. "Geospatial Analytics And Modelling"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "Spatial analysis and modeling"@en . . "4" . "THis area of Geoinformatics builds advanced translation skills from application domain problems towards conceptual reframing and structuring, and into the analytical methods and toolsets of Geoinformatics. Based on this knowledge of operational methods, complete workflows representing complex processes are modeled and represented in structured frameworks for spatial decision support across domains. Students will: Be able to map conceptual spatial relations (topological and geo-\nmetrical) to the body of analytical methods. Recognize the value of different metrics in the spatial as well as attribute domains (e.g. fuzzy algebra). Describe shape characteristics of spatial features as well as complex landscape structures with the aim of diagnosing change. ‐ Identify, select (including SQL clauses) and statistically describe spatial features based and their distance to and/or topological relations with a target feature. Estimate values of a continuous (real or thematic) surface based\non sample points through interpolation methods.‐ Select adequate interpolation methods (based on characteristics of surface theme, measurement level, sample density) and assess quality of results. Derive characteristics of continuous surfaces as a basis for advanced models. Develop and adequately parameterized basic models of surface runoff, groundwater dynamics, visibility, solar irradiation and diffusion / spreading over inhomogeneous surfaces. Apply topological relations for combination of spatial themes (overlay analysis), derive and implement weighting schemes. ‐ Find best routes (paths) across fields and networks. Allocate areas and features to service centres, distinguish from (‘optimal’) location analysis. Choose classification and regionalization methods according to specific requirements and contexts. ‐ Design, implement and validate complex workflows and process models built from individual methods and operations.‐ Move from data analysis to generation of context-specific information and the creation of higher level domain knowledge." . . "Presential"@en . "TRUE" . . "Master in Applied Geoinformatics"@en . . "https://www.plus.ac.at/wp-content/uploads/2022/07/mb160323-curr-geoinf-applied.pdf" . "120"^^ . "Presential"@en . "The study programme provides application-oriented knowledge based on relevant theories and methods. Discipline-specific ways of thinking, analytical skills and techniques as well as problem-solving competences are developed in core areas of Geoinformatics, especially in:\nGeospatial data acquisition and visual / cartographic communication;\nData modelling and spatial data management;\nData analytics across the spectrum of Geoinformatics: georeferenced data and data\nstreams; in-situ, remote and mobile sensing; statistics;\nSpatial analysis, as well as dynamic system simulation;\nStandards for architectures of open and distributed systems and spatial data infra-\nstructures;\nDevelopment of geospatial applications."@en . . . . "2"@en . "FALSE" . . "Master"@en . "Thesis" . "no tuition, other costs may apply" . "Euro"@en . "749.42" . "Mandatory" . "The ‘Applied Geoinformatics’ MSc aims at the building of advanced competences in geospatial\ndata acquisition and data management, data analytics and simulation as well as interactive\ncommunication. Graduates are expected to interface with different spatially oriented applica-\ntion domains, contribute to solving problems across societies, economies and environments\nas well as leading teams assigned pertinent tasks"@en . "1"^^ . "no data" . "Downstream"@en . . . . . . . . . . . . . . . . . . . .