• Introduction to Remote Sensing and Photointerpretation: Fundamental concepts, principles, methods, techniques, and applications.
• Satellite Data Collection and Open-Source Geospatial Databases
• Physical and Spectral Principles of Remote Sensing
• Remote Sensing Sensors and Data Acquisition Systems:
o Heterogeneous remote sensing systems: satellite, aerial, terrestrial, marine, and underwater.
o Manned and unmanned systems.
o Optical, multispectral, hyperspectral, thermal, radar, and LIDAR sensors.
o Advantages and limitations of each system.
• Preprocessing of Remote Sensing Data:
o Histograms, multispectral images, and pseudocolor composites.
• Photointerpretation Fundamentals:
o Photo-identification elements, keys, and land use/land cover mapping systems.
• Methodology for Analysis and Interpretation:
o Spectral signatures and thematic class statistics.
o Band ratios and spectral indices.
• Automation Techniques: Object and thematic category detection.
• Change Detection and Time-Series Analysis
• Practical Applications:
o Road construction, hydraulic and irrigation works.
o Spatial planning and urban development.
o Geology, soil science, and water resource management.
• Advancements and Future Prospects in Remote Sensing Systems and Sensors
- Teacher: Δημήτριος Αργιαλάς
- Teacher: Κωνσταντίνος Καράντζαλος
ECTS : 5
Language : el
Learning Outcomes : Upon completion of the course, the student will be able to: • Collect and visualize remote sensing data, describe basic photointerpretive characteristics of objects/thematic categories. • Recognize the differences in reflectivity of objects/thematic categories in different spectral regions and be able to apply operations and automations in their detection and localization. • Estimate the suitability of spatial, radiometric, spectral, and temporal data analysis from satellite, aerial, terrestrial, and marine acquisition systems and multispectral, hyperspectral, radar, lidar, thermal, etc. sensors and apply basic processing for their analysis. • Apply basic photointerpretation procedures and analysis of heterogeneous remote sensing data for mapping vegetation, water, and other thematic categories. • Apply basic processing to time-series data for change detection.