Current projects

SLM

Sea Level Map

g2lab has develop a web-based visualization of sea level rise simulations for Northern Germany. 
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PaKOMM

Partizipation: Kollaborativ und Multimedial (PaKOMM)

g2lab leads this project which concerned with the comination of various visualization formats for public participation processes, including Augmented and Virtual Reality applications. Project partners are the City Science Lab (HCU) and the FTZ Digital Reality (HAW). Funding is provided by the City of Hamburg.
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unGESUND

Modelling and simulation of accessibility of medical facilities (unGESUND)

g2lab works on modeling and simulating accessibility of medical facilities.  Project partners are the Universitätklinikum Eppendorf (UKE), Hochschule für Angewandte Wissenschaften (HAW) and collegues from HCU. 
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0 CO2

0 CO2 Speicherstadt

g2lab is working on the development of usable Building Information Models (BIM) in the context of a CO2 neutral operation of historical building in the Hamburg Speicherstadt. 
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Current Ph.D. projects

PhD Güren

Object Based Change Detection using Machine Learning and Multi-source data (Güren Tan Dinga)

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PhD Martin

Deep Learning methods for cartographic generalization based on geographical vector data (Martin Knura)

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PhD Patrick

Optimised Utilisation of Geospatial Data in Extended Reality Environments (Patrick Postert)

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Copyright OpenStreetMap contributors, Staatsbibliothek Berlin

Automated Georeferencing of historical maps (Jonas Luft)

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Finished projects

TOVIP

Improvement of task-oriented visual interpretation of VGI point data (TOVIP)

g2lab has received funding by the German Research Foundation (DFG) for a project on improving the visualization of point data derived from Volunteered Geographic Information (VGI). The project is embedded into the Priority Program "Volunteered Geographic Information: Visualization - Interpretation - Social Computing"
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FAIR

Flexible and demand-oriented provision, processing, and integration of climate and weather data for seamless business processes (FAIR)

g2lab has received funding by the German Federal Ministry of Transport and Digital Infrastructure (BMVI) for a project within the mFUND-program for the development of services related to open weather data.
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Historic Maps

Development of a Semiological Methodology on the Comparability of Current with Historical Geodata (Inga Schlegel)

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aChor

Task-oriented data classification for choropleth maps (aChor)

g2lab has received funding by the German Research Foundation (DFG) for a project on improving the task-oriented generation of choropleth maps. The idea is to preserve spatial patterns like extreme values or hot spots after the classification step.
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UeGeo

Overlay of Geodata (UeGeo)

g2lab has received funding by the German Federal Ministry of Transport and Digital Infrastructure (BMVI) for a project within the mFUND-program that enables the overlay of geodata with different reference geometries.
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UeGeo

Better decisions based on uncertain data (BEMUDA)

g2lab has received funding by the German Federal Ministry of Transport and Digital Infrastructure (BMVI) for a project within the mFUND-program that develops a concept and software tool for handling uncertain data in typical sptio-temporal processes. 
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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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WELT

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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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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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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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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