Pan-arctic land cover mapping and fire assessment for the ESA Data User Element Permafrost

M. Urban, S. Hese, M. Herold, S. Pöcking, C. Schmullius

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)


The paper presents first results of a pan-boreal scale land cover harmonization and classification. A methodology is presented that combines global and regional vegetation datasets to extract percentage cover information for different vegetation physiognomy and barren for the pan-arctic region within the ESA Data User Element Permafrost. Based on the legend description of each land cover product the datasets are harmonized into four LCCS (Land Cover Classification System) classifiers which are linked to the MODIS Vegetation Continuous Field (VCF) product. Harmonized land cover and Vegetation Continuous Fields products are combined to derive a best estimate of percentage cover information for trees, shrubs, herbaceous and barren areas for Russia. Future work will concentrate on the expansion of the developed methodology to the pan-arctic scale. Since the vegetation builds an isolation layer, which protects the permafrost from heat and cold temperatures, a degradation of this layer due to fire strongly influences the frozen conditions in the soil. Fire is an important disturbance factor which affects vast processes and dynamics in ecosystems (e.g. biomass, biodiversity, hydrology, etc.). Especially in North Eurasia the fire occupancy has dramatically increased in the last 50 years and has doubled in the 1990s with respect to the last five decades. A comparison of global and regional fire products has shown discrepancies between the amounts of burn scars detected by different algorithms and satellite data
Original languageEnglish
Pages (from-to)283-293
JournalPhotogrammetrie, Fernerkundung, Geoinformation
Issue number4
Publication statusPublished - 2010


  • carbon-cycle
  • vegetation
  • climate
  • avhrr
  • validation
  • emissions
  • products
  • wildfire
  • siberia
  • modis

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