COURSE CURRICULUM

The course provides a comprehensive foundation in geospatial science, covering key technologies and analytical methods for environmental and spatial data management. It begins with GIS and Spatial Data Management, equipping students with an understanding of spatial data models, mapping fundamentals, and analysis techniques, primarily using ESRI’s software. The Aerial Photography and Digital Photogrammetry module introduces interpretation and analysis of remotely sensed images, stereo imagery, and orthophotography. Scientific Python develops programming skills in Python, focusing on data analysis, visualization, and geospatial data handling using libraries and tools like Jupyter Notebooks. Applied Earth Observation covers radiometric principles, sensor technologies, atmospheric correction, and image data processing for environmental monitoring. Image Processing and Analysis focuses on enhancement, classification, and extraction of information from various image types using both traditional and machine learning techniques. Advanced GIS Methods expands on GIS capabilities with an emphasis on environmental modelling, spatial analysis using QGIS and ArcGIS Pro, and Python scripting for automation. Environmental Resource Survey teaches statistical survey methods for evaluating environmental resources, using R for data analysis and introducing sampling techniques, data fusion, and quality assessment. These modules collectively train students to collect, analyze, and interpret spatial and environmental data using advanced technologies, programming skills, and modelling techniques, enabling them to solve complex problems in real-world geospatial and environmental contexts.