Continental-Scale Living Forest Biomass and Carbon Stock: A Robust Fuzzy Ensemble of IPCC Tier 1 Maps for Europe

  • Daniele de Rigo
  • José I. Barredo
  • Lorenzo Busetto
  • Giovanni Caudullo
  • Jesús San-Miguel-Ayanz
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 413)


Forest ecosystems play a key role in the global carbon cycle. Spatially explicit data and assessments of forest biomass and carbon are therefore crucial for designing and implementing effective sustainable forest management options and forest related policies. In this contribution, we present European-wide maps of forest biomass and carbon stock spatially disaggregated at 1km x 1km. The maps originated from a spatialisation improvement of the IPCC methodology for estimating the forest biomass at IPCC Tier 1 level (IPCC-T1). Using a categorical map of ecological zones within the mapping technique may originate boundary effects between the ecological zones. This may induce undue artifacts in the outcomes, as evident in previously published maps generated with the IPCC-T1 methodology. Here we present a novel method for IPCC-T1 biomass mapping which mitigates these artifacts. We propose the use of a fuzzy similarity map of the FAO ecological zones computed by estimating the relative distance similarity (RDS) of each grid-cells climate and geography with respect to the FAO ecological zones. A robust ensemble approach was used to merge an array of simple models with spatially distributed fuzzy set-membership. This allowed the boundary artifacts to be reduced, while mitigating the impact of model semantic extrapolation. The chain of semantically enhanced data-transformations is described following the semantic array programming paradigm. Preliminary results obtained from the application of this novel approach are presented along with a discussion of its impact on the derived maps.


Ecological Zones Living Forest Biomass Living Forest Carbon Stock IPCC Tier 1 Relative Distance Similarity Robust Fuzzy Ensemble Semantic Array Programming 


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Copyright information

© IFIP International Federation for Information Processing 2013

Authors and Affiliations

  • Daniele de Rigo
    • 1
    • 2
  • José I. Barredo
    • 1
  • Lorenzo Busetto
    • 1
  • Giovanni Caudullo
    • 1
  • Jesús San-Miguel-Ayanz
    • 1
  1. 1.Joint Research Centre, Institute for Environment and SustainabilityEuropean CommissionIspraItaly
  2. 2.Dipartimento di Elettronica e InformazionePolitecnico di MilanoMilanoItaly

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