: Geography Department

Earth Observation Lab

Geography Department
Earth Observation Lab

"We advance terrestrial
Earth observation
from space"

Our focus is on developing and applying remote sensing methods to better understand global change related to land systems, adhering to FAIR principles and adopting an open data philosophy. We concentrate on mapping land cover, land use and related spatio-temporal change patterns. Applications extend from agriculture (both cropland and grassland), over forest ecosystems to urban areas. The analysis of long and dense time series from Landsat and Sentinel data is core for our research - from landscape to continental scales. Hyperspectral image analysis is a second cornerstone of the Earth Observation Lab.

Faculty of Mathematics and Natural Sciences - Earth Observation Lab

Earth Observation Lab | Advanced Remote Sensing topics using R

Advanced Remote Sensing topics using R

German: Modul Vertiefungsmodul Vegetationsfernerkundung

Prerequisites: Introduction to Remote Sensing
B.Sc.: optional (recommended especially for students with interest applied programming and bachelor thesis in methods of remote sensing)
B.A.: optional

Fig.:

RStudio environment. Fig. mix from https://upload.wikimedia.org/wikipedia/commons/thumb/1/12/R_logo_2000.png/220px-R_logo_2000.png and http://www.rexamples.com/img/rstudio-run-source.jpg. Fig.: Katja Janson

The monitoring and mapping of vegetation and land cover is one of the key activities in Earth observation (EO). Advanced EO products are pivotal for many geographic and environmental studies. In this module students learn concepts and techniques for analyzing and mapping vegetated land cover and its characteristics at various spatial scales and with different sensor systems. Data analysis is fully done in R and students learn to create customized R-scripts along a series of processing tasks throughout the semester.