Keywords
systematic review; text mining; ontology; carbon sequestration
Location
Session C1: VI Data Mining for Environmental Sciences Session
Start Date
13-7-2016 9:10 AM
End Date
13-7-2016 9:30 AM
Abstract
Human induced land-use changes and land-cover changes (LUCC) are a major driving force of global environmental change. To develop an improved scientific understanding of the mechanisms and effects of LUCC models and scenarios are important tools. The integrated model LandSHIFT was developed to study LUCC under different biophysical and socio-economical scenarios. It is a spatially explicit modelling system that aims at simulating and analysing land use dynamics and their impacts on the environment at global and regional level. Land-use activities in LandSHIFT are allocated depending on processed demands and suitability values for every land-use activity. In order to study the options and trade-offs of carbon sequestration it is necessary to add (long-term) carbon sequestration as a land-use activity. This new activity requires a global suitability map. Data and knowledge about factors and mechanisms influencing carbon sequestration and especially its long-term aspects are fragmentary. Therefore it is crucial to systematically search, map and analyse the information that is available. A systematic review to identify publications including factors influencing carbon sequestration was conducted. The mentioned factors and information concerning the frequency, links, interdependencies and magnitudes of these factors, the scale, scope and quality of the studies, as well as expert opinions on uncertainty and trends were extracted from the selected publications using text mining tools. They were compiled in an ontology framework, which was used to identify the necessary factors to map biophysical suitability for (long-tern) carbon sequestration on the global scale.
Included in
Civil Engineering Commons, Data Storage Systems Commons, Environmental Engineering Commons, Hydraulic Engineering Commons, Other Civil and Environmental Engineering Commons
Using Text Mining and Ontology Tools to Identify Important Factors for Modelling Long-term Carbon Sequestration
Session C1: VI Data Mining for Environmental Sciences Session
Human induced land-use changes and land-cover changes (LUCC) are a major driving force of global environmental change. To develop an improved scientific understanding of the mechanisms and effects of LUCC models and scenarios are important tools. The integrated model LandSHIFT was developed to study LUCC under different biophysical and socio-economical scenarios. It is a spatially explicit modelling system that aims at simulating and analysing land use dynamics and their impacts on the environment at global and regional level. Land-use activities in LandSHIFT are allocated depending on processed demands and suitability values for every land-use activity. In order to study the options and trade-offs of carbon sequestration it is necessary to add (long-term) carbon sequestration as a land-use activity. This new activity requires a global suitability map. Data and knowledge about factors and mechanisms influencing carbon sequestration and especially its long-term aspects are fragmentary. Therefore it is crucial to systematically search, map and analyse the information that is available. A systematic review to identify publications including factors influencing carbon sequestration was conducted. The mentioned factors and information concerning the frequency, links, interdependencies and magnitudes of these factors, the scale, scope and quality of the studies, as well as expert opinions on uncertainty and trends were extracted from the selected publications using text mining tools. They were compiled in an ontology framework, which was used to identify the necessary factors to map biophysical suitability for (long-tern) carbon sequestration on the global scale.
