The textbook you need to understand spectroscopy for Remote Sensing
So, what is object parameter estimation using spectral data, i.e. spectroscopy? What is spectral discrimination? Do they have something in common? Can a machine learning approach help to tackle both problem?
This textbook course answers all these questions and more! The textbook book course presents not only the basic theoretical principles of spectroscopy, spectral matching, labeling and discrimination, but also a new novel method, the k-step methodology, that automates the entire process. Both for object parameter estimation and spectral discrimination!
A machine learning approach is incorporated to achieve the full automation; the simple genetic algorithm.
For all these topics, extensive measurements were collected and experiments were performed in order to prove the concept.
Spectral measurements of different varieties of plants (vetch and lentil) were used to showcase the subtle spectral discrimination concept.
Regarding the parameter estimation, soil spectral measurements were taken along with chemical analysis to quantify the soil organic matter.
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.