Monitoring of Agricultural Landscapes
The module addresses methods on how Earth Observation and the use of geoinformation can support different fields of land and water management. Focus is set on remote sensing based concepts and methods for monitoring and supporting resource management in agricultural landscapes. Achievements and challenges are elaborated. The students will be guided to gain knowledge in selected practical examples.
Mapping the parameters
- Mapping cropland extent, cropland use, and cropping intensity at different scales
- Rainfed agriculture, irrigated cropland or pasture? Disentangling of complex vegetation classes
- Quantification of cropland production, status quo and developments
- Aproaches to mapping land abandonment
- More crop per drop? Assessing land and water use in irrigated landscapes
Remote sensing contributions to multi-sector assessments
- Population growth and the competition for land in rural areas
- Understanding the role of lakes and wetlands in agricultural landscapes
- Vulnerabillity of agricultural landscapes under changing climate conditions
- Crop yield predictions
Practical part on cropland use intensity in irrigation systems in Central Asia.
Small classification codes in R will be written (classification and accuracy assessment).
ArcGIS, ENVI / IDL, R
Practical work: Mapping cropland extent, cropland vegetation phenology, and crop types at different scales (Landsat / MODIS)
- Classification (random forest, knowledge-based decision trees)
- Accuracy assessment
Seminar plus practical part.
General Course News and Updates
The EAGLE course "Remote Sensing in Biodiversity and Conservation Science" took place in the last week of the summer term at the field research station in Fabrik Schleichach, Steigerwald. 20 biology and EAGLE students worked and lived together for one week and...read more
The first field methods course in our EAGLE MSc programme took place in the JECAM test site of DEMMIN-Germany (close to the city of Demmin in Mecklenburg-Vorpommerania) from 12.- 17.6.2017. Six EAGLE students, one colleagues of DLR, Dr. Erik Borg, and two lecturers,...read more
The course on UAV application for Remote Sensing started successfully. The weather was good enough to do some first flights. In the next weeks and months more flights will be undertaken and data collected for different fields sites in order to gain more information...read more
The new term started with the course “Object-oriented image analysis”. It is a hands-on seminar covering eCognition by Dr. Michael Thiel and Dr. Christian Geiss. Christian is an invited guest lecturer from DLR’s Remote Sensing Data Center (Department: Geo-Risks and...read more
one of our field sites in the Steigerwald For several upcoming EAGLE courses we visited potential field sites and tested our equipment. During this first field work of the year our UAV and D-GPS data collection were tested in the Steigerwald at the research station of...read more
Our EAGLE 2016 students visited the DLR-EOC last Friday and got a very good overview of the work done by the scientists at DLR. Many different topics were covered and nearly all applications of applied earth observation research done at DLR-EOC were presented. ...read more
On Monday 17th of October we welcomed our new EAGLE students. The EAGLEs in 2016 are from Afghanistan, Bangladesh, Columbia, Egypt, India, Iran, Pakistan, Sweden and Germany. After the official welcome by all lecturer and the study program coordinator Christopher Conrad and the head of the remote sensing department and director of the DLR-DFD, Stefan Dech,read more
The course on remote sensing for biodiversity analysis covered 10 days of field work, R coding, testing field methods such as UAVs and lots of hiking in the National Park Bavarian Forest. This year we had sunny and rainy weather and on the peaks also snow which made...read more
Analyzing species-environment interaction is feasible using various data and method. An increasing technology is the tracking of animals and especially its linkage to remote sensing, as covered in AniMove.org. However, with this technology new challenges have to be...read more
This study will examine whether the application of hybrid classifiers increases the classification accuracy in comparison to a single classifier. A combination between parametric and non-parametric classifiers will be applied and their performance will be assessed....read more