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 handed in on impact of remote sensing for biodiversity monitoring
Anna Stephanie handed in her MSc thesis on “Impact of remote sensing characteristics for biodiversity monitoring”. Very impressive study on multi-scale, multi-model and multi-variable analysis of mangroves in Myanmar. She was supervised by Martin Wegmann. While...
MSc handed in on object-oriented classification of historical maps for ecosystem services
Yrneh Ulloa handed in her MSc “Land change in the Main catchment with an Object Based approach using eCognition” within GCE which dealt with classifying landcover in historical maps (1810+) automatically using object oriented approaches. She was supervised by Martin...
MSc: Analysis of Airborne LiDAR Data for Deriving Terrain and Surface Models
The M.Sc thesis by Raja Ram Aryal has been handed in (supervision of Dr. Hooman Latifi and Prof. Michael Hahn). The thesis focused on a comparative study on the variations of an adaptive TIN ground filtering algorithm to extract DTM from discrete LiDAR point cloud...
MSc: predicting forest understory canopy cover
The M.Sc thesis by Bastian Schumann focused on a LiDAR-based approach to combine structural metrics and forest habitat information for causal and predictive models of under-story canopy cover. The data base used consisted of a bi-temporal LiDAR dataset as well as two...
Explore species-environment interaction
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...
MSc by Asja Bernd: “Mind the Gap: A Global Analysis of Grassland Fragmentation using MODIS Land Cover Data”
The MSc thesis by Asja Bernd titled “Mind the Gap: A Global Analysis of Grassland Fragmentation using MODIS Land Cover Data” is handed in. Very interesting results on global grassland fragmentation. Read the abstract:Around the world, grassland and savannah...
MSc on deforestation in Myanmar and its drivers
The MSc by Andrea Hess “Deforestation in Myanmar – what can we say about causes?” has been handed in. It has been supervised by Peter Leimgruber (Smithsonian Conservation Biology Institute) and Martin Wegmann. Deforestation in the tropics is a global issue. Tropical...
Deployment of a multi-classifier approach to improve land cover classification accuracy
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....
Stereo photogrammetry for multi-temporal surface models based on aerial imagery
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...
Estimation of actual evapotranspiration in irrigation agricultural area of Uzbekistan using high resolution multi-frequent synthetic remote sensing data
Actual evapotranspiration (ETact) is an essential component of the water balance and its determination for large areas is difficult on regional scale and can be explored within an innovation laboratory. The use of remote sensing data to determine ETact is particularly...