With increased degradation of natural resources due to land use decisions and the subsequent loss of biodiversity across large spatial scales, there is a need for a Spatial Decision Support System (SDSS) which showcases the impacts of developments on terrestrial and aquatic ecosystems. The Gap Analysis Program (GAP) and a Bayesian Belief Network (BBN) were used to assess the impacts of an impoundment in the Bienville National Forest, Smith County, Mississippi on landcovers, threatened and endangered species, species richness and fish populations. A test impoundment site was chosen on Ichusa Creek and using GAP data, landcovers, species and species richness were compared with those of Bienville National Forest, Smith County, Mississippi. For the aquatic analysis, a BBN model was developed for each fish so that population probabilities could be calculated using a given configuration of available habitats and compared to current fish population.

The present thesis aimed to investigate different traffic models and provide their analysis in context to traffic management decision support tools and evaluate the potential application of Dynameq software as a decision support system in Stockholm. A literature study, as well as a simulation case study, was used to meet the aim of the thesis. The main arguments for decision support systems were described in the context of traffic management and traffic control centres as a supportive tool for making informed decisions. The key features of the decision support system were identified as an advance knowledge-based system, inference system, or other AI system, and a simulation tool. In total, 18 traffic simulation tools were described and their applicability as decision support systems was assessed. Next, Dynameq traffic simulation software was examined both from the literature perspective and in context with a practical traffic simulation case study. The aim was to describe Dynameq software and its functionality in terms of a decision support system. Last, 5 incidents representing typical non-recurring congestion in forms of traffic incidents historically occurred during the Autumn 2019 were simulated and responses from Dynameq model were examined along with an investigation of a provided Stockholm traffic model in Dynameq. Limiting factors include the traffic data used, limited literature available for traffic software, and the quantity and quality of available incident data. The overall results were intended to provide answers to the formulated research questions. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet</p>

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.