Topics Addressed: Disaster, Health, Energy, Climate, Water, Weather, Ecosystems, Agriculture and Biodiversity (societal benefit areas GEO – ordering equal importance)
Projects homepage: http://www.geo-bene.eu/
Participant list:
1. International Institute for Applied Systems Analysis (IIASA), International , CO
Researcher responsible for the
study in the KTL: Marjatta Karvonen
Principal investigator:
Elena Moltchanova
Global Earth Observations are instrumental to attain sustainable development goals and are major drivers of how the society–technology–environment system is managed. An integrated economic, social and environmental assessment of the nine benefit areas as specified by Global Earth Observation Systems of Systems (GEOSS) has not yet been carried out. These benefit areas are: Disaster, Health, Energy, Climate, Water, Weather, Ecosystems, Agriculture and Biodiversity. In order to support the international negotiation processes connected to these areas and for the development of good policies the “Global Earth Observation – Benefit Estimation: Now, Next and Emerging” (GEO-BENE) project’s objective is to develop methodologies and analytical tools to assess societal benefits of GEO and to perform benefit assessments. The assessment will be carried out using quantitative and qualitative methods and data. Benefit assessment tools are centered around spatially explicit information applying deterministic and stochastic approaches. The various model structures will be applied to global data sets assessing benefit functions using harmonized socioeconomic and technology scenarios. Concise policy conclusions from the modeling exercise will aim at supporting the implementation of international agreements.
In the proposal we advocate for a multi-method assessment on different spatial levels, integrating quantitative and qualitative data. This includes a spatially explicit approach for benefit estimation motivated by the fact that activities underlying the nine benefit areas of GEO are by their very nature spatial entities and aggregate non-spatial treatment could, according to our experience, lead to serious biases in the assessment. We propose a simple and easily tractable static and deterministic approach for the aggregate benefit calculation and also more comprehensive, dynamic, and uncertainty augmented assessment of individual benefit areas. We believe that such a multidimensional approach is necessary since the underlying processes of the benefits areas are complex and consistency across a variety of decision rules should guarantee robustness of the final aggregate benefit estimates.