Aim
In this course we will learn the alternative image analysis paradigm of object-based image classification. Image objects are areas in images which consist of pixels from the same land-cover class (e.g. buildings, water surfaces, vegetation) and allow the application of additional image classification methods in comparison to pure pixel-based methods and the integration of multi-modal date (e.g. vector data).
Content
In the course we will use satellite images and high resolution aerial images in combination with vector data and analyze various image classification methods (nearest neighbor -> random forests -> deep learning) to extract relevant information from the images.
We will use the software “eCognition”.
The course will be held on 3 days in Würzburg plus an introductory lecture which is being held online.
Session 1: getting to know to image objects and eConition software, basic classification methods
Session 2: advanced classification (Machine Learning)
Session 3: Deep Learning
Coding
Software
Techniques
Content
General Course News and Updates
EAGLE summer dialogue 2022
After two years we finally had our EAGLE summer dialogue again with many Earth Observation alumni, now working in various research organizations and companies. Great to talk to all our past and present students and also seeing all the students getting to know each...
WWF course on applied Earth Observation
Our EAGLE students joint a course offered by the earth observation unit at WWF and learned how to apply remote sensing within a conservation NGO. They learned a lot and their results are published as story maps on their webpage...
Inno lab and internship presentations
On Friday, 8th of July, at 9:30 we will have the following presentations: Jana Maier (InnoLab at DLR): Multitemporal SAR Analysis for Sentinel-1 metrics based Land Cover Classification in West Africa - InnoLab in Agroecosystems and Phenology at DLR. Nora Nieskens...
MSc defense by Antonio Castaneda
On Friday, 1st of July at 9am Antonio will present his M.Sc. thesis "Potential and limits of using UAS in forest monitoring". From the abstract: "The exponential development, usage, and application of uncrewed area systems (UAS) have given remote scientists a clear...
internship, inno lab and MSc idea presentation
On Monday, 30th of May, from 10am onwards, we will have the following presentations: Ása Dögg (Inno-lab): "Potential of Sentinel-1 data for research and monitoring in Tröllaskagi peninsula, Iceland - Snow cover mapping using S-1 time series."Supervisors: Tobias...
Internship and Inno Lab presentations
On Friday 20th of May at 9am we will have the following internship and inno lab presentations: Andrea Cardenas (Internship at DLR): “Data analysis of the refugee crisis in West Africa and definition of test sites in NRW – Germany”supervisor: Martin Muehlbauer Ása Dögg...
EAGLE application in 2022
We received again more than 200 applicants from all over the world. In total applicants from 42 different countries applied to our international Earth Observation M.Sc. program, covering countries such as Hungary, Morocco, Malaysia, Kenya, Nepal or Columbia. We are...
EAGLE application deadline 2022
Our application deadline for 2022 is approaching. If you want to study applied Earth Observation and learn about a variety of remote sensing sensors and methods as well as about fields of applications, submit your application at the latest on May 15th. Accepted...
MSc defense by Haiyin Ye
On Friday 20th of May at 9am Haiyin will present her M.Sc. thesis "Monitoring Gypsy Moth Outbreak Using Sentinel-1 and Sentinel-2 Data". From the abstract: "Gypsy moth Lymantria dispar (L.) is a serious pest in deciduous forests, the larvae of which can feed on a...
inno lab and MSc defense Jakob Wachter
this Friday, 22nd of April, at 9am we will have one inno lab and one M.Sc. defense, both by Jakob Wachter. inno lab: "Assessment of climate-induced drought impact on crop types in bavaria" (Tobias Ullmann) M.Sc. defense: "Potential of webcam Imagery as reference data...