. "Geographic Information Science"@en . . "Remote Sensing"@en . . "Geoinformation theory"@en . . "7.5" . "Theoretical Basis of Geoinformatics - Historical Development\nConcepts of space and time and representation of spatial knowledge\nImplementation of spatial concepts and models in a Geographic Information System\nAdvanced data structures and modelling\nModelling of three-dimensional data\nSpatial analysis\nGeomatics\nSpatio-temporal Geographic Information Systems\nSpatial data infrastructures\nAccuracy, ambiguity and completeness" . . "Presential"@en . "TRUE" . . "Spatial data acquisition and positioning"@en . . "7.5" . "Reference System, Geodetic Datum.\nSpatial data sources. Spatial data collection techniques and analysis with:\nClassical and satellite Geodetic methods\nClassical and conventional methods, including classical and geodetic methods\nStatistical and photogrammetric methods; Statistical and photogrammetric methods; Remote sensing methods; Statistical and photogrammetric methods; Remote sensing methods.\nStatistical methods and methods of mapping" . . "Presential"@en . "TRUE" . . "Analytical methods in geoinformatics"@en . . "7.5" . "Review of Elements of Probability Theory and Statistics. Distribution and density functions. Statistical tests. Transmission law of variables.\nTheory of least squares measurement correction. General and special cases. Special cases of solution of observation equations. Sequential addition of observations, correction of observations in phases, summation of normal equations.\nObservation equations with prior parameter estimates and/or parameter constraints, parameters with weights. Solution of systems of regular equations of large dimensions and/or special arrangements (tridiagonal, arrowhead, multi-banded)\nModelling of dynamic states, derivation of Kalman filter equations, aspects of their application. Statistical tests and analysis in least squares and Kalman filter methods.\nInterpolation and filtering methods. Various Kriging cases. Surface adaptations. Method of least squares collocation, relation to the least squares method." . . "Presential"@en . "TRUE" . . "Computational methods in geoinformatics"@en . . "7.5" . "Data Structures and Algorithms\nWhere data structures are needed, types of structures (tables, lists, trees, hash), algorithms for searching and sorting data, files.\nDatabases\nIntroduction to Databases (DB) - Fundamentals - Database Management Systems (DBMS) - Categories of DBMS - DBMS Architectures - Data Models - The relational model - Information System Design for DBMS (Imaginative Design, Logical Design, Physical Design). DB languages - The SQL language - Simple and complex questions. DBMS for small applications - The Microsoft Access package - Tables - Creating tables and associations - Questions (simple, statistical, etc.)\nAnalysis and processing of images\nCapture (capture) and Visualization (display) of images, Image structures and encoding (binary, quadtrees, etc.), Pattern recognition - statistical, syntactic, structural recognition.\nKnowledge Systems and Experiential Systems\nKnowledge representation. Basic principles and methodologies. Relationship between knowledge bases and databases. Experiential systems." . . "Presential"@en . "TRUE" . . "Processing, analysis and display of spatial data"@en . . "7.5" . "ategories of spatial data [maps, photographs, remote sensing images].\nCartographic data: Interpretation - classification. Creation of structures based on selected spatial models. Transformations between different structures.\nPhotogrammetric data:\nInstruments, software, two-dimensional - three-dimensional rendering systems\nPhotogrammetric networks, software, instruments, software, tools, 3D and 3D data processing.\nOrthophotography\nRemote sensing images: \nDigital processing of multispectral images\nEnhancement of multispectral images with point and spatial processing\nClassification of multispectral images with supervised and unsupervised classifications\nCartographic data\nSynthesis - rendering of 3D models\nSynthesis of static dynamic maps - Visualisation elements\nErrors in spatial databases\nSpatial data analysis methodology\nDevelopment of applications for the processing, analysis and rendering of all categories of spatial data using existing databases." . . "Presential"@en . "FALSE" . . "Applications of geoinformatics"@en . . "7.5" . "Data processing (data entry, digitisation, web integration, integration)\nGeodatabase design and development\nCreation of a Digital Terrain Model\nSpatial analysis - spatial queries (topology, network analysis, zoning)\nGeo-visualisation - Data/results rendering" . . "Presential"@en . "FALSE" . . "Research topics in geographic information science"@en . . "7.5" . "Βuilds on the knowledge acquired in the course \"Theory of Geoinformatics\" of the previous semester. The main purpose of the course is to introduce graduate students to the research process and methodology, as well as to the most current research issues in the field of Geographic Information Science (GIScience researc" . . "Presential"@en . "FALSE" . . "Expert systems in geoinformatics"@en . . "7.5" . "Introduction to Arificiall Intelligence. Categories of Artificial intelligence, supervised, unsupervised and semi-supervised learning methods. Methods with or without modelling. Probabilistic methods. Intelligent Agents.\nIntroduction to artificial intelligence methods without modeling (stateless - Supervised learning). The structure of the simple preceptor, neuron. The structure of neural networks. The method of backpropagation. Deep learning neural networks. Methods of nonlinear categorization.\nIntroduction to model-free artificial intelligence methods (stateless - Unsupervised learning). Classification methods, k-means, DBSCAN, spectral clustering. Unsupervised learning methods using training ( autoencoders, stacked autoencoders, deep learning).\nIntroduction to artificial intelligence methods with modeling (state modeling - deterministic). Introduction to Search Problem Modeling. Search trees. Euphemistic Methods. Local Search Algorithms and Optimization Methods. Search by width, depth. Uniform Cost Search. A Star A Star Relaxations.\nIntroduction to artificial intelligence methods with modeling (state modeling - competitive). Competitive Methods. Game Theory, Max Min Algorithms, ExpectMax Algorithms, Alpha-Beta pruning. Adversarial Generative Networks (GANs) and deep learning" . . "Presential"@en . "FALSE" . . "Geographic knowledge representation"@en . . "7.5" . "Introduction to Knowledge Representation\nConceptual structures (Semantic Networks, Lattices)\nFormal Concept Analysis (FCA)\nInformation Flow (Channel theory - Information Flow)\nConceptual Graphs (Conceptual Graphs)\nOntologies - development, extension and integration\nSemantic Similarity Measures and mapping\nNatural Language Processing (NLP)" . . "Presential"@en . "FALSE" . . "Spatial databases"@en . . "7.5" . "Introduction to Knowledge Representation\nConceptual structures (Semantic Networks, Lattices)\nFormal Concept Analysis (FCA)\nInformation Flow (Channel theory - Information Flow)\nConceptual Graphs (Conceptual Graphs)\nOntologies - development, extension and integration\nSemantic Similarity Measures and mapping\nNatural Language Processing (NLP)" . . "Presential"@en . "FALSE" . . "Methods of positioning and navigation on land and sea"@en . . "7.5" . "Geodetic reference systems\nMethods for optimisation of localisation and navigation parameters\nLocalisation and navigation techniques and technologies\nElectronic and nautical chart navigation techniques and technologies\nHardware, software and cartographic parameters for land navigation" . . "Presential"@en . "FALSE" . . "Specialized methods of engineering survey and industrial geodesy"@en . . "7.5" . "Models for the analysis of geodetic measurements and results in the monitoring of engineering projects and industrial products\nCutting-edge technologies in technical and industrial geodesy\nFields of application of technical and industrial geodesy at different scales and low and high dynamic response phenomena" . . "Presential"@en . "FALSE" . . "Large scale engineering surveys"@en . . "7.5" . "Deepening and integration of methods of Geometric Documentation of Monuments\nGeodetic Measurements, Networks, Instruments, Methods\nPlanning of field and office work\nPhotogrammetric Measurements\nPlanning and execution of field surveys\nOffice work\nThree-dimensional reconstruction of monuments or objects requiring large-scale mapping\nDesign and development of information systems for monuments\nIntegrated examples-Applications\nElaboration of a Theme adapted to the particular wishes of those who choose the course" . . "Presential"@en . "FALSE" . . "Advanced methods in digital remote sensing"@en . . "7.5" . "Photo interpretation. Physical principles of remote sensing. Multispectral, Hyperspectral, Thermal and Radar imaging.\nEarth, Sea, Atmosphere observation satellites. International Programmes.\nGeometric and Radiometric Image Reduction\nAlgorithms for Digital Analysis and Classification of Remote Sensing Imagery\nAdvanced Classification Methods. Object Oriented Remote Sensing Image Analysis, applications.\nDigital terrain models and geomorphometric feature extraction\nPattern Detection, Representation, Description and Recognition. Area Segmentation, Mathematical Morphology. Computer Vision in Remote Sensing.\nApplications to Earth, Sea, and Atmosphere." . . "Presential"@en . "FALSE" . . "Earth observation big data and analytics"@en . . "7.5" . "The main objective of the course is to introduce basic concepts and methods for the collection, management, analysis, visualization and dissemination of large-scale land observation data and geospatial products. The course is addressed to postgraduate students of NTUA's MSc courses who have already attended the compulsory courses of the 1st semester and have basic skills in programming languages such as Python, C, C++. Current scientific and technological challenges and solutions for harmonization, fusion and web-based processing of heterogeneous data and production of geospatial products will be described in detail. Upon completion of the course, the student will be able to implement geospatial databases, web-based applications for data search and visualization and geospatial products; design and implement individual automation in data and time series analysis; implement and integrate machine learning methods for information extraction; for applications such as precision agriculture, water quality assessment, automatic detection of changes in urban, natural and marine environments. Course Material\nData collection and automation of geospatial database import and update processes.\nFormats and representations of spectral spatio-temporal data and their characteristics.\nSystems and architectures for storage, management, analysis and delivery of large geospatial data and products in cloud computing systems.\nData visualisation and dimensionality reduction strategies.\nStatistical processing and analysis for data harmonization and merging.\nWeb-based processing and high-performance computing systems for land observation data.\nData and time series analysis for change, object and feature detection.\nBig data analysis using machine learning techniques with applications in precision agriculture, water quality assessment, automatic detection of changes in urban, natural and marine environments." . . "Presential"@en . "FALSE" . . "Digital methods in photogrammetry"@en . . "7.5" . "Digital image processing\nMeasurement automation techniques\nDigital matching\nEdge detection\nPattern recognition\nFeature extraction\nApplications of digital methods\nDigital products" . . "Presential"@en . "FALSE" . . "Theoretical approach to spatial visualizations"@en . . "7.5" . "Map reading \nVision and visual perception\nVisual perception and knowledge\nSpatial thinking - cognitive patterns\nIntroduction to semiotics\nSignal semantics and spatial data\nSign syntax and cartographic notation\nSignal pragmatics and spatial representations" . . "Presential"@en . "FALSE" . . "Advanced methods of analytical cartography"@en . . "7.5" . "Cartographic line theory\nCartographic generalization\nDigital elevation models & geomorphometric analysis\nCartograms\nFractional geometry\nMulti-source analytical light shading\nInteractive network cartography\nSound maps" . . "Presential"@en . "FALSE" . . "Digital technology and cartographic production"@en . . "7.5" . "Internet services and geospatial data on the web\nGeospatial servers\n Designing maps for the web\nRendering geospatial data on the web - Symbolism\nWeb-based map libraries\nPublishing cartographic data on the web\nImage reproduction\nAnalogue technique\nNon-continuous tone image reproduction\nEngraving, screen tints\nReproduction of continuous tone images\nDigital technique\nDigital screen tints\nHalftone screens\nPrinting an image in multiple copies\nOffset technology\nColour on the computer screen\nRaster screens\nSpecial problems [Gamma-dithering correction]\nColor rendering models\nColour in designers/printers\nColour management\nIllustrators \nDigital map reproduction\nDigital map reproduction in Arc/GIS environment" . . "Presential"@en . "FALSE" . . "Analysis of urban systems"@en . . "7.5" . "Introduction to the structure of the settlement network of Greece.\nGeneral reference to the sizes of settlements, their form and their problems.\nThe Settlement issue in Greece : historical reference to the formation of the settlement network.\nEconomic situation, productive forces and settlements. The effects of economic choices on the sizes of settlements and their structure.\nThe formation of the legislative framework (land-use, town planning, housing, etc.) governing the development and evolution of settlements. The consequences of the implementation, non-existence or non-implementation of the legislative framework on the settlement network. The new regulations (Kapodistrias, etc.) and their consequences.\nThe methodologies and techniques for the development of settlements in Greece. Brief references to the identifications and the study of their physiognomy.\nDetermination of boundaries, building conditions, restrictions, etc. as a result of the development process in Greece.\nMethodology for the formulation of a programme for a settlement plan. Standard specifications.\nProcedures and ways of implementation of settlement plans in the Natural Area.\nComparisons of the settlement network of Greece with the settlement network of Europe and especially of the Mediterranean countries." . . "Presential"@en . "FALSE" . . "Geographical-syntactical analysis and modeling of spatial organization and growth using gis"@en . . "7.5" . "Theories, methods, techniques and technologies of spatial analysis and planning belonging to the fields of Geostatistics, Location - Allocation Models, Spatial Interaction Models, Space Syntax Analysis and Urban Growth Models are presented. In this context, the potential of GIS is exploited in combination and their role as Spatial Decision Support Systems is highlighted." . . "Presential"@en . "FALSE" . . "Environmental Impact assessment methods and techniques- natural resources management"@en . . "7.5" . "Environmental impact issues from projects and programmes\nSpecific issues of natural resource management (resource management)\nMethods and Techniques of Environmental Impact Assessment, interdisciplinary information and data combination for carrying capacity investigation, impact assessment and comparison of alternatives (scenarios)" . . "Presential"@en . "FALSE" . . "Real property valuation - land management"@en . . "7.5" . "The value of property: land and its sustainable management. The different values of land. Concepts. Definitions market value, tax value, cost, price. Analysis and Operation of the \"Real Estate Market\". The basic principles of good market functioning. Conditions of equilibrium and adequacy. Law of supply and demand. The evolution of prices. The necessity of determining the Value. Legislative provisions. Real estate taxation. Factors affecting the \"Real Estate Market\". The use and ownership of Real Estate as key elements of price formation. Use restrictions. Optimal use. Traditional methods of valuation and their use where appropriate. Development of a system of \"Mass Valuation\" of Real Estate.\nReal Estate Development (Real Estate Development or RED): Real Estate Development. The dead capital. Examples. Strategy planning, site selection, market analysis, existing constraints. Settlement of unauthorized properties. Housing policy. Energy improvements of properties. Possibilities of funding or subsidies through Development Laws. Resolution of land and property disputes through mediation. Property expropriation." . . "Presential"@en . "FALSE" . . "Application of informatics in road transport"@en . . "7.5" . "Geographic Information Systems (GIS-T)\nGeneral. Role of GIS in Road Infrastructure. System Architecture. Data Organisation and Structure. Applications: Road Safety, Road Network Management, Optimal Route Selection, Public Transport Route Planning.\nAutomation and Robotics Systems\nGeneral. Definitions. Criteria for the selection of construction works. General System Architecture. Construction Environment Capture Systems and Accuracies. Automatic Positioning and Operation Control of Road Construction Machinery. Coordination of Automated Road Machinery. Research work on prototype development. Cases: Road Paving, Pavement Recycling, Pipeline Construction, Pavement Crack Repair, Bridge Reinforcement Repair.\nTelematics/Intelligent Transport Systems\nIntroduction to Intelligent Transport Systems (Technological components. Human Factor. Social Acceptance. Use and Applications of Telematics Systems). Intelligent Transport Systems and Road Safety. Intelligent Transport Systems and Traffic Management, Intelligent Transport Systems and Public Transport. Intelligent Transport Systems and Supply Chain. Evaluation of Intelligent Transport Systems. Localisation and navigation in transport\nUser requirements and localisation parameters in transport applications, GNSS kinematic localisation and navigation methods and techniques, GNSS system augmentation, implementation and evaluation of localisation systems for intelligent transport applications, integrated kinematic mapping systems." . . "Presential"@en . "FALSE" . . "Applications of geostatistics in geological sciences"@en . . "7.5" . "Bivariate or multivariate statistics: two-dimensional distributions, conditional averages, covariance and correlation, random variables as vectors, Hilbert space of random variables.\nINTRODUCTION TO RANDOM FIELD THEORY: joint distribution of many random variables, the vector space of random variables, Covariance function and Positively Defined Functions, covariance models, simplified Random Fields.\nSTRUCTUAL ANALYSIS: Analysis of the concept of spatial correlation, definition of the barogram and its physical meaning, calculation and interpretation of the barogram, models of barograms, the barogram as a generalized covariance.\nSpatio-temporal mapping: the projection algorithm and its geometric interpretation, simple and regular kriging, cases of algorithm failure and their treatment, trend treatment, uncertain data, spatio-temporal interpolation, error estimation.\nAPPLICATIONS IN MINING: Density optimization of exploratory drilling canvass density, mineral reserve estimation, estimation error maps.\nAPPLICATIONS IN HYDROGEOLOGY - GEOMETRY: Combined use of causal and stochastic models for the interpolation of hydrogeological measurements, spatial correlation of geochemical parameters.\nAPPLICATIONS IN GEOTHERMOLOGY: Combined use of causal and stochastic models for the description of geothermal reservoirs\nAPPLICATIONS IN SOIL - ROCK ENGINEERING: Spatial distribution of soil - rock mass parameters, correlation of parameters, combined use of causal and stochastic models.\nAPPLICATIONS TO ENVIRONMENTAL POLLUTION EVALUATION: Spatio-temporal pollution mapping, correlation of pollutant distributions.\nAPPLICATIONS TO EPIDEMIOLOGY: Combined use of causal and stochastic epidemiological models to visualise the spread of public health and safety parameters." . . "Presential"@en . "FALSE" . . "Applications of geoinformatics in mining"@en . . "7.5" . "A course that includes (a) a series of introductory lectures on the principles governing the sustainable use of Mineral Resources, (b) individual/team work on the above topics. For the preparation of the assignment, which is the deliverable of the course, students proceed to the collection, organization, visualization and management of geological, demographic, spatial, environmental and other data concerning the siting of new or expansion of existing mining projects in areas of deposit interest, taking into account the particular environmental, cultural and social characteristics, and the infrastructure of the immediate and wider area under consideration.\nApplication of techniques for the analysis and spatial visualisation of these data for the rational operational planning and management of mining projects, the harmonious integration of mining activity in areas with potential for O.P.S. The above tools are also used for the examination and selection of the best alternatives for the restoration and enhancement of areas where the life cycle of mining projects has been completed and post closure activities are planned." . . "Presential"@en . "FALSE" . . "Artificial intelligence and knowledge base"@en . . "7.5" . "Introduction to Technical Intelligence. Categories of technical intelligence, supervised, unsupervised and semi-supervised learning methods. Methods with or without modeling. Probabilistic methods. Intelligent agents.\r\nIntroduction to artificial intelligence methods without modeling (stateless - Supervised learning). The structure of the simple preceptor, neuron. The structure of neural networks. The method of backpropagation. Syneclectic deep learning neural networks. Nonlinear categorization methods.\r\nIntroduction to artificial intelligence methods without modeling (stateless). Classification methods, k-means, DBSCAN, spectral clustering. Unsupervised learning methods using training (autoencoders, stacked autoencoders, deep learning).\r\nIntroduction to artificial intelligence methods with modeling (state modeling - deterministic). Introduction to Search Problem Modeling. Search trees. Heuristic methods. Local Search Algorithms and Optimization Methods. Search by width, depth. Uniform Cost Search. A Star A Star Relaxations.\r\nIntroduction to artificial intelligence methods with state modeling. Competitive methods. Game Theory, Max Min Algorithms, ExpectMax Algorithms, Alpha-Beta pruning. Adversarial Generative Networks (GANs) and deep learning\r\nIntroduction to artificial intelligence methods with state modeling. Bayesian classifiers, Decision tress, modeling with Markov models, policy evaluation, particle filters, Q-learning, Reinforcement learning, deep reinforcement learning\r\nIntroduction to Knowledge Bases and Expert Systems. Symbolic representation of knowledge: objects, production rules, semantic networks, frameworks, tables.\r\nSymbolic Inference Methods and Decision Control Procedures. Use and mechanism of production rules, correct, reverse and two-way reasoning, deep – and broad – research.\r\nRepresentation and drawing conclusions with uncertain and inconclusive knowledge. Uncertain Reasoning, Fuzzy Logic, Probability Reasoning, Theory of Testimony.\r\nDevelopment of experienced systems. The Architecture of Experienced Systems. Steps to Develop an Expert System. Formulation and Identification of the Problem. Conceptual Conception of the Problem, Capture of knowledge from written sources and Experts. Standardization and Organization of the Knowledge Base, Implementation of the Expert System, Evaluation of the Expert System.\r\nProgramming Languages and Expert Systems Development Tools. Types of Tools, Language or Tool Selection, Hardware Infrastructure for Expert Systems.\r\nExamples of expert systems. Review of systems experiences in Earth Sciences.\n\nOutcome: Not Provided" . . "Presential"@en . "TRUE" . . "Postgraduate seminars"@en . . "0" . "Postgraduate seminars concern a subject or a combination thereof as covered in the elective courses. These include a Postgraduate Research Seminar.\n\nOutcome: Not Provided" . . "Presential"@en . "TRUE" . . "Master in Geoinformatics"@en . . "http://geoinformatics.ntua.gr/ https://www.survey.ntua.gr/en/postgrad/geoinformatics" . "90"^^ . "Presential"@en . "The Interdisciplinary PostGraduate Programme \"GeoInformatics\" is offered by NTUA since 1998, with the participation of: (a) School of Rural and Surveying Engineering, (b) School of Electrical and Computer Engineering, and (c) School of Mining and Metallurgical Engineering. The general coordination and support of the program as well as the awarding of the degree is undertaken by the School of Rural and Surveying Engineering. The Programme is addressed to NTUA graduates but also to those from other universities, having an interest in geospatial science and technology. It provides specialization in: (a) the collection, georeferencing, description, interpretation, and mapping of geospatial data of the physical, artificial and socio-economic environment, (b) spatial analysis and planning, and (c) the development of various geo-applications employing state-of-the-art methods and cutting-edge geospatial technologies. The duration of the Programme is three academic semesters. Awarding the Postgraduate Specialization Diploma (MSc) in Geoinformatics requires: (a) successful completion of 8 courses (4 core and 4 specialization courses), and (b) successful completion of a research thesis. The total number of credits (ECTS) corresponding to the acquisition of the Diploma is 90 (30 per semester). The number of annually enrolled students is about 30. The number of applicants varies between 70 and 120."@en . . . "1,5 years"@en . "TRUE" . . "Master"@en . "Thesis" . "no tuition, other costs may apply" . "Euro"@en . "1000.00" . "None" . "No Job Prospects Listed"@en . "2"^^ . "FALSE" . "Downstream"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "Greek"@en . . "School of Rural, Surveying and Geoinformatics Engineering"@en . .