- Full List of Supporters: https://www.geo.university/pages/certificates14676707Supported by_____________________________________________________________________________________________This certificate was issued by GEO University with Blockchain technology and has Certificate IDCERTIFICATE OF COMPLETIONFebruary 4, 2020Learn Hyperspectral Remote Sensing from the Scratchhas successfully completed the course of GEO UniversityGianfranco Di PietroThis document certifies that








Full List of Supporters: https://www.geo.university/pages/certificates







14676707

Supported by
_____________________________________________________________________________________________
This certificate was issued by GEO University with Blockchain technology and has Certificate ID
CERTIFICATE OF COMPLETION
February 4, 2020
Learn Hyperspectral Remote Sensing from the Scratch
has successfully completed the course of GEO University
Gianfranco Di Pietro
This document certifies that
Gianfranco Di Pietro
Understanding a problem or project that involves satellite imagery can be very difficult and easily can come to a dead-end. There are numerous of Earth Observation satellites orbiting the earth and produce vast amount of data. Data that need to be processed, analyzed, and valuable information to be extracted.
Earth Observation satellites or Remote Sensing satellites contain payloads (sensors) that capture parts or the entire globe at different wavelengths (spectral bands). A primary categorization of these sensors are:
Optical (multispectral, hyperspectral)
Thermal (multispectral, hyperspectral)
Synthetic Aperture RADAR (SAR)
Of course there are a few other types sensors, but the above are the most mature and used in an operational manner. The main focus of the course is at the hyperspectral optical remote sensing. Due to the nature of the subject, several concepts, processing chains, algorithms and methods discussed in this course are also applicable to other domains (optical multispectral and thermal).
Based on my past experience, research and knowledge I composed this course with one thing in mind: help students, professionals, or even researchers to understand the main concepts of hyperspectral imagery and how you can place them in your everyday-work-life. Starting from a quick introduction about remote sensing and hyperspectral imaging, we continue to the various applications hyperspectral data are being used (from the Earth Observation perspective). At the core of the course, students get familiar with the main processing concepts and techniques applied on hyperspectral data. Four major processing workflows are being analysed:
Spectral Mixing and Unmixing
Spectral Matching and Labeling
Spectral Library Building and Updating
Spectroscopy and Object Parameter Estimation
In each of these series of lectures, enrolled students are provided with extensive written documentation to further study the presented concepts and methods.
This course is recommended for anyone who needs to understand and start working with hyperspectral data and imagery. People who are about to start either a Remote Sensing project or start to learn the basics of remote sensing, as well as those who have come to a dead-end in the middle of a remote sensing/earth observation project and need to know how hyperspectral data can help them overcome their problems.
Skills / Knowledge
- Principles of Hyperspectral or Imaging Spectroscopy concepts
- Spectral Mixture Analysis
- Dimensionality Estimation and Reduction
- Endmember Extraction Algorithms
- Abundance Estimation Algorithms
- Spectral Similarity Measures, Matching & Labeling
Issued on
February 4, 2020
Expires on
Does not expire