Remote Sensing of Urban Areas

Lecturer

Hannes Taubenböck
Henri Dubray

ECTS

5 ECTS

 

Aim

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.

Content

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

MSc idea and interesting presentations

MSc idea and interesting presentations

on Friday 18th of February at 9am we will have the following presentations:   Jakob Rieser - Thesis Idea: "A Synergistic Use of Optical and SAR Remote Sensing Data for the Long-term Evolution of Biocrusts and their Activity across diverse Dryland Ecosystems"....

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Our EAGLEs featured on the University page

Our EAGLEs featured on the University page

Our EAGLEs Sofia, Annika, Antonio, Andreas and Nils are featured on the University webpage with their UrbanSens idea of combining mobile IoT sensors and Earth Observation data for urban climate monitoring. Their success winning the DLR Copernicus challenge rewarded...

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MSc defense by Yomna Eid

MSc defense by Yomna Eid

Yomna will present her M.Sc. thesis "Assessment of ESA CCI+ and NASA MODIS-LST in Ecological Transects of Australia" on January 14th 2022 at 10am. From the abstract: "Identifying the best-performing MODIS LST products available for scientific analysis is instrumental...

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MSc defense by Marius Witt

MSc defense by Marius Witt

Marius Witt will present his M.Sc. thesis "Investigating discharge dynamics at catchment level usingremote sensing timeseries" on Friday 14th of January 2022 at 9am. From the abstract: The anthropogenic induced climate change is one of the foremost challenges of the...

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Great dashboard by our EAGLE students

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...

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MSc defense by Christabel Ansah

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...

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MSc defense Diego Alarcon

MSc defense Diego Alarcon

Diego will present his M.Sc. thesis "Exploring the potential of remote sensing using machine learning to predict yields for table grape farms in Chile" on Friday, 10th of December at 9am. From the abstract: Table grape is among Chile most important crops, the country...

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