About the lab
Digital City Science at HCU explores urban complexity with digital technologies. Our team develops scientific new approaches for the analysis and integrative planning of urban systems. For this purpose, the team comprises expertise in architectural design, urban and spatial planning, media technology, IT, and software development, among others. In cooperation with partners from academia, business, administration, and civil society, we develop data-based tools and methodologies that are applied in the national and international context. Our scientific activities span from fundamental research across applied projects to knowledge transfer in scientific teaching and training.
Featured research (5)
Pedestrian activity is a cornerstone for urban sustainability, with key implications for the environment, public health, social cohesion, and the local economy. Therefore, city planners, urban designers, and decision-makers require tools to predict pedestrian mobility and assess the walkability of existing or planned urban environments. For this purpose, diverse approaches have been used to analyze different inputs such as the street network configuration, density, land use mix, and the location of certain amenities. This paper focuses on the location of urban amenities as key elements for pedestrian flow prediction, and, therefore, for the success of public spaces in terms of the social life of city neighborhoods. Using agent-based modeling (ABM) and land use floor space data, this study builds a pedestrian flow model, which is applied to both existing and planned areas in the inner city of Hamburg, Germany. The pedestrian flows predicted in the planned area inform the ongoing design and planning process. The flows simulated in the existing area are compared against real-world pedestrian activity data for external validation to report the model accuracy. The results show that pedestrian flow intensity correlates to the density and diversity of amenities, among other KPIs. These correlations validate our approach and also quantify it with measurable indicators.
This paper presents a digital online tool and interaction process that supplies algorithmic analysis and predictive simulation for early-stage urban design proposals within the framework of public competitions. Specifically, the system supports the decision-making of two user groups: 1) planners in the process of developing urban designs proposals and 2) competition juries in evaluating those proposals. The system provides instant assessment of the design solutions' environmental and spatial impact regarding selected target criteria such as noise propagation or pedestrian accessibility. Enabling the easy testing of functional programs and the identification of feasible trade-offs between multiple design targets, the system supports rapid design iterations as well as the objective evaluation of proposals. Applied for the first time within an innovative tender format for a new residential and business district in Hamburg, Germany, the new toolset paves the way towards a more holistic and interactive form of sustainable urban design.
The research presented in this paper describes an evaluation of the impact of spatial interventions in public spaces, measured by social media data. This contribution aims at observing the way a spatial intervention in an urban location can affect what people talk about on social media. The test site for our research is Domplatz in the center of Hamburg, Germany. In recent years, several actions have taken place there, intending to attract social activity and spotlight the square as a landmark of cultural discourse in the city of Hamburg. To evaluate the impact of this strategy, textual data from the social networks Twitter and Instagram (i.e., tweets and image captions) are collected and analyzed using Natural Language Processing intelligence. These analyses identify and track the cultural topic or “people talking about culture” in the city of Hamburg. We observe the evolution of the cultural topic, and its potential correspondence in levels of activity, with certain intervention actions carried out in Domplatz. Two analytic methods of topic clustering and tracking are tested. The results show a successful topic identification and tracking with both methods, the second one being more accurate. This means that it is possible to isolate and observe the evolution of the city’s cultural discourse using NLP. However, it is shown that the effects of spatial interventions in our small test square have a limited local scale, rather than a city-wide relevance.
A combination of Telecom tracking data, Instagram posts, and a summary of data extracted from person-counting sensors and vehicle parking records were utilized to simulate and evaluate scenarios transferring cruise passengers from Hamburg Central Station to several cruise terminals.
Harbors are complex sociotechnical systems in which several agents are involved. The Port City Model (PCM) is a project that investigates multimodal land transportation related to cruise tourism, focusing on comfort and efficiency from the user perspective. To do so, it combines data analysis and visualization with simulation of future scenarios. The outcome is a software tool running on an interactive hardware platform that simplifies decision-making and facilitates dialogue among the stakeholders involved in the optimization of cruise passenger routes planning. This paper offers a description of the project with special focus on Agent-Based simulations to model flows and routes linking the Hamburg Central Station to different Cruise Terminals.