Skill course: Earth Observation Techniques
 

Category: Skill course
Credit points: 0.2/course day
 

1.  When & where?

September 3-4, 2018
at the Friedrich Schiller University Jena, Institute of Geography, R121 (second floor)
and
September 5-7, 2018
Max Planck Institute for Biogeochemistry, B0.002

 

2.  Outline

Legend

TTheory
PPractice

 

DayTypeContentWho
 
Monday, September 3 Optical remote sensing (incl. preprocessing like atmospheric & topographic correction) 
9:00-10:00TIntroduction to Remote Sensing Concepts: EMSChristiane Schmullius
10:15-11:15TSensor Concepts (Spectral, Geometric, Radiometric, Temporal Resolution)Christiane Schmullius
11:30-12:30TSensor Overview and ApplicationsChristiane Schmullius
13:30-14:30TIntroduction to Image ProcessingSören Hese
14:45-15:45TAtmospheric and topographic correction methodsSören Hese
16:00-17:30PPractical exercises (using ENVI)Sören Hese
 
Tuesday, September 4 RADAR remote sensing for Earth surface 
9:00-10:00TIntroduction to Radar Concepts and Image GeometryChristiane Schmullius
10:15-11:15TSensor Parameters (Wavelength, Polarisation, Incidence Angle)Christiane Schmullius
11:30-12:30TSurface Parameters (Dielectric Constant, Roughness)Christiane Schmullius
13:30-15:30TApplications: Forest (inkl. INSAR, POLSAR)tba
15:45-17:30PPractical exercises using the free software packages ESA SNAP and Quantum GISCarsten Pathe
 
Wednesday, September 5 Atmosphere compositionJulia Marshall
9:00-10:00TIntroduction to sensing of the atmosphere, and atmospheric ECVs. Some discussion about different orbit configurations, and a brief history of remote sensing of the atmosphere. 
10:15-11:15TAn introduction to ground-based remote sensing of the atmosphere, focusing on the FTIR. 
11:30-12:30TPassive emission sensing of greenhouse gases, using the the sensors AIRS and IASI as teaching examples. 
13:30-14:30TPassive scattering sensing of the atmosphere, using the examples of SCIAMACHY and GOSAT. 
14:45-15:45TActive sensing of the atmosphere, using the example of the aerosol satellite CALIPSO and the planned methane mission MERLIN. 
16:00-17:30PPractical session: "Design a satellite", where two groups will be given different measurement goals, and asked to plan and present a hypothetical satellite mission to meet these goals.
 
Thursday, September 6 Vegetation - essential climate variables 
9:00-12:30TNovel data streams (hyperspectral data and fluorescence to monitor vegetation physiology)
  • Principles of proximal sensing, reflectance factors and chlorophyll sun induced fluorescence
  • Proximal sensing of vegetation
  • Hyperspectral Airborne and Proximal Sensing for plant physiology
Javier Pacheco
 
13:30-16:30T+PGlobal monitoring of ecological dynamics with satellite remote sensing
  • Satellite remote sensing of vegetation structure, ecosystem functioning, and biodiversity
  • Satellite remote sensing of landscape dynamics and vegetation phenology
  • Accessing and analysing time series of MODIS satellite products for fluxnet sites from NASA’s ORNL DAAC web service
Xuanlong Ma
 
Friday, September 7 Remote sensing using unmanned aircraftMartin Kunz

9:00-9:30
9:30-10:15
10:30-11:45
11:45-12:00

T/P

Introduction to unmanned aircraft and their use in Earth science (T)
How does a multicopter fly? (T/P)
Creating three-dimensional models from two-dimensional images: structure from motion (SfM) (T)
Dos and Don'ts with unmanned aircraft (T)

 
Friday, September 7 Fire disturbance - Essential climate variablesMarcus Guderle

13:00-15:00

T

Fire detection using remote sensing technique
small-scale detection using LiDAR

 

 

3.  Course material

Presentation by Christiane Schmullius (zip)
Presentation by Sören Hese (pdf) Δ
Material by Carsten Pathe (pdf)
Presentation by Julia Marshall (zip)
Presentation by Julia Marshall (pdf)
Presentation by Julia Marshall (pdf)
Practical by Julia Marshall (pdf)
Material by Javier Pacheco (zip)
Material by Xuanlong Ma (zip)
Material by Martin Kunz (zip)
Presentation by Markus Guderle (pdf)

 

4.  Feedback

The survey gives feedback of 11 (out of 19) participants. Statistics and statements should not be taken as an exhaustive or exclusive list.

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