EAGLE 2016 welcome

EAGLE 2016 welcome

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,

Explore species-environment interaction

Explore species-environment interaction

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 dealt with, e.g. the decrease in accuracy of tracking devices in dense vegetation. In this innovation laboratory ...

Deployment of a multi-classifier approach to improve land cover classification accuracy

Deployment of a multi-classifier approach to improve land cover classification accuracy

multi_classifier

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. The student is expected to gain a deep knowledge of applied Machine Learning algorithms within this innovation laboratory.

Stereo photogrammetry for multi-temporal surface models based on aerial imagery

Stereo photogrammetry for multi-temporal surface models based on aerial imagery

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 analysis based on parallax and obtaining information on vertical forest structure. As compared to the state-of-the-art LiDAR data, the stereo ...

Estimation of actual evapotranspiration in irrigation agricultural area of Uzbekistan using high resolution multi-frequent synthetic remote sensing data

Estimation of actual evapotranspiration in irrigation agricultural area of Uzbekistan using high resolution multi-frequent synthetic remote sensing data

Evapotranspiration_irrigation_agricutlure_Uzbekistan

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 suitable to provide area based indicators for the evaluation of the efficiency and productivity ...