Courses
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6601. Theory of Geoinformatics
The course provides a comprehensive understanding of theoretical issues and practical applications in the field. Upon successful completion, students will demonstrate both foundational and advanced knowledge, exhibiting originality in developing and applying ideas within research contexts. They will be adept at utilizing problem-solving skills in interdisciplinary settings and tackling complex issues, forming well-founded judgments. The course emphasizes effective communication, enabling students to present their conclusions and underlying reasoning clearly to diverse audiences. It also fosters autonomous learning, preparing students for ongoing self-directed study. Key topics covered include the theoretical basis and historical development of Geoinformatics, spatial and temporal concepts, GIS implementation, data structures, object-oriented representations, 3D data modeling, spatial analysis, geovisualization, spatiotemporal GIS, spatial data infrastructures, and issues of accuracy, vagueness, and completeness.
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6602. Spatial Data Acquisition and Positioning
The course is an introductory, interdisciplinary course providing a foundational understanding of Geoinformatics. Students completing this course will gain knowledge of key definitions and concepts related to geospatial data and its geometric representations across spatiotemporal scales. They will understand the principles of topographic and geodetic disciplines, photogrammetric analyses, reference surfaces, map projections, and coordinate system transformations. The course covers the theoretical background and applications of geodesy, photogrammetry, remote sensing, and cartography, including contemporary data acquisition technologies and processing techniques. Students will learn mathematical models and positioning techniques, the relationships among topographic elements, and computational processes for coordinate computation. Additionally, the course addresses error sources and statistical processes for quality control in topographic measurements. The syllabus includes sections on geodesy, photogrammetry, remote sensing, cartography, and geospatial data optimization and adjustment.
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6603. Analytical Methods in Geoinformatics
The course covers advanced topics in probability, statistics, and observation correction theory, providing students with a comprehensive understanding of these critical areas. Learning outcomes include mastery of probability theory, statistical tests, and distribution functions, as well as the application of computational methods through programming. Students will delve into observation correction using the Least Squares method, addressing general and special cases, and learn techniques for handling large systems of normal equations. The course also covers dynamic state modeling, Kalman filter equations, and their applications. Interpolation and filtering methods, including various forms of Kriging and surface adjustments, are thoroughly explored.
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6605. Computational Methods in Geoinformatics
The course equips students with comprehensive knowledge in elements of algorithms and data structures, including linear data structures, trees, and graphs. They will understand algorithm theory and algorithms for spatial problems such as Dijkstra and k-means. The course covers the representation of spatial data using standards like JSON, XML, and simple features, as well as software architectures for spatial data management. Students will learn about web services for spatial data and services, including elements of web application programming. The syllabus includes standards for the representation of spatial data, representation of spatial data in databases, architectures of networked software applications, and open-source tools for spatial data and services. Additionally, the course introduces AI techniques for spatial data.
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6606. Processing, Analysis and Visualization of Spatial Data
The course is an interdisciplinary course that combines the fields of Cartography, Remote Sensing, and Photogrammetry within the context of Geoinformatics when processing, analysing, and visualizing geospatial information. The course aims to introduce students to cutting-edge topics in these sciences and provide specialized knowledge and skills. Upon successful completion, students will learn to design and implement spatial databases for map composition, combine spatial data from multiple sources, use VGI, apply cartographic generalization, understand spatial data quality issues, and apply state-of-the-art visualization techniques. Additionally, they will process LiDAR data, use automation in photogrammetric image processing, understand multi-image photogrammetric processing, and select and enhance remote sensing data. Students will also apply remote sensing data analysis methods, including statistical analysis, machine learning, and object-based image analysis, and integrate remote sensing data with other geospatial data.
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6607. Applications of Geoinformatics
The course acquaints students with the functions of GIS in real Geoinformatics problems. Primarily laboratory-based with a few lectures, the course combines theoretical teaching with practical exercises. Students extend and enrich their undergraduate knowledge about collecting, processing, and integrating data for GIS projects. They gain the ability to design and create geodatabases, perform tasks such as coordinate transformations, georeferencing, creating Digital Terrain Models, spatial analysis, geovisualization, and spatial decision support. Students also acquire the ability to design a complete spatial decision support system by applying multi-criteria analysis methods. Through this course, students develop the necessary skills to work autonomously and interdisciplinarily.
Core Courses - Fall Semester
Each course has 7.5 ECTS. Students select
4 out of 6 courses
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6611. Research Topics in Geographic Information Science
The course introduces students to the research process, methodology, and current research topics in Geographic Information Science. Each student investigates and analyzes a chosen topic, presenting progress and final findings. Lectures by faculty and invited researchers, along with peer presentations, provide comprehensive exposure to various research topics, equipping students with research experience, analytical and synthesis skills, and the ability to write and defend a scientific paper. The course structure includes research agendas, methodology lectures, topic discussions, and student presentations. Upon successful completion of the course, students will possess highly specialized knowledge in Geographic Information Science, including cutting-edge knowledge that fosters original thinking. They will be critically aware of research topics and their interconnections with various fields, equipped with specialized problem-solving skills essential for research and innovation. Students will develop effective oral and written communication skills and recognize the importance of academic and professional integrity.
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6612. Artificial Intelligence and Knowledge-Based Systems
The course is divided into two parts, focusing on Artificial Intelligence (AI) and Knowledge Bases and Expert Systems. Part A covers foundational AI concepts, including supervised, unsupervised, and semi-supervised learning, probabilistic methods, and intelligent agents. It delves into neural networks, deep learning, classification methods, and state modeling techniques, such as heuristic methods, game theory, and Bayesian classifiers. Part B introduces Knowledge Bases and Expert Systems, exploring symbolic knowledge representation, inference and decision control processes, fuzzy logic, and the development of expert systems. Students will learn advanced mathematical tools for modeling knowledge-based systems and training machine learning models. The course emphasizes practical applications in real-world engineering problems, especially in geoinformatics, and includes hands-on experience with Python and other programming environments. Upon completion, students will be equipped to execute research projects in AI and expert systems for engineering applications.
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6613. Geographic Knowledge Representation Methods
The course equips students with highly specialized and cutting-edge knowledge in geographic knowledge representation. It covers methods and conceptual tools for the extraction, standardization, representation, and integration of geospatial information. Key topics include geographic knowledge representation, semantic networks, Formal Concept Analysis (FCA), ontology development and integration, semantic similarity measures, and geospatial information visualization. Students choose a topic to study during the semester, such as: development of an ontology or integration of existing ontologies, extraction, and analysis of geographic information from texts, twitter, etc., application of similarity measures - spatialization and development of a semantic network. Upon successful completion of the course, students will be critically aware of methods and conceptual tools for representing geographic knowledge and their interconnections with different fields using their knowledge and problem-solving skills in new or unfamiliar environments.
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6620. Methods of positioning and navigation on land and sea
The course offers a comprehensive study of geodetic reference systems and positioning techniques for land and sea applications. The curriculum includes geodetic reference systems, map projections, satellite positioning and navigation systems, data processing and analysis, and inertial and radio-positioning technologies. It also covers integrated positioning systems, localization in hybrid and indoor environments, advanced and low-cost positioning techniques, and sea navigation technologies. Students will engage with both hardware and software, developing practical skills in computational methods through coding projects. By the end of the course, students will have a solid understanding of geodetic reference systems, localization and navigation techniques, and application of these systems in geospatial engineering.
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6621. Specialized methods of Engineering Survey and industrial Geodesy
The course aims to build upon students' existing geodetic knowledge by introducing them to advanced instruments and methods in technical and industrial geodesy. The course covers the analysis of geodetic measurements and results, particularly in monitoring technical projects and industrial applications. Students will explore state-of-the-art technologies in geodesy and their applications across various scales and phenomena with low and high dynamic responses. By the end of the course, students will have a comprehensive understanding of cutting-edge geodetic tools and techniques, enhancing their ability to analyze and interpret geodetic data in technical and industrial contexts.
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6622. Large scale surveys
The course focuses on the geometric documentation of monuments, emphasizing practical skills and modern techniques. The syllabus includes advanced methods in geodetic measurements, network planning, and the use of photogrammetric measurements for ground and office work. Students will learn automated 3D reconstruction algorithms and how to use modern optical scanning systems for large-scale imaging projects. The course also covers complete examples and applications, allowing students to work on personalized projects. Upon completion, students will have developed skills in planning and executing large-scale documentation projects, evaluating modern photogrammetric products, and understanding the collection of 3D information using various tools. The course aims to refresh and expand students' knowledge in photogrammetry and geodesy, preparing them for complex documentation tasks in technical and industrial contexts.
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6631. Advanced Methods of Remote Sensing
The course provides a comprehensive introduction to remote sensing and its applications in machine learning. The syllabus covers topics such as Earth observation, multispectral and hyperspectral data, thermal, radar, LIDAR, and SAR data, as well as various data acquisition systems. Students will learn basic remote sensing data processing pipelines, supervised classification techniques, and neural network architectures, including convolutional neural networks. The course also includes object-based image analysis and practical applications of remote sensing. Upon successful completion of the course, students will have the skills to integrate scientific knowledge, implement remote sensing data processing pipelines, and develop software for visualizing and classifying multispectral data and filtering images. They will also be able to integrate, implement & develop software for statistical and machine learning (PyTorch) remote sensing analytics.
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6632. Earth Observation Big Data and Analytics
The course focuses on Earth observation big data and its application in deep learning and data analytics. The syllabus covers a broad range of topics including Earth observation data analytics, deep learning fundamentals, convolutional neural networks, transfer learning, autoencoders, transformers, generative models, self-supervised learning, and object detection. Practical lab sessions provide hands-on experience with tools like Google Earth Engine, PyTorch, and TensorFlow. Students will gain skills in implementing server-side technologies, front-end services, and machine learning tools. They will also learn to develop software for data ingestion, querying, management, processing, and visualization. The course emphasizes the analysis of various types of data (1D, 2D, nD, time series, multispectral, hyperspectral) using advanced statistical and machine learning techniques. Upon successful completion of the course, students will be able to present and discuss their findings on theoretical and technical challenges effectively.
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6636. Digital Photogrammetric Methods
The course provides students essential knowledge and skills in measurement automation, photogrammetric techniques, and digital image processing. The curriculum covers a range of topics, including edge detection, pattern recognition, feature extraction, and LiDAR data processing. Students will also explore advanced concepts such as multimedia data transformations, geometric and affine image transformations, and structure from motion techniques for 3D reconstruction. Upon successful completion of the course, students will have developed the ability to produce and evaluate digital terrain models, orthophotos, and other photogrammetric products. They will also be able to deal with digital photogrammetry development algorithms and photogrammetric programming issues to solve complex photogrammetric and 3D reconstruction problems. Additionally, students will be adept at verifying automation results using real optical data and images.
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6641. Theoretical Approach to Spatial Visualizations
The course introduces students to the theoretical foundations of Cartography. It explores cartographic and spatial representations through the lenses of visual perception, cognitive psychology, and semiotics. The syllabus includes topics such as map reading, visual cognition, mental categorization, knowledge representation, and the semantics, syntactics, and pragmatics of cartographic symbols. Students will learn the principles governing cartographic language and geospatial visualization, ensuring cartographic products meet user needs for more functional spatial representations. By the end of the course, students will deepen their understanding of cartographic language and geovisualization, combining insights from cognitive science, psychology, neuroscience, semiotics, and philosophy. They will be able to clearly communicate the acquired knowledge to both specialized and general audiences and develop the skills to independently and interdisciplinarily address course tasks.
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6642. Advanced Methods of Analytical Cartography
The course introduces students to the foundational concepts of Analytical Cartography. The syllabus covers a range of topics including geospatial data transformations and processing for map production, spatial frequencies, cartographic line theory, digital terrain models, and fractal geometry. Students will explore methods for visualizing topographic relief, cartographic and model generalization, multi-directional hillshading, and automated label placement on maps. Special visualization methods such as dasymetric mapping and the evaluation of continuous cartograms are also discussed. Upon successful completion, students will understand the conceptual frameworks of cartography, evaluate digital representation, and apply various algorithms for spatial analysis and spatial data processing. The course combines lectures with interactive sessions and assignments, fostering skills in problem-solving, independent research, and effective communication of findings.
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6643. Digital Technology and Cartographic Production
The course offers students the skills and knowledge to create web mapping applications. The syllabus covers web cartography and technology, web standards e.g. W3, OGC, geographic data formats for the web, server-side/client-side architecture, and web map design principles. Students learn to design and create multiscale maps, create and encode cartographic symbolization, and use web tile maps. The course also delves into basic web page development tools e.g. HTML, CSS, JavaScript, open-source web mapping libraries e.g. Leaflet, and server-side geographic data publishing e.g. Geoserver. By the end of the course, students will build online cartographic applications with backend e.g. Geoserver, SLD and frontend tools e.g. geojson, Javascript. They will also use off-the-shelf and cloud tools e.g., commercial GIS / ArcGIS and ArcGIS Online, FOSS / QGIS and QGIS2Web tool.
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6644. Analysis of Urban Systems
The course explores regional development, spatial planning, and policy in national and regional contexts, with a focus on Greece. More specifically, it aims to provide students with a structured understanding of the forces that shape cities, particularly in cases of contested urbanism and geographies of the Mediterranean region. In that context, international guidelines and key theories in geography, spatial planning, economics, and developmental studies are compared. Students will delve into housing and settlement planning policy, the roles of the state, market, and civil society, as well as the impacts of urban sprawl and industrial activities on peri-urban spaces. The course also covers Greece’s spatial planning framework, development models, housing policies, transportation planning, and urban resilience. Through case studies and participatory processes, students will learn to apply various planning methodologies. By the end of the course, students will understand urban networks, settlement classifications, and the tools needed for effective spatial planning.
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6646. Methods and Models of Spatial Analysis
The course delves into contemporary Geographic Analysis, covering methodological issues essential for understanding spatial phenomena and designing interventions in urban, spatial, and environmental planning. It is divided into three parts: Syntactic Analysis of Space, Socioeconomic Modeling, and Geodemographic Analysis using Fuzzy Logic. Students will learn key concepts and techniques such as syntactic measures, spatial socioeconomic unit analysis, and fuzzy clustering. The course aims to enhance students' understanding of geographic space, highlighting the significance of spatial relationships and processes in analysis and design. By the end of the course, students will be able to manage and analyze geospatial data, explore spatial relations, model socioeconomic units, and apply fuzzy logic in spatial analysis.
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6647. Environmental Impact Assessment Methods and Techniques - Natural Resources Management
Τhe course provides essential scientific knowledge and practical experience to assist students in getting involved in the design of development projects with a focus on sustainability. It covers environmental policy, strategic impact assessment, and the use of modern technological tools for mapping and evaluating spatial environmental data. Students will learn to analyze natural and anthropogenic conditions, make educated decisions, and work effectively in interdisciplinary teams. Key learning points include understanding environmental governance in the context of climate change, adopting to new conditions, and respecting diversity and the natural environment. The course emphasizes environmental spatial planning using GIS, focusing on Environmental Impact Assessment and Natural Resource Management. Educational objectives include understanding the nature, distribution, and assessment of natural resources, protecting these resources, and mitigating environmental impacts from human activities, within the relevant legal framework.
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6652. Real Property Valuation - Land Management
The course focuses on equipping students with comprehensive knowledge and practical skills essential for managing urban spaces within the real estate market and sustainable land management frameworks. Covering a wide spectrum from legal foundations to cutting-edge technologies, the course delves into property rights, valuation methodologies, and the role of digital tools like BIM and Digital Twins in urban planning and management. Key topics include international principles for sustainable development, property valuation methods, land policy, and regulatory frameworks. Emphasis is placed on understanding the real estate market dynamics, including factors influencing property values, financing mechanisms, and policies for affordable housing. The course also addresses legal aspects, such as property taxation and dispute resolution, alongside ethical considerations in professional practice. Upon completion, students will possess the expertise to navigate complex issues in real estate and contribute to the advancement of scientific topics and the development of tools related to the operation of a sustainable real estate market and land management.
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6665. Application of Informatics in Road Transport
The course explores the integration of advanced technologies in transportation systems, focusing on Intelligent Transportation Systems (ITS), Geographic Information Systems for Transportation (GIS-T), Remote Sensing applications, and Location-Based Services (LBS). Students delve into the technological components, societal impacts, and applications of ITS in road safety, traffic management, urban mobility, and supply chain logistics. GIS-T provides a foundation for designing road networks, optimizing transit routes, and managing road infrastructure. Remote Sensing techniques equip students with skills in using various sensors for road quality assessment, object detection, and behavior recognition. Additionally, the course covers the implementation and evaluation of LBS for navigation and tracking in transportation systems. By integrating theoretical knowledge with practical applications, students gain expertise in evaluating, designing, and applying intelligent solutions that enhance efficiency and safety across transportation networks.
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6671. Spatial Databases
The course focuses on Relational Database Management Systems (RDBMS) and Spatial Database Systems (SDBMS), emphasizing the modeling, structuring, indexing, and processing of spatial data. Students gain insights into real-world SDBMS tools like PostgreSQL and its extension PostGIS, which support advanced geometrical representations according to OGC standards. Special applications include managing and visualizing geospatial data in web environments, handling movement data, and ensuring interoperability across SDBMS platforms. Upon completion of the course, students will possess the knowledge and skills to model geospatial problems effectively, design and implement Spatial Databases, and develop tools and services for storing, searching, and visualizing spatial data. They will be able to solve complex geospatial problems in an innovative way and adapt them for practical use in fields such as cadastral mapping, movement data analysis, and 3D visualization.
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6675. Applications of Geostatistics in Geological Sciences
The course explores fundamental Geostatistical concepts and their practical application in addressing challenges related to mineral exploration, with a particular emphasis on estimating the ore reserves of a mineral deposit. Topics include data acquisition, database preparation, geological modeling, and statistical analysis of exploration data. Special emphasis is placed on non-parametric statistics, spatial correlation, variogram modeling, and estimation algorithms such as Kriging. Students explore structural analysis of deposits, calculation of variograms, and evaluation of estimation errors through grade-tonnage curves. Upon successful completion of the course, students will possess knowledge of the tools and techniques of Geostatistics and how they are applied to achieve specific goals. They will be able to analyze and process the available exploration data, integrating the results into a unified numerical block model, and implementing the numerical block model using Excel, the R programming language, as well as specialized commercial software.
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6676. Applications of Geoinformatics in Mining
This course focuses on techniques and technologies for collecting, analysing and rendering geospatial data to solve problems related to the whole cycle of mining projects and their impacts on the environment. Students will learn to search for information in specialised databases and exploit it using appropriate software. The course covers methods for land use analysis in mining areas, risk modeling, and monitoring surface deformation. It also includes advanced techniques for collecting and utilizing geospatial data from satellite, air, ground, and marine techniques and technologies to optimize mining operations and mitigate environmental impacts. Additionally, students will be introduced to marine law and its relevance to deep-sea mining, covering environmental issues and relevant technologies. Upon successful completion of the course students will be able to identify and evaluate potential environmental impacts and risks from the development of mining projects, evaluate alternatives for the restoration and enhancement of areas and present the results in cartographic form.
Specialization Courses - Spring Semester
Each course has 7.5 ECTS. Students select 4 out of 20 courses
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6691. Communication skills for engineers (Fall Semester)
This course is designed to enhance students’ knowledge of written and oral communication skills in an engineering context. The course will help students to properly structure and write their course assignments and dissertation. In particular, students will learn how to manage and evaluate relevant and reliable sources, cite sources appropriately in their written material, write abstracts and reports concisely and meaningfully, write critical literature reviews and critically analyse key issues in engineering topics both in a written and an oral format. This course is interdisciplinary, and is mainly based on the use of case studies addressing a number of topical engineering issues (e.g. sustainability, engineering failure analysis, engineering ethics, energy transition, etc.). By engaging with these case studies, students will not only refine their communication skills, but also deepen their understanding of specialised engineering terminology while gaining valuable insights into the principal challenges faced today.
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6692. European and Greek Technical Law (Spring Semester)
The "European and Greek Technical Law" course is offered to multiple schools at the National Technical University of Athens, including Electrical, Mechanical, Chemical Engineering, and more. It introduces students to the fundamentals of International Law affecting the energy sector, such as investment and energy transit laws, as well as International Maritime Law. A key focus is on European Law, particularly the legal frameworks governing EU institutions, environmental policies, and energy regulations. Additionally, it includes references to European Tax Law, highlighting its cross-sectoral relevance. The course also covers Greek Law, providing essential knowledge of Greek Public, Constitutional, and Civil Law, which young engineers need for their professional activities. Structured to address the legal relationships and principles relevant to technical professions, the course equips students with the understanding required to navigate the legal aspects of engineering projects at both national and international levels.