Objectives and competences
The objectives of the course are:
• identification of big geospatial databases and use within smart communities,
• understanding and using selected spatial analyzes and measurements, such as spatial distribution, patterns, clusters and spatial relationships,
• understanding and applying GIS-T methodology and network models,
• mapping smart cities and communities for the purpose of analyzing and planning strategic decisions,
• GIS modeling of the business environment for planning strategic transport-logistics decisions.
Competences acquired by students:
• develop geovisualization skills,
• develop geospatial thinking in the field of smart communities and business environments,
• develop digital competence of advanced work with geospatial data and cartographic representations in the case of smart communities and business environments.
Content (Syllabus outline)
1. Challenges of big geospatial databases (definition, use within smart communities).
2. GIS spatial analysis and measurement (definition, types (spatial distribution, patterns, clusters, spatial relationships), application).
3. Advanced GIS-T methods (definition, types (network model, VRP problem, finding location), application)).
4. Mapping for smart cities and communities (definition and use (location perspective on real-time field activities, smart routing and prepareness for risks, finding optimal locations, visualization and mapping of sensor data, mass events, 3D visualization).
5. Mapping for business environment (definition, use (optimization of "internal" transport routes, safety in (inter)storage transport, design of transport routes (roads) and establishment of logistics infrastructure within the company complex, determining the optimal location of the logistics (storage and distribution) center).
Learning and teaching methods
Lectures: Students understand the theoretical frameworks of the course. Part of the lecture course is held in standard classroom while the rest is in the form of e-learning (e-lectures may be given via videoconferencing or with the help of specially designed e-material in a virtual electronic learning environment).
Tutorials: Students enhance their theoretical knowledge and are able to apply it. Practical professional excursions to companies. Part of the seminar is in a classroom while the rest is in the form of e-learning (e-tutorials may be given via video-conferencing or with the help of specially designed e-material in a virtual electronic learning environment).
Intended learning outcomes - knowledge and understanding
Knowledge and understanding:
The student will be able to:
• identify and use data from big geospatial databases in strategic logistics decisions,
• apply selected spatial analyzes and measurements to examples of smart communities and business environments,
• analyze and plan with selected GIS-T methods;
• map smart cities and communities in terms of strategic logistics decisions, real-time activities, smart vehicle routing, location finding, mass events and 3D visualization,
• model the business environment in terms of optimizing "internal" transport routes, risks in (inter)warehousing, designing transport routes and establishing logistics infrastructure within the company complex, determining the optimal location of the logistics (warehousing-distribution) center,
• use modern Esri ArcGIS software with extensions, in conjunction with some SQL, VBScript and Python skills; use the computer program QGIS in cartographic transformations.
Readings
• Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2015). Geographic information systems and science. John Wiley & Sons.
• Werner, M. & Chiang, Y.-Y. (Eds.) (2021). Handbook of big geospatial data. Springer. https://doi.org/10.1007/978-3-030-55462-0
• Mitchell, A., & Scott Griffin, L. (2021). The ESRI guide to GIS analysis. Vol. 2, Spatial measurements and statistics (2st ed.). Esri Press.
• Rodrigue, J.-P. (2024). The Geography of Transport Systems (6th Ed.). Routledge. https://doi.org/10.4324/9781003343196
• Ciglič, R., Geršič, M., Perko, D. & Zorn, M. (Eds.). (2020). Modeliranje pokrajine. Založba ZRC.
• Esri. (b. d.). Introduction to ArcGIS Pro. https://pro.arcgis.com/en/pro-app/latest/get-started/get-started.htm
• Esri. (b. d.). ArcGIS Pro help. https://pro.arcgis.com/en/pro-app/latest/help/main/welcome-to-the-arcgis-pro-app-help.htm
Additional information on implementation and assessment Successful completion of e-lectures and e-tutorials is a prerequisite for entering the exam.
Written examination from theory 35%
Written examination wit GIS program 35%
Research work 30%
For a positive assessment of the subject, each written part of the exam must be positive.
