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VACCIA Action 2: Derivation of GMES-related remote sensing data


This action will provide Earth observation-based extended GMES services for FinLTSER environmental network points-of-interest, as a basis for the sector-specific assessment work in actions 5-13. The use of climate change –sensitive land cover information (including snow and phenology) in climate change studies will also be demonstrated.

Remote sensing provides extensive information on the state of earth's surface, either for instant needs or for long-term analyses. At SYKE, the maturity of remote sensing techniques relevant to the present topic is a good basis for multidisciplinary utilization of the provided EO-data. The aim of this action is to derive a new kind of joint data from existing datasets, which would contribute to the climate change assessments in a novel way. These datasets are created within three different GMES service elements with SYKE's involvement. These are GSE Polarview, GSE Marcoast and GSE Land. In the on-going Fast Track Land Monitoring precursor (CLC2006) SYKE produces the land information over Finland together with Finnish Forest Research Institute. Produced regional land cover information will be available 2009.

Methods employed

The Earth observation data is provided by several satellite-borne sensors: Terra/MODIS by NASA and Envisat MERIS by ESA. For temperature datasets, NOAA AVHRR data is used. These data are processed into GMES-related products: 1) Maps on local percentage of snow covered area (SCA) 2) vegetation state (phenology) and 3) water quality and temperature. From these multi-year data sets 1) and 2), inter-annual and intra-annual time series for points-of-interest are generated. Particularly, a novel approach is to form a chronological data set by combining the snow depletion data with the sequential information on primary production (as reflected by the NDVI), thus describing the length and power of the photosyntetically active period. This inter-annual data set starts at the time of melting on-set (March) and ends at the end of growing season in late autumn. The relevant EO-imagery are reprocessed in order to gain a coherent data set throughout the year in order to reveal snow cover related time series phenomena in the same areas (e.g. potential melting periods during winter). In addition to the rectified and quality controlled top-of-atmosphere (TOA) radiation data and NDVI/vegetation product time series, enhanced temporal data sets are constructed by estimation of the missing observations, noise reduction and computation of relevant indicators. TOA data is an essential element of the result time series, as it is the basis of the interpretation of data into significant geophysical parameters.

Expected results

Earth observation-based extended GMES services, particularly for FinLTSER environmental net-work points-of-interest. This includes time series of daily-weekly observations describing the extent of snow cover, vegetation status, water quality in lakes and coastal waters, surface temperatures of Baltic Sea and large lakes. These data may become available also for international LTER network (e.g. for Baltic Sea states)

This enables:
  • Comparison on inter-seasonal changes (year-by-year) for e.g. snow-clearance and start of growing season. Seasonal differences on different types of terrain and (forest, open areas, etc.) can be evaluated.
  • Usage of climate change –sensitive land cover information (including snow and phenology) in climate change studies 
  • Interpolation and extrapolation of site-specific observations completed in the LTER sites to cover large areas in climate change assessments.
  • Calibration of models with the aid of historical EO derived data sets.

Contact person

Saku Anttila, Finnish Environment Institute,

Published 2013-05-06 at 8:48, updated 2013-05-06 at 8:47