Spatial Python for Remote Sensing
In this course we will elaborate large and complex workflows dealing with the analysis and handling of big data using Python. Moreover, we will try to develop a fully automated processing chain in Python for landcover mapping starting with the download of Landsat data, preprocessing, classification and building up a spatial database that enables GIS functionality over large datasets for further analysis.
We will start with the basics of Python programming language and quickly evolve towards image processing techniques with packages such as scipy, numpy, scikit-learn, scikit-image and gdal. We will also focus on arcpy for ESRI software products which allows for a convenient and powerful automatization of spatial analysis functions.
General Course News and Updates
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
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