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
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
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
The data provided by aerial imagery are amongst the oldest sources of spatially explicit information for modern-time environmental management. These data are often captured over landscape-level domains using overlapping flight stripes to enable stereo photogrammetric...read more
Estimation of actual evapotranspiration in irrigation agricultural area of Uzbekistan using high resolution multi-frequent synthetic remote sensing data
Actual evapotranspiration (ETact) is an essential component of the water balance and its determination for large areas is difficult on regional scale and can be explored within an innovation laboratory. The use of remote sensing data to determine ETact is particularly...read more
Remote sensing based crop mapping is still challenging when just relying on optical information as the only data source. Due to the unavailability of adequate optical satellite images the integration of SAR is promising and can be explored within an innovation...read more