- and snow depths, to air-, ground-, and borehole temperature data as well as soil moisture measurements and the description of landform and vegetation. The GTN-P sites, with their position in different permafrost zones in the DUE Permafrost case study regions, are highly suitable for the evaluation of DUE Permafrost remote sensing products. Air and surface temperatures with high-temporal resolution are available for three GTN-P sites in Siberia and compared to LST products. Daily average GTN-P borehole- and air temperature data for 22 sites in Alaska and 6 sites in Western Siberia were used to validate surface frozen and thawed state. The preliminary results are promising. In addition, landform and vegetation descriptions of circumpolar GTN-P sites are used for the evaluation of global ‘landcover’ remote-sensing datasets like GlobeCover, Landcover2000 and EcoClimap – global datasets used as input for climate modeling.