A Scientific Approach to Employ Monitoring and Modelling Techniques for Global Change and Terrestrial Ecosystems and Other Related Projects

Abstract

The ultimate goal of understanding processes in the Earth's geophysical/biogeochemical/climate system can be achieved by multi-disciplinary studies using global monitoring systems, regional networks and models merging scientific and technological issues. The Global Climate Observing System (GCOS) and its composite parts-Global Ocean Observing System (GOOS) and Global Terrestrial Observing System (GTOS)-are on the agenda of current and subsequent international efforts. To outline scientifically the construction of the systems, an approach is proposed that includes the following interrelated blocks: Climate/Biosphere Models, Observation Systems, Geoinformation Systems and Predictability Problems. The opportunity to unify these blocks in the general context of global/regional change studies are determined by the proposed application of the information and thermodynamic properties of the entropy category that reveals its dualism in the information content assessments for data of modelling/ monitoring and in state parameter retrievals for natural targets using multi-spectral remote sensing images. The Climate/Biosphere Models block is designed to highlight how global and regional change problems are drawn up in terms of models, data, and processes for natural media (the atmosphere, hydrosphere, land surface, biosphere). The Observation Systems block, linking modelling and monitoring quantities on various scales, serves to account for recommendations to optimization techniques based on certain criteria, value functions and information content metrics. The recommendations are due to the necessity to improve or make cost-effective the systems which are planned within the EOS (Earth Observing System) and similar other programmes. The Geoinformation Systems (GIS) block gives an explanation to what extent GIS-technologies, databases and information systems can be unified with general principles of data processing, related algorithms and procedures. The Predictability Problems block enables one to understand what can be determined from temporal data set analyses and inter-annual variability of multi-spectral satellite products and samples of ground mea-