About
Dr. Martin Bachmann is research scientist with the Applied Spectroscopy Group at the German Remote Sensing Data Center, German Aerospace Center (DLR), Wessling, Germany. He has over 10 years of experience in the fields of hyperspectral data analysis and data pre-processing. For 8 years he was in charge of the data pre-processing chain of DLR’s Optical Airborne Remote Sensing and Calibration Facility (OpAiRS). He leads the work package on “Data Quality Control’ within the EnMAP ground segment, and is involved in the FP7 EUFAR Joint Research Activity on Data Quality Control for airborne hyperspectral and LiDAR pre-processing. In addition, he is also involved in the pre-processing of NOAA AVHRR time series within DLR’s TIMELINE project, and was involved within ESA CCI “fire” within the same field of activity. His research interests also include the development and application of spectral unmixing approaches, and algorithm developments towards the derivation of soil parameters using field, laboratory and airborne spectroscopy. His teaching and training experience is focusing on field and imaging spectroscopy, and includes courses at the Universities of Wuerzburg and Jena, within FP6 Marie Curie Project “Hyper-I-Net”, for Carl-Cranz-Gesellschaftand within DLR capacity building activities.
Courses
Recent News
Great dashboard by our EAGLE students
our EAGLE students created various informative remote sensing and spatial environmental data dashboards and learned a lot how to communicate their Earth Observation research in an interactive online platform. One example by our student Ronald Okoth is shown below and...
MSc defense by Christabel Ansah
Christabel will present her M.Sc. thesis "ASSESSING THE ENVIRONMENTAL IMPACT OF OIL SPILLS IN THE NIGER DELTA, NIGERIA" on Monday 20th of December at 10am. From the abstract: "The Niger Delta region of Nigeria has been battling with an unprecedented number of oil...
MSc Defense by Sandro Groth
Sandro Groth will present his M.Sc. thesis "Using street-level imagery and multi-task deep learning for multi-hazard risk related building characterization" on June 28th at 9am. From his abstract: "Accurate building characterization is a key component of multi-hazard...
MSc defense by Magdalena Halbgewachs
Magdalena Halbgewachs will present her MSc thesis "A Spectral Mixture Analysis and Landscape Metrics based framework for monitoring spatio-temporal forest cover changes: A case study in Mato Grosso, Brazil" on Wednesday 16th of June at 9am. From the abstract: More and...
Review of applications
Dear all applicants in 2021, we are currently working through the first evaluation of all 230 applications and will send out invitations for interviews in the next days/weeks. Unfortunately we are a bit delayed due to the high number of applications and we want to...
high number of application submitted for 2021
The application deadline for the 2021 EAGLE generation passed yesterday and 230 application were submitted. That are 80 more than last year. Check out who started in the 2020 EAGLE generation here. We are now going through each single one and check for general...
EAGLE 2021 application deadline approaching
the application deadline for our international Earth Observation M.Sc. program EAGLE is slowly approaching. Apply before May 15th to be reviewed and potentially interviewed for a place in the 2021 EAGLE group. Check out our courses, our lecturer and most important...
Internship, inno lab and MSc idea presentations
On Thursday, May 20th, at 2pm the following students will present their internship, inno lab or MSc thesis idea: Christopher Chan:“Patching up old Deep Learning code and working with data center remotely” (Internship with DLR, supervisor Benjamin Leutner) Diego...
internship and MSc idea presentation
on Tuesday April 6th 3pm we will have the folling internship and MSc idea presentations: Joy-Giovanni Matabishi, " MESMA of DESIS data to identify Rooftops in Kigali"- Internship/EKUT Luisa Pflumm, "Comparison of the performance of different accessibility layers for...
Great Earth Observation presentations despite distance learning
Despite the online courses we learned and managed to deliver great presentations on remote sensing data analysis in our courses and also improved our virtual presentation skills which might also partially be valuable in future conference or workshop presentations.