Current projects

CoGran

Combining data of different spatial granularity (CoGran)

g2lab has received funding by VolkswagenStiftung for the project on “Combining data of different spatial granularity (CoGran)” which will be conducted together with Julius Tröger (Berliner Morgenpost).
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CoGran

3D "Dive throughs" the Elbe 

Together with the newspaper WELT g2lab has developed new views of the river Elbe, showing the riverbed in a couple of 3D interactive views and videos.
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Erwärmung

GEWISS - Geographical Heat Information and Simulation System Hamburg (GEografisches WärmeInformations- und Simulations-System Hamburg)

g2lab is involved in new research project funded by the German Ministry for Economic Affairs and Energy (BMWi) which aims at the development of a Geographical Heat Information and Simulation System.
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pedestrian

Pedestrian navigation considering cognitive processes (PhD project)

Within this PhD project a navigation and information system for pedestrian orientation will be developed. The final goal of this project is to develop concepts and methods for a new graphical map structure considering the cognitive aspects and the dynamic geo data in order to represent an overlay of a mass geospatial information in items of anthropogenic objects for wayfinding in urban area.
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visualhierarchy

Enhancing visual hierarchy derived from Pedestrian Requirements for Wayfinding Combining Indoor and Outdoor Environments

This project is related to graphical structure in terms of the map for the overlay of signage information pedestrians need combining indoor and outdoor environment. A new graphical structure will be derived from the visual cognitive process and the hierarchy of signage information pedestrians need during locomotion in different locations.

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Sound Maps

Sound Maps for Encoding Quantitative Information

We aim at exploring possibilities to convey quantitative information as sound. Hence we develop prototypes to compare classical forms of presentation such as color and hachure with sound.
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Geoinformation for the Coastal Zone

Geoinformation for the Coastal Zone

Development and processing of geoinformation for coastal areas as well as implementation of spatial data infrastructures for a sustainable and integrated management of coastal zones.
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Finished projects

HEFV

Hamburg Energy Research Network (HEFV)

The Hamburg Energy Research Network HEFV was set up by the Hamburg Senate on January 1st 2013 to connect the various research efforts at the local universities and strengthen the importance of Hamburg in the energy sector. At the HCU we aim to identify two research foci in which future efforts may be concentrated.
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Noise Maps

Analysis and Improvement of the User-Friendliness of Strategic Noise Maps for Public Participation (PhD project)

We aim at improving the user-friendliness of strategic noise maps and conducted qualitative, quantitative and requirements analyses to evaluate aspects to be improved.
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ic|change

Uncertainty in Geovisual Analytics of Land Cover Change Processes (PhD project)

This project is concerned with the role of uncertainty during analyses using Geovisual Analytics. Is uncertainty information beneficial when it is visually communicated to the user during the analysis? Can users get better insights with the use of uncertainty information?
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Colorvision

Adjustment of Map Colors for Users With Color Vision Deficiencies

Our research aims at the improvement of color schemes to make them accessible to users with color vision deficiencies.
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KLIWAS

KLIWAS: Climate - Water - Navigation

Modeling and visualization of uncertainties in estuary vegetation monitoring based on multi- and hyperspectral remotely sensed data.
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Evaluation and Optimization of Noise Action Plans

OptiLAP - Evaluation and Optimization of Noise Action Plans

Analysis of the visualization of noise used for public participation and suggestions for the design of target group oriented noise maps.
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Classification Assessment Using an Integrated Method

CLAIM - Classification Assessment Using an Integrated Method (funded by DFG)

Modeling of uncertainty introduced by classification of remote sensing data (fuzzy model). Development of advanced quality assessment measures based on the uncertainty model.
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