syllabus
June 28, 2021
15:30 h "Central European Time (CET)"
Presentation
CIVIS Copernicus satelites
Madrid, from satellite view
14:00-15:20
José A. RODRÍGUEZ-ESTEBAN
Madrid Heat Island
15:30-16:50
Elena ARAGONESES
June 29
Physical fundamentals of remote sensing
14:00-15:20
Vicente TORRES-COSTA
Pixel-based and object-based
paradigm
in image classification
15:30-16:50
Taïs GRIPPA
June 30
Synthetic aperture radar
14:00-15:20
Ian BROWN
Introduction to machine learning for remote sensing
15:30-16:50
Taïs GRIPPA
July 1
Introduction to UAS and photogrammetric
processing. Theory and practical
issues
14:00-15:20
Emmanuel VASSILAKIS
Techniques for high accuracy field
measurements, using Real Time
Kinematics GNSS equipment and T
errestrial LiDAR
15:30-16:50
Emmanuel VASSILAKIS
July 2
Fluorescence (INTA, Spain-
Copernicus Relay)
14:00-16:50
Marcos Jiménez-Michavila
July 5
Workshop: cities and remote sensors,
ESA-RUS Copernicus*
Special session with a joint exercise
13:30-18:00
Miguel CASTRO GÓMEZ
July 6
Remote Sensing in Agriculture 4.0
14:00-15:20
Felipe YUNTA
Soils and remote sensing
15:30-16:50
Zulimar HERNÁNDEZ
July 7
Acquisition and interpretation
of Point Clouds for
Several Geological Applications
14:00-15:20
Emmanuel VASSILAKIS
Quantification of shoreline
displacement using high
spatial resolution remote sensing data
15:30-16:50
Emmanuel VASSILAKIS
July 8
Applied calibration and atmospheric correction
14:00-15:20
Ian BROWN
Land cover monitoring with
Sentinel and Very‐High resolution imagery
15:30-16:50
Taïs GRIPPA
July 9
Supporting evidence-based policy
making in sub-Saharan African
cities with Sentinel imagery
14:00-15:20
Eleonore WOLFF
End of the course. Diplomas
15:30-16:00
CIVIS Copernicus satellites
* In this exercise we will employ RUS Copernicus Virtual Machines to process a multi-temporal dataset of Sentinel-1 SLC products and derive coherence (in SNAP), which will be used later to map urban areas over a region of interest in Germany. For that, we will use different methods using Python scripts provided in JupyterLab and compare their results.