Applications of Earth Observation

04-GEO-TB2

Lecturer

Christopher Conrad

ECTS

5 ECTS

 

Aim

In this lecture you will gain a broad overview of the applications of remote sensing. Examples from different disciplines and applied Earth Observation projects will provide your with a comprehensive understanding of if, where and how remote sensing can contribute to qualitative and quantitative assessments of the cryosphere, forest ecosystems, agro-ecosystems, the coastal zone and urban ecosystems; amongst others. We will evaluate the potential of passive and active sensor systems and adress the advantages and shortcomings of existing sensors in the optical / mutlsispectral, thermal and microwave domain.

Content

This lecture provides knowledge on applications of Earth Observation with a focus on remote sensing of the land surface. Which research questions of different disciplines can be answered by the means of Earth Observation? What are the main approaches? The module links up remote sensing measurements to geo- and biophysical parameters required for further geoanalysis. Commonly used methodological approaches for the derivation of the different parameters are presented. Examples include amongst others applications in geography, environmental planning, ecology, biology, oceanology, soil science, geology, atmospheric science, but also e.g. pollution control (monitoring) and natural resource management. In addition, the module outlines selected examples, how remote sensing technology can be transferred to the workplace of professionals also beyond science, e.g. via the use of geoinformation systems.

General Course News and Updates

EAGLE Internships

On Monday, 24th of September, at 1pm the following internship reports will be presented: Bharath: "Installation and Characterization of an imaging Spectrometer for the UAV-based remote sensing" Johannes: "Crop classification based on S1/S2 in...

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EAGLE students coding with sweets

Today our EAGLE students applied data munging, pipes, plotting and statistics using colour distribution of sweets. They specifically used the dplyr, ggplot, kableExtra and others to compute derivatives, rearrange the data, plot it and run statistics on colour...

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