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Rising complexities and uncertainties have emphasized the need to employ scenario thinking in urban design and planning. While different scenario methods have been widely used across disciplines, a comprehensive review of scenario approaches in planning literature is limited. Thus, we provide an overview of scenarios and existing scenario approaches currently in practice. We also review a scenario building process to provide a guide for developing scenarios in the context of urban design and planning. The process highlights the different steps that contribute to adaptive planning and improve decision-making.

The accessibility of suburban and rural areas presents existential challenges for resident communities. Municipality inhabitants with little access to public transport and structurally weak regions often work in distant urban agglomerations, with long commutes. Widespread monofunctional ‘dormitory’ villages and suburban areas with low building density and access to public transport, fuelling automobility dependence, are still implemented as planning concepts in Lower Saxony. The objectives of this study are to analyse the quality of public transport accessibility along the urban-rural gradient in relation to settlement types in two regions in Lower Saxony; to identify the interrelations between good accessibility by public transport and population density; to identify opportunities and challenges of urban-rural public transport accessibility. The application of the settlement classification system TOPOI – developed to analyse and define settlement patterns in urban-rural gradients – enabled us to determine the quality of public transport. Furthermore, we newly developed the ‘Public Transport Access Score’ based on parameters such as available public transport modalities, their catchment areas, operating frequencies, and connectivity and applied it to demonstrate the level of accessibility for different settlement types of similar characteristics (TOPOI). Hence, we localised how sustainable accessibility of public transport can benefit the development of the urban–rural network.

Recreational green spaces are associated with human thriving and well-being. During the ongoing COVID-19 pandemic a spotlight has been shed on the interconnection between access to these spaces, human well-being and social equity. Containment measures enacted in many cities effectively precluded people from reaching distant recreational areas during the pandemic and consequently, recreational areas close to home became particularly important. Urban density is often associated with building or population density with the assumption that if either parameter has a high value, the availability of open (green) space is low. Certain densities are associated with specific spatial qualities. Addressing challenges of sustainable development, a detailed evaluation of density is necessary to allow evidence-based arguments, planning and decision-making. In this study we develop a multi-scale analysis method for quantifying and assessing green infrastructures from settlement unit to building level to reach a differentiated view on density, arguing that density can be organized in different ways achieving very different qualities. For this purpose, we use geospatial-data analysis and in-depth neighborhood studies to compare two cities in Asia and Europe, revealing different ways of organizing density in the built environment and identifying a derivation of approaches for sustainable development in dense urban regions.

The METAPOLIS as the polycentric network of urban–rural settlement is undergoing constant transformation and urbanization processes. In particular, the associated imbalance of the shrinkage and growth of different settlement types in relative geographical proximity causes negative effects, such as urban sprawl and the divergence of urban–rural lifestyles with their related resource, land and energy consumption. Implicitly related to these developments, national and global sustainable development goals for the building sector lead to the question of how a region can be assessed without detailed research and surveys to identify critical areas with high potential for sustainable development. In this study, the TOPOI method is used. It classifies settlement units and their interconnections along the urban–rural gradient, in order to quantify and assess the land-uptake and global warming potential driven by residential developments. Applying standard planning parameters in combination with key data from a comprehensive life cycle assessment of the residential building stock, a detailed understanding of different settlement types and their associated resource and energy consumption is achieved.

Deep Learning (DL) based identification and detection of elements in urban spaces through Earth Observation (EO) datasets have been widely researched and discussed. Such studies have developed state-of-the-art methods to map urban features like building footprint or roads in detail. This study delves deeper into combining multiple such studies to identify fine-grained urban features which define streetscapes. Specifically, the research focuses on employing object detection and semantic segmentation models and other computer vision methods to identify ten streetscape features such as movement corridors, roadways, sidewalks, bike paths, on-street parking, vehicles, trees, vegetation, road markings, and buildings. The training data for identifying and classifying all the elements except road markings are collected from open sources and finetuned to fit the study’s context. The training dataset is manually created and employed to delineate road markings. Apart from the model-specific evaluation on the test-set of the data, the study creates its own test dataset from the study area to analyze these models’ performance. The outputs from these models are further integrated to develop a geospatial dataset, which is additionally utilized to generate 3D views and street cross-sections for the city. The trained models and data sources are discussed in the research and are made available for urban researchers to exploit.

With the increasing availability of mobility-related data, such as GPS-traces, Web queries and climate conditions, there is a growing demand to utilize this data to better understand and support urban mobility needs. However, data available from the individual actors, such as providers of information, navigation and transportation systems, is mostly restricted to isolated mobility modes, whereas holistic data analytics over integrated data sources is not sufficiently supported. In this paper we present our ongoing research in the context of holistic data analytics to support urban mobility applications in the Data4UrbanMobility (D4UM) project. First, we discuss challenges in urban mobility analytics and present the D4UM platform we are currently developing to facilitate holistic urban data analytics over integrated heterogeneous data sources along with the available data sources. Second, we present the MiC app - a tool we developed to complement available datasets with intermodal mobility data (i.e. data about journeys that involve more than one mode of mobility) using a citizen science approach. Finally, we present selected use cases and discuss our future work.

Das Berufsbild der Architektin und des Architekten wandelt sich: dem Allgemeinwohl und den Zielen der Nachhaltigkeit verpflichtend, kooperativ arbeitend, transformativ wirkend und fachubergreifend denkend. Um Studierende auf die Herausforderungen einer nachhaltigen Stadtentwicklung vorzubereiten, hat das Institute for Sustainable Urbanism (ISU) das praxisnahe und kooperative Lehr-Lern-Format „Projektakademie Landlicher Raum“ ins Leben gerufen. Studierende der Architektur und des Sustainable Designs kommen in einem Entwurfsstudio mit real existierenden Fragestellungen, Akteurinnen und Akteuren in niedersachsischen Dorfern und Kleinstadten in Beruhrung. Ziel ist es, Potenziale des landlichen Raums zu analysieren und Ideen fur die Zukunft jedes Ortes im Kontext seiner Region zu entwickeln. Die Projektakademie fordert ein erweitertes Verstandnis fur Stadtentwicklung sowie wichtige Kompetenzen wie inter- und transdisziplinare Teamarbeit, Partizipation und Gemeinwohlorientierung.