Plant Functional Type (PFT) map over Siberia derived from GlobCover 2005 dataset, link to dataset in NetCDF format

High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover data sets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing Earth system models. Earth system models also require specific land cover classification systems based on plant functional types (PFTs), rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover data sets against one another and with auxiliary data to identify key uncertainties that contribute to variability in PFT classifications that would introduce errors in Earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, vegetation continuous fields (MODIS VCFs) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover data set, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFT maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT data set, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to represent the water and carbon cycles in northern latitudes better. Updated land cover data sets are critical for improving and maintaining the relevance of Earth system models for assessing climate and human impacts on biogeochemistry and biophysics.

A fractional vegetation cover remote sensing product on pan-arctic scale with link to geotiff image

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.

Pan-European land cover/use map for 2009

GlobCorine demonstrated an automatic service that can generate in a consistent way land cover / land use maps and land change indicators, based on a CLC-compatible legend. CLC is derived from a visual identification and classification of landscape objects using high resolution images. This methodology provides high thematic accuracy but limits the update rate since it is time-consuming. Therefore, the project evaluated the use of MERIS FR time series, processed automatically to provide a more frequent update of CLC-compatible maps. GlobCorine built upon the experience and resources available through the GlobCover project, to tune the classification chain and adapt it to the EEA needs, covering the pan-European area (including the Mediterranean basin and the European Russia), although the system could be potentially extendable globally. The project delivered two CLC-compatible pan-European land cover maps in less than two years, demonstrating efficient and quick production. The first map is based on Envisat MERIS fine resolution (300m) mode data acquired between end 2004 and mid 2006, while the second used full-year 2009 data. GlobCorine is an initiative of ESA with the partnership of EEA and is implemented by Universite' catholique de Louvain - UCL.