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
Data collection and automation of geospatial database import and update processes.
Formats and representations of spectral spatio-temporal data and their characteristics.
Systems and architectures for storage, management, analysis and delivery of large geospatial data and products in cloud computing systems.
Data visualisation and dimensionality reduction strategies.
Statistical processing and analysis for data harmonization and merging.
Web-based processing and high-performance computing systems for land observation data.
Data and time series analysis for change, object and feature detection.
Big data analysis using machine learning techniques with applications in precision agriculture, water quality assessment, automatic detection of changes in urban, natural and marine environments.
