Derivation of land-cover change data and their assimilation in ecosystem models IA

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Context and objectives

The general objective of the research is to develop new methodologies, and to advance and refine existing methodologies to allow for: (i) a more realistic description of long-term processes of land-cover changes, based on a variety of data sources, and (ii) a better integration of remote sensing data into ecosystem models in order to better address key issues on land-cover changes and their impacts.
The proposal is divided into four Modules: (i) Characterisation from space of subtle changes in land cover, (ii) Detection of land-cover change trajectories with long temporal series of data from a variety of sources, (iii) Validation and calibration of remote sensing-based land-cover change data with field measurements - the case of LAI, (iv) Assimilation of remote sensing-based land-cover change data in ecosystem models.

Project outcome

Expected scientific results

• Module 2: Database (aerial photographs, maps, satellite images) + Diagnostic of different spatial aggregation methods Method for homogenising a time series of land cover data. Method for change detection on long-term time series. • Module 4: Database Detection algorithm for vegetation change Methodology: Sensitivity of emission models to biomass burning input data derived by remote sensing.
Project leader(s): UCL - Georges Lemaître Centre for Earth and Climate Research
Location: Region:
  • Central Africa,West Africa,Zambia

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