. "Geographic Information Science"@en . . "Geography"@en . . "Remote Sensing"@en . . "English"@en . . "Orientation and introduction"@en . . "1" . "no data" . . "Presential"@en . "TRUE" . . "Scientific methods and writing"@en . . "1" . "no data" . . "Presential"@en . "TRUE" . . "Methods in spatial analysis"@en . . "2" . "Students therefore will be able to immediately apply the respective methods in project-oriented work and take methodological responsibilities in working groups and complex workflows. Depending on individual choices, students will: ‐ Design and implement advanced geovisualisation interfaces for use-case oriented media, devices and user experiences. Decide on adequate Remote Sensing data sources and workflows across available passive and active sensors. ‐ Apply the Object-Based Image Analysis (OBIA) paradigm to the extraction of features and monitoring of change across remote sensing application domains. Select and implement advanced geodata acquisition processes using e.g. photogrammetry, LiDAR, in-situ and mobile sensors,\ncrowdsourcing and UAV platforms, including real-time data streams . Prepare and support decisions through (geo-)simulation. Choose and apply spatial- and geo-statistical methods to analyse.Mmultidimensional and multivariate data sets to explain and model complex relations and processes. Manage information extraction from large (‘big’) data sets, including flow of data, DBMS aspects and pattern analysis." . . "Presential"@en . "TRUE" . . "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" . . "Basics of software development"@en . . "3" . "no data" . . "Presential"@en . "TRUE" . . "Practice: software development"@en . . "3" . "no data" . . "Presential"@en . "TRUE" . . "Geo-application development"@en . . "6" . "articipants in this module will gain a well-structured understanding of\nsoftware development from a software engineering (SWE) perspec-\ntive, enabling them to work as geospatial experts in development\nteams and to successfully communicate with software developers.\nBased on the foundations of programming and development, students\nacquire competences in at least two development environments and\nlanguages, enabling them to design simple software programs, to cus-\ntomize existing applications, and to automate basic workflows. This in-\ncludes practical skills in geo-application development in the areas of\nweb applications, mobile applications, or desktop analytical applica-\ntions. Having completed this module, students are able to carry out\nbasic development tasks on a variety of platforms and architectures\nwith an emphasis on understanding and translating demands from typ-\nical geospatial application domains. This key competence is devel-\noped and verified through a development project in one of the se-\nlected IPs." . . "Presential"@en . "TRUE" . . "Design of geospatial data models"@en . . "3" . "no data" . . "Presential"@en . "TRUE" . . "Opengis: standards, architectures and services"@en . . "3" . "no data" . . "Presential"@en . "TRUE" . . "Sdi services Implementation"@en . . "6" . "A spatial data infrastructure (SDI) comprises technology, standards,\npolicies, organisational/legal aspects, human resources and related ac-\ntivities to integrate, exchange, process, maintain and preserve geospa-\ntial data and information. Students will:\n‐ Be able to describe the main components of SDIs and know key\nobjectives, benefits and current state-of-the-art of such initiatives\n[OI5-1].\n‐ Understand the conceptual strategies, organizational requirements\nand legal frameworks for leveraging the advantages of open geo-\ngraphic data infrastructures [DA3-3, GS1].\n‐ Recognize the importance of standardized data models to store, an-\nalyse and manipulate geographic phenomena.\n‐ Be able to explain the role of metadata for spatial data sharing\nacross distributed networks [GD12].\n‐ Be able to describe the existing spatial data sharing policies includ-\ning intellectual property rights, security issues, privacy issues, Open\nGovernment data initiatives [GS5-4, OI5-6].\n‐ Be able to explain the Service Oriented Architecture (SOA) concept\ntogether with its underlying publish-find-bind principle.\n‐ Know internationally accepted geographic- and IT standards (OGC,\nOASIS & ISO) and apply these in practical projects [OI5-1].\n‐ Be able to understand, design and implement geodata models ac-\ncording to standardised approaches [CF3-CF6].\n‐ Be able to publish geodata and geoprocessing services over the\nweb: map services, data services (editing, search, image service),\nand analytical services.\n‐ Be able to define the interoperability needs beyond technical issues\nlike direct access and industry standards on a legal, semantic and\norganizational level [OI5-2].\n‐ Understand the principles and techniques of spatial data organiza-\ntion and apply these principles and techniques to design and build\nspatial databases [DM2, DA4].\n‐ Based on these concepts, the students will learn how to utilize open,\nshared GIS resources to design and use Open GIS data structures,\nworkflows and processes leveraging information repositories" . . "Presential"@en . "TRUE" . . "Integrated projects"@en . . "12" . "As a capstone project, students develop, test and validate the compe-\ntences required for ‘putting it all together’. Acknowledging the differ-\nences between ‘the whole and its many parts’, challenges from com-\npleting a major project through all its stages are successfully dealt with.\nFrom problem analysis, conceptualization, workflow design and data\nacquisition to schema implementation, analyses, validation and com-\nmunication of essential outcomes, all major phases of a project are\npracticed. In particular, skill sets for collaborative work and structuring\nof larger projects are developed. Based on impulse elements and struc-\ntured inputs in the domains of project management, presentation tech-\nniques, moderation / facilitation and controlling / supervision, a project\nreflecting the key elements of practice-oriented work flows will qualify\nstudents to function in teams and to start organizing tasks and chal-\nlenges into structured projects. In addition, by being familiar with stand-\nard project management and communication steps, graduates will con-\nfidently accept responsibilities within major project environments. At the\nsame time, this experience will be a major contribution to successfully\ndevelop and complete the master thesis" . . "Presential"@en . "TRUE" . . "Lectures in giscience"@en . . "2" . "no data" . . "Presential"@en . "TRUE" . . "Giscience: theory and concepts"@en . . "4" . "Participants in this module can describe the highly dynamic nature of the evolving field of Geographic Information Science or GIScience in short. Students can work scientifically in the broader field of GIScience and communicate in an interdisciplinary manner with other fields based upon generic scientific as well as GIScience-specific skills and competencies. Students acquire competences both in GIScience thory including its epistemology and in Geoinformatics applications fields. They are able to use theory in application contexts. Geospatial technologies support a wide variety of uses in society. Students can evaluate technological and scientific trends and whether they may provide opportunity or threats for our society." . . "Presential"@en . "TRUE" . . "Advanced remote sensing"@en . . "6" . "no data" . . "Presential"@en . "TRUE" . . "Multivariate statistics | spatial statistics | geostatistics"@en . . "6" . "no data" . . "Presential"@en . "TRUE" . . "Geovisualization and advanced cartography"@en . . "6" . "no data" . . "Presential"@en . "TRUE" . . "Geodata acquisition"@en . . "6" . "no data" . . "Presential"@en . "TRUE" . . "Spatial simulation"@en . . "6" . "no data" . . "Presential"@en . "TRUE" . . "Location based services"@en . . "6" . "no data" . . "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 . . . . . . . . . . . . . . . . . . . . . "Department of Geoinformatics - Z_GIS"@en . .