Remote Sensing in Urban Geography
Aim of this course is to provide you with an overview on geographic processes of urbanization, the related demographic and structural changes of cities, and data analyses methods using remote sensing data for applications in urban geography.
Humankind is within its largest migration ever: from rural areas into cities. The drivers of this global process of urbanization from demographic to economic and the related structural changes cities are facing will be discussed in this course. Remote sensing is one crucial data source in this dynamic transformation and its products are highly relevant for urban planning, as well as environmental management. Within this course different approaches and techniques are covered focusing on deriving relevant information about urbanized areas on different levels of detail. Uni-temporal-, multi-temporal-, and time series based image classification, segmentation, the analyses of point patterns, GIS analyses to assess spatial context and dependencies, as well as analyses in the 3D domain will be addressed in this course. This will be done providing and discussing example applications from different regions globally (e.g. urban sprawl analysis of megacities, the development of new dimensions of urban landscapes such as mega-regions, the rearrangement of business districts within the urban landscape, etc.). You will learn what capabilities Earth observation data, methods and products have for urban research and applications and how to design remote sensing based urban analysis, how to avoid caveats, troubleshoot errors and interpret the results.
General Course News and Updates
Our new EAGLEs arrived! We welcomed our new international EAGLE students from the US, Ecuador, Bangladesh, Ruanda or Germany for the upcoming winter term and introduced the lectures as well as the courses. In the evening we had a joint dinner to get to...read more
On Monday, 24th of September from 1:30 onwards the following EAGLE students will present their M.Sc. idea. Everybody is welcome to join their presentations and to provide feedback: Julia: "Time-Series Analysis of Sentinel-1 and Sentinel-2...read more
On Monday, 24th of September, at 1pm the following internship reports will be presented: Bharath: "Installation and Characterization of an imaging Spectrometer for the UAV-based remote sensing" Johannes: "Crop classification based on S1/S2 in...read more
Pilar Endara started her M.Sc. thesis on "Time series analysis of flooding and vegetation patterns in wetlands of the Colombian Orinoco Basin" The ecosystems that are present within Colombian Orinoquia flooded savannas are currently being threatened by conversion of...read more
The following students presented their innovation labs, internships and ideas for MSc. thesis: Ahmed: Innovation Lab at DLR (team of Ursula Gessner) and Master Thesis Idea: Title: Status of Agricultural Lands in Egypt using Earth Observation Maninder (at DLR,...read more
Our 2018 EAGLE summer dialogue took place last Friday, 22nd of June and was a great place to meet all students, lectures, staff of the department and quite some external guests from all around Europe.read more
Today some of our EAGLE students presented their internship and innovation laboratory projects. Very interesting topics and they obviously applied and deepened their remote sensing knowledge a lot. Julia Sauerbrey: Prediction of Organic Matter Content from Sentinel-2...read more
the application deadline for our next term of the international M.Sc. program EAGLE “applied Earth Observation and Geoanalysis of the Living Environment” is approaching. Application for the upcoming winter term are accepted until May 15thread more
The course "from field work to spatial data" by Tobias Ullmann and Martin Wegmann is covering the whole range of field campaign planning and especially training all necessary methods such as GPS handling, coordinate systems, setting waypoints or finding locations. In...read more
Jakob Schwalb-Willmann just started his M.Sc. thesis titled "A deep learning movement prediction model using environmental data to identify movement anomalies". He will combine animal movement and remote sensing data in order to develop a generic, data-driven DL-based...read more