Earth Observation Network

Exchange of Earth Observation training approaches and data

teaching

Sharing Earth Observation training approaches to improve course content and approaches

Data

Exchange of Earth Observation Data Set for training that provide challenging and insightful analysis options

Network

Overview of german remote sensing teaching and research for lecturer and students

Aim

Exchange and manage informative remote sensing data for teaching activities. Aim is to compile various data sets for the diverse teaching goals and share course approaches and content.

Within this network we aim to exchange data sets and best-practice approaches for training remote sensing and spatial data analysis. Irregular and informal workshops on data collection, data analysis and software solutions are organized.

Teaching Data

Remote Sensing data exchange for training, especially with UAV data acquisition and information exchange on approaches, methods and challenges

Members

Department of Remote Sensing

Institute of Geography – University of Wuerzburg

We conduct research in various regions from Europe to Africa up to Arctic and Antarctic for diverse applications. Concerning teaching we focus on applied remote sensing mainly within the international EAGLE M.Sc. program and international capacity building. Our Earth Observation training is conducted with a variety of software such as R, Python, QGIS, Arc*, ENVI, SNAP, Data Cube, … for topics like land management, conservation, ecology, coastal or urban mainly using passive remote sensing data. For courses we use data from UAVs for regional examples up to tropical deforestation analysis in South America.

Oswald-Külpe Weg 86, 97074 Würzburg

martin.wegmann@uni-wuerzburg.de

Ecosystem Dynamics and Forest Management Group

Technical University of Munich

We study ecosystem dynamics with a particular focus on forest ecosystems. We use a wide variety of tools, including remote sensing, simulation modeling and field observations. We thus tackle pressing ecological questions from a multi-method perspective, covering a wide range of temporal and spatial scales. We have strong ties to the Berchtesgaden National Park, Germany’s only Alpine National Park! Our research, however, has application beyond Germany, with study sites across Europe, the USA, and Japan.

Hans-Carl-von-Carlowitz-Platz 2, 85354 Freising

cornelius.senf@tum.de

Research Group remote Sensing & Spatial Modelling

Institute of Landscape Ecology – University of Muenster

We study and teach the acquisition and analysis of spatio-temporal environmental dynamics in a board spectrum of landscape-ecological topics. We combine multi-scale remote sensing data with methods of spatial modelling in order to obtain continuous spatio-temporal information from limited ecological field samples. The complexity of environmental systems requires the use of modelling strategies that take complex relationships into account. For this reason, we focus on the application of machine learning methods. In addition to their application for research questions in the context of landscape ecology, we also develop new modelling strategies for spatial and spatio-temporal data.

Heisenberg Str.2, 48149 Münster

hanna.meyer@uni-muenster.de

Forest Inventory and Remote Sensing

University of Göttingen

Our research and teaching focuses on modern approaches of forest monitoring where we combine concepts of sample-based statistics with up-to date remote sensing and geospatial technologies. Our research projects cover various regions of the world including central and South America, Indonesia, and Southern Africa. We organize and deliver courses in remote sensing image processing, applications of UAVs in the context of environmental monitoring and deep learning approaches for image analysis at the Faculty of Forest Science and Ecology in Göttingen. Our remote sensing courses use 100% open-source software. Through our research networks we participate in interdisciplinary research projects such as the Biodiversity-Exploratories, where we develop remote sensing assisted biodiversity monitoring approaches. With a strong background in forestry, we are also developing monitoring systems in the context of forest management where we utilize 3D point clouds from terrestrial and airborne laser scanners. At the campus in Göttingen we host the UAV campus group.

Büsgenweg 5, 37077 Göttingen

paul.magdon@forst.uni-goettingen.de

latest news

Workshop in the National Park Bavarian Forest

Workshop in the National Park Bavarian Forest

Our first workshop took place in October 2021 in the National Park Bavarian Forest. Beside discussions of our Earth Observation research, potential collaborations, new remote sensing developments, challenges of software applications also potential of joint teaching...

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workshop on UAV knowledge exchange

workshop on UAV knowledge exchange

In October 2021 we will have a small workshop with University members from e.g. Münster, Marburg, Göttingen, Munich and Würzburg on UAV applications in environmental research and especially in exchange of best-practice, sensor and UAV mission planning etc. and of...

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Earth Observation Network started

Earth Observation Network started

After quite some discussions among colleagues of different universities and the identified joint interest in exchange of teaching approaches and lesson-learnt as well as in application of e.g. UAV in research projects and of course also joint research and projects, we...

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Data Sets

The data set in Steigerwald consists of ….. Especially in-situ data such as ….

Data Set Steigerwald

Frankonia, Bavaria, University of Wuerzburg

The study region X provides in-situ data for … and remote sensing data of …

Data Set ...

somewhere, University of ...