The complete theoretical framework with experiments and results
An introduction to the Network Based Method concept regarding the spectral unmixing of hyperspectral images. Bringing together several years of research performed in the unmixing domain, the readers can understand the principles behind the theory of the NBM framework and corresponding algorithms. A comprehensive analysis is also made on the current state-of-art of techniques and methods used to spectrally unmix remote sensing/hyperspectral data. The textbook course is intended for researchers, tutors, and students who want to read and understand the mathematical framework of NBM along with corresponding implemented algorithms. The full spectrum of spectral unmixing is covered, i.e. estimation of number of endmembers, endmember extraction, abundance estimation.
I'm a Remote Sensing and a Surveying Engineer. I received my degree from NTUA in 2010, where I also received my Ph.D. in hyperspectral remote sensing in 2016. From graduation in 2010, my career started as a Researcher Associate and Teaching Associate in the Laboratory of Remote Sensing of NTUA. From that time I also worked at several private companies as a Remote Sensing Expert and Geospatial Analyst. From the beginning of 2015 I was positioned as Senior Earth Observation Expert. During these years, I have participated in more than 20 funded European Commission and European Space Agency projects, have over 16 peer reviewed scientific publications in the field of Remote Sensing, and have an international patent in hyperspectral data compression.
My main research and professional interests are in the optical remote sensing area, where I specialize in data (images, point measurements) processing and algorithm design and development. Some of the software tools that I operate to accomplish my research and business dreams are SNAP, ENVI, IDL, QGIS, ERDAS Imagine, ArcGIS, and Python. I have been working with these tools since 2008.