THE ESA DUE PERMAFROST PROJECT - A SERVICE FOR HIGH LATITUDE RESEARCH

Annett Bartsch

and ESA DUE Permafrost team∗

Frank Martin Seifert

European Space AgencyESRIN, Frascati, Italy

ABSTRACTPermafrost is an essential climate variable (ECV). It is a sub-surface phenomenon which cannot be directly measured withremotely sensed data. However, many parameters which in-� uence the ground thermal regime and surface indicators canbe captured with satellite data. Those are e.g. land surfacetemperature, land cover and snow parameters, soil moistureand terrain changes. The capabilities of currently availableremotely sensed datasets need to be assessed with respect tooperational monitoring and their value enhanced by a syn-ergistic use. A wide range of EO datasets have been inves-tigated and integrated in an information system within theDUE Permafrost project with extensive involvement of thepermafrost research community. This paper summarizes theachievements within the DUE Permafrost project and presentsthe design of the information system.

Index Terms— arctic, land surface temperature, terrainmapping, hydrology, vegetation mapping

1. INTRODUCTION

The objective of this project was to establish a permafrost-monitoring system based on satellite data. The goal of thePermafrost project was to demonstrate Earth Observation(EO) integrated services in the � eld of permafrost monitoringof the boreal zone with active participation of user organisa-tions, mainly from the scienti� c world. The project acted as aplatform to users and service providers in order to harmoniseinformation needs and develop a set of key tools to addressthem.

∗This study was carried out as part of the PERMAFROST project,which is funded by ESA’s Data User Element (DUE) program as acomponent of the Earth Observation Envelope Program (EOEP) (ESRINContr. No. 22185/09/I-OL) and co-ordinated by TU Wien. The team mem-bers are: A. Bartsch, V. Naeimi, D. Sabel, C. Paulik, S. Schlaffer, T. Melzer,T. Mistelbauer, C. Notegger and W. Wagner from Institute of Phorogram-metry and Remote Sensing, Vienna University of Technology (A. Bartschis also a recipient of a fellowship by the Austrian Science Fund (V150-N21).); B. Heim, K. Elger, J. Boike, T. Opel, G. Schwamborn from the Al-fred Wegener Institute of Polar and Marine Research, Potsdam, Germany;C. Duguay, A. Soliman and S. Hachem from the Interdisciplinary Centre onClimate Change, University of Waterloo, Canada; M. Urban, M. Voltersen,S. Pocking, S. Hese and C. Schmullius from Department of Remote Sensing,Friedrich-Schiller-University Jena, Jena, Germany; T. Strozzi, A. Wiesmannfrom Gamma Remote Sensing, Gumligen, Switzerland

The international permafrost research community re-quires easy access to end-products which provide informationon the current status of permafrost and add value to existingnetworks. Data interchange ability with respect to exist-ing data platforms such as the Arctic Portal and the NSIDCarchiving system is a basic requirement. This has been ad-dressed within DUE Permafrost and should be continued byfuture services.

The user community comprises institutions, organizationsand scientists from a wide range of subjects and interests. Cli-mate modelers as well as � eld investigators have contributedto the service development.

Fig. 1. Service scales and potential � eld of application

2. OBSERVATION STRATEGY

Permafrost is a subsurface phenomenon and cannot be di-rectly observed with satellite data. Yet, monitoring can bedone based on indicators and via permafrost models. Indi-cators are especially thermokarst lake dynamics and surfaceelevation changes. Those phenomena need to be observed ona local scale. Regional to circumpolar monitoring requiresthe use of permafrost models. Relevant satellite-observableparameters are land surface temperature (LST), snow extent,snow water equivalent (SWE), vegetation, and soil moisture.Existing services have been integrated into the Permafrostprocessing system - Earth Observation (PEO) and adapted tothe needs of permafrost modelling at high latitudes [1]. Allsatellite datasets are made available via a data portal (incl.WebGIS) which will tie into the permafrost information sys-tem of the International Permafrost Association (IPA).

The implemented service is based on a comprehensive

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user requirements survey and follows a multi-scale concept.Pan-boreal arctic products cover all permafrost affected ar-eas north of 55 N. Five regional service cases have beenidenti� ed based on ground data availability: Alaska NorthSlope/Borehole transect, Mackenzie delta and borehole tran-sect, Ob-Esturay including Yamal-peninsula, Laptev sea re-gions including East Taymir, Lena-Delta and Cherskii, andcentral Yakutia. Temporal coverage varies from product toproduct. The overlapping period for all products is 2007 -2009.

3. USER INVOLVEMENT

A comprehensive user survey has been carried out. It includednot only the collection of requirements but also ground dataavailability. The location and extent of service case areas hasbeen de� ned based on this user feedback. The � rst DUE Per-mafrost User Workshop was held in May 2010 in Vienna as anof� cial side-event of the EGU. The observation strategy for allproducts and regions was presented by the project team andreviewed with the participants. The second DUE PermafrostUser Workshop has been hosted and � nancially supported bythe International Arctic Research Centre, IARC, Universityof Alaska Fairbanks (US) in March 2011. The third and � nalDUE Permafrost User Workshop took place at AWI Potsdam(DE) in February 2012 back-to-back with the � nal ESA ALA-NIS User Workshop with more than 60 participants.

4. THE SERVICE

The Processing System follows a modular approach. This ap-proach was selected to take into account the different datasources and product contributors and to have an easy to adaptsolution. Automated processing chains for database updatehave been implemented for land surface dynamic productsavailable at a suf� ciently mature level: land surface temper-ature, relative surface soil moisture, surface status and openwater. Static components (no regular updates, although timeseries partly available) are land cover and terrain parameters.

4.1. Land Surface Temperature

The rate at which permafrost evolves can be determined bystudying its thermal regime, which is dependent on surfacetemperature. Surface temperature is a key parameter as itgoverns the surface energy budget and the thickness of thepermafrost active layer. The LST processing subsystem inte-grates the LST level 2 products from MODIS and AATSR dis-tributed by NASA and ESA, respectively [2]. Post-processingfunctions supply UW level-3 weekly and monthly LST prod-ucts for regional and pan-Arctic scales. The main compo-nents of the processing subsystem are: Interpolation to reg-ular grid, Spatial averaging, Temporal averaging and weekly

LST. The weekly LSTs are calculated from all satellite over-passes within a seven- day period based on aggregation ofdaily products. It is available for each day based on a 7-daysliding time window giving most recent observations highestpriority following the GlobSnow convention. The monthlyLSTs are calculated from all satellite overpasses within a cal-endar month period.

4.2. Landsurface Hydrology

Variations in parameters which impact heat conductivityplay a role in the reaction of the subsurface frozen groundto changes in the atmosphere. Soil moisture information simportant for active layer development and one of the keyparameter for modelling of permafrost extent [3].

The ASCAT Level 2 product including soil moisture dataare produced by EUMETSAT in near-real time following themethod by [4, 5]. The ASCAT SSM DUE Permafrost prod-uct is the result of an improved SSM retrieval algorithm. TheSSM Product is delivered with a weekly temporal resolutionand 25km, Geo-TIFF/NetCDF format, spatial resolution inEASE Grid projection [6]. Data are masked for frozen groundconditions also based on MetOp ASCAT[7] in cooperationwith the ESA STSE ALANIS-Methane project in order to re-� ect daily status and also snowmelt conditions.

A regional service for surface soil moisture (1km), openwater summer extent (150m, [8]) and surface status (1km,citepark11) has been implemented based on ENVISAT ASARwith the TU Wien SGRT [9]. For application at high latitudesthe following adjustments to the algorithm have been imple-mented: (1) Processing (with NEST) in polar stereographicprojection and storage of data. (2) A dry reference correc-tion algorithm has been implemented in order to account forpermanently wet areas [10]; (3) Implementation of a post pro-cessing function for the production of weekly composites ofsurface soil moisture and enhanced masking. Availability ofASAR Global Mode and Wide Swath data is highly variablein the high latitudes and needs to be accounted for. Auxiliarymaps with numbers of measurements have been therefore de-rived as quality indicator.

4.3. Terrain

Information on surface topography and on change in surfacetopography is fundamental over permafrost regions. Ice-richlayers are usually close to the surface and are the � rst tobe melted by increases in downward heat energy � ux due tochanges in the surface energy balance. The immediate resultis subsidence. A DEM (3 arcsec spatial resolution) is com-piled at pan-arctic scale from available data sources and de-rived at local scale from optical stereoscopic pairs and SARinterferometry (InSAR) [11]. SAR interferometry proofed tobe a reliable tool to detect seasonal surface subsidence due topermafrost thaw on many regions thanks to the short repeat

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Service Case regions Product Temporal

resolu�on

Spa�al

resolu�on

Pan arc�c

extent Alaska Mackenzie Laptev

Sea

Central

Yaku�a

Ob

Estuary/Yamal

Polar Bear

Pass (local)

Years/ Comments

LST MODIS Weekly 1 km X X X X X 2007 – Sep. 2010

monthly 1 km X X X X X 2007 – Sep. 2010

Weekly 25 km X 2007 – 2009

monthly 25 km x 2000 – 2010

LST AATSR Weekly 25 km X 2008

Monthly 25 km x 2005-2009

ASCAT

SSM/FT

weekly 25 km X 2007 – Sept 2010

ASAR SSM Weekly 1 km X X X X X 2005 - 2010

ASAR FT annualy 1 km X X x x X 2005 – 2010

ASAR WB annually 150 m X X X (X) X 2007 - 2010

DEM once 3 arcsec X

Harmonized

Landcover

once 1 km X

Combined

fires

monthly 1 km x 1996-2009

Local WB Once 5 m x x 2009

Local land

cover

once 5 m x x 2009

Local DEM once 10 m x x 2007 - 2010

Local

Subsidence

x x x

Fig. 2. DUE Permafrost product overview

interval of 11 days of TerraSAR-X. The time-series of dis-placement highlighted that subsidence is occurring within arelatively short time period.

4.4. Landcover

Vegetation is commonly incorporated into spatial modelspredicting permafrost distribution. The land cover and thesurface texture are affected by the seasonal thawing dynamicsof the active layer. The yearly MODIS land cover productwith a spatial resolution of 500 m, the GlobCover land covermap, SYNMAP and MODIS VCF (vegetation continuous� eld) have been combined into one land cover dataset [12].The datasets consist of four layers, describing the percent-age information for each class, with a spatial resolution of1 km. By summarizing all four layers each pixel ends upwith a value of 100%. The harmonized land cover map wasimproved by using the Circumpolar Arctic Vegetation Map1.

To represent the seasonal vegetation dynamics on pan-arctic scale the LAI product from GlobCarbon with a spatialresolution of 1 km was utilized. Pan-arctic � re information ispresented by using different burned area and active � re prod-ucts (MODIS, GlobCarbon, Terra Norte, ATSR World FireAtlas).

Subject of the local land cover analysis were three differ-ent test sites: Central Yakutsk and Lena river delta (Siberia)as well as North Slope (Alaska). The land cover classi� cationwas done by utilizing an object based classi� cation approach[13]. Object characteristics (shape, spectral properties and in-formation within different hierarchical object levels) are used

1www.geobotany.uaf.edu/cavm

to analyze vegetation class properties and to assign each im-age object to a thematic class. Land cover was analyzed usingRapidEye data.

5. SERVICE ASSESSMENT AND ADDED VALUEDEMONSTRATION

Ground measurements in arctic permafrost regions involvechallenging logistics and are networked on multidisciplinaryand circum-arctic level by the Permafrost community. A ma-jor part of the DUE Permafrost core user group is contributingto the Global Terrestrial Network for Permafrost (GTN-P).Ground data from GTN-P was used for the evaluation of DUEPermafrost products MODIS LST (land surface temperature)and ASCAT SSF (Surface State Flag for the surface frozenand thawed ground) [7, 14, 15, 16]. The added value of satel-lite products for permafrost monitoring has been discussed inthe frame work of the � nal user workshop. An abstract vol-ume has been compiled and made available online.

6. DATA PORTAL

A data portal has been setup for dissemination. GeoServerextensions which have speci� cally been developed in thisproject are the (1) support of temporal rasters, (2) pole cen-tered coordinate systems and (3) user de� ned map styling.The system is interoperable with many GIS tools since alldata are available through services based on internationalstandards (OGC, ISO). All datasets including product guidesare available through the website. The full dataset will beadditionally made available via the information system PAN-

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GAEA, an Open Access library aimed at archiving, publish-ing and distributing georeferenced data from earth systemresearch. The system guarantees long-term availability of itscontent through a commitment of the operating institutions.

The DUE Permafrost regional and pan-arctic dataset DOIisdoi:10.1594/PANGAEA.780111

7. OUTLOOK

The data set will be exploited and further assessed as part ofthe FP7 project PAGE21: Changing Permafrost in the Arcticand its Global Effects in the 21st Century.2

8. REFERENCES

[1] A. Bartsch, A. Wiesmann, T. Strozzi, C. Schmullius,S. Hese, C. Duguay, B. Heim, and F. M. Seifert, “Im-plementation of a satellite data based permafrost infor-mation system - the DUE Permafrost project,” in Pro-ceedings of the ESA Living Planet Symposium, Bergen,2010.

[2] C. Duguay, S. Hachem, and A. Soliman, “The DUEPermafrost project - land surface temperature products:Overview and cross-comparison between MODIS andAATSR,” in ESA Living Planet Symposium, Bergen,2010.

[3] S. Marchenko, V. Romanovsky, and G. Tipenko, “Nu-merical modeling of spatial permafrost dynamics inAlaska,” in Proceedings of the Ninth International Sym-posium on Permafrost, Fairbanks, Alaska, 2008, pp.1125–1130.

[4] Vahid Naeimi, Zoltan Bartalis, and Wolfgang Wagner,“ASCAT soil moisture: An assessment of the data qual-ity and consistency with the ERS scatterometer her-itage,” Journal of Hydrometeorology, vol. 10, pp. 555–563, 2009.

[5] W. Wagner, G. Lemoine, and H. Rott, “A method for es-timating soil moisture from ERS scatterometer and soildata,” Remote Sensing of Environment, vol. 70, pp. 191–207, 1999.

[6] A. Bartsch, T. Melzer, K. Elger, and B. Heim, “Soilmoisture from metop ascat data at high latitudes,” inProceedings of the Tenth International Conference onPermafrost, 2012.

[7] V. Naeimi, C. Paulik, A. Bartsch, W. Wagner, R. Kidd,J. Boike, and K. Elger, “ASCAT Surface State Flag(SSF): Extracting information on surface freeze/thaw

2www.page21.eu

conditions from backscatter data using an empiricalthreshold-analysis algorithm,” IEEE Transactions onGeoscience and Remote Sensing, in press.

[8] A. Bartsch, C. Pathe, W. Wagner, and K. Scipal, “Detec-tion of permanent open water surfaces in central Siberiawith ENVISAT ASAR wide swath data with special em-phasis on the estimation of methane � uxes from tundrawetlands,” Hydrology Research, vol. 39, no. 2, pp. 89–100, 2008.

[9] Daniel Sabel, Zoltan Bartalis, Wolfgang Wagner,Marcela Doubkova, and Jean-Pierre Klein, “Develop-ment of a global backscatter model in support to thesentinel-1 mission design,” Remote Sensing of Environ-ment, vol. 120, pp. 102–112, 2012.

[10] A. Bartsch, D. Sabel, W. Wagner, and S.-E. Park, “Con-siderations for derivation and use of soil moisture datafrom active microwave satellites at high latitudes,” inGeoscience and Remote Sensing Symposium (IGARSS),2011 IEEE International, 2012, pp. 3132–3135.

[11] T. Strozzi, U. Wegmuller, R. Delaloye, H. Raetzo,A. Kos, A. Bartsch, and C. Lambiel, “Radar inter-ferometric observations of permafrost related surfacedeformation,” in European Permafrost Conference,Longyearbyen, 2010.

[12] M. Urban, M. Herold, S. Hese, S. Pocking, andC. Schmullius, “Synergistic analysis of coarse resolu-tion vegetation and land cover data for permafrost moni-toring,” in ESA Living Planet Symposium, Bergen, 2010.

[13] S. Pocking, S. Hese, M. Urban, M. Herold, and Schmul-lius, “High resolution vegetation and water body map-ping in arctic permafrost regions,” in ESA Living PlanetSyposium, Bergen, 2010.

[14] B. Heim, J. Boike, M. Langer, S. Muster, J. Sobiech,K. Piel, and A. Bartsch, “The Lena River Delta, ArcticSiberia: An arctic ground data observatory of the DUEPermafrost project,” in ESA Living Planet Symposium,Bergen, 2010.

[15] B. Heim, A. Bartsch, K. Elger, H. Lantuit, J. Boike,S. Muster, M. Langer, C. Duguay, S. Hachem, A. Soli-man, C. Paulik, T. Strozzi, and F.-M. Seifert, “ESA DUEpermafrost: An earth observation (EO) permafrost mon-itoring system,” in EARSeL eProceedings, 2010, pp. 73–82.

[16] K. Elger, B. Heim, A. Bartsch, C. Paulik, C. Duguay,S. Hachem, A. Soliman, H. Lantuit, J. Boike, and F.-M. Seifert, “Evaluation of ESA DUE Permafrost re-mote sensing products using global permafrost networks(GTN-P),” in Proceedings of the Tenth InternationalConference on Permafrost, 2012.

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