In phase 1, different settlement types are analysed in their multidimensional context and visualised in a 3D regional geomodel. This process forms the spatial research framework for all other research packages and can later be developed into an AI-driven urban dynamic system model (UDSM). For this purpose, urban network areas and the links between them are first determined, from which the study area is defined. Subsequently, the Urban Climate Knowledge Graph (UCKG) developed in the KNOW work package can be linked to the UDSM, thus enabling a spatial model that takes all results into account.

Based on the previous work and data from Phase 1, scenario planning techniques are now further developed and refined. This will then be applied in collaboration with experts within and outside the consortium to link this knowledge with local knowledge. The process of URB is to quantitatively assess the impacts from the scenarios through refined planning support systems (PSS) and link to UDSM to identify potential trade-offs and synergies to develop strategies for the settlement types. The aim is to support the implementation of climate change mitigation and adaptation strategies.

Increasing complexity and uncertainties in urban and regional planning lead to a need to develop precise scenarios. 
In 2022, Carlow and others developed a novel method for mapping and classifying territorial settlements and spatial formations that enables a fine-grained analysis of these places. To this end, settlement patterns in relation to mobility, the consumption of building resources, energy and the distribution of open spaces were examined and scenario planning methods were applied to identify critical influencing factors and understand future urbanisation patterns.

●Chen, H.-H., Mumm, O., & Carlow, V. (2023). A computational approach for categorizing street segments in
urban street networks based on topological properties. Front. Built Environ. Sec. Urban Science 9(2023).
https://doi.org/10.3389/fbuil.2023.1216888

●Abou Jaoude, G.; Murad, M.; Mumm, O.; Carlow, V.; Operationalizing the Open City: A case study in Berlin.
Env Plan B Urban Anal City Sci, 2023. https://doi.org/10.1177/23998083231196016

●Verma D.; Mumm O.; Carlow V.; Generating citywide street cross-sections using Aerial LiDAR and detailed
street plan, Sustainable Cities and Society, 104673, 2023. https://doi.org/10.1016/j.scs.2023.104673

●Abou Jaoude, G.; Mumm, O.; Karch, A.; Carlow, V.; Understanding land take in small and medium-sized
cities through scenarios of shrinkage and growth using autoregressive models. Front. Built Env., 8, 2023.
https://doi.org/10.3389/fbuil.2022.908698

●Abou Jaoude G.; Mumm O.; Carlow V.; An Overview of Scenario Approaches: A Guide for Urban Design
and Planning", J. Plan. Lit, 37(3), pp. 467-487, 2022. https://doi.org/10.1177/08854122221083546

●Carlow V.; Mumm O.; Neumann D.: Schneider A.K.; Schröder B.; Sedrez M.; Zeringue R.; "TOPOI –
Method for analysing settlement units and their linkages in an urban–rural fabric", Env Plan B Urban Anal
City Sci, 49(6), pp. 1663-1681, 2022. https://doi.org/10.1177/23998083211043882

●Zhu, P.; Mumm, O.; Zeringue, R.; Endres, E.; Carlow, V.; Building-related resource use in Chinese eastern
cities – Qingdao building stock as a case study. Applied Energy, 313, p. 118697, 2022. https://doi.org/10.1016/j.apenergy.2022.118697

●Verma D.; Mumm O.; Carlow V.; Identifying Streetscape Features Using VHR Imagery and Deep Learning
Applications Remote Sensing, 13(17):3363, 2021. https://doi.org/10.3390/rs13173363

●Tempelmeier N.; Rietz Y.; Lishchuk I.; Kruegel T.; Mumm O.; Carlow V.; Dietze S.; Demidova E.; Data4UrbanMobility:
Towards Holistic Data Analytics for Mobility Applications in Urban Regions, WWW2019, 2019.
https://doi.org/10.1145/3308560.3317055

●Gerike, R., Carlow, V., Görner, H., Hantschel, S., Koszowski, C., Medicus, M., & Krieg, M. (2023). Vibrant
streets: characteristics, success factors and contributions to sustainable development. nbn-resolving.
https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-872011

●Carlow V.; Gräser Y.; Hagedorn A.; Löhdefink M.; Mumm O.; Move in the City – Ansätze datengetriebener
Analyse von Stadträumen und die Umkehr des Assistenz-Gedankens in partizipativer Stadtentwicklung,
(Move in the City - Approaches to data-driven analytics of urban spaces and inversion of the assistance
concept in participatory urban development.) in Assistive Technologien im Sozial- und Gesundheitssektor,
E.W. Luthe, S.V. Müller, I. Schiering, Eds. Wiesbaden: Springer VS, 2022. https://doi.org/10.1007/978-3-658-34027-8_33

●Abou Jaoude G.; Appelhans N.; Carlow V.; Mumm O.; Murad M.; Schröder B.; Trapp J.H.; An Interdisciplinary
Approach to Understanding the Open City, Trialog, vol. 136, pp. 41-46, 2020. https://doi.org/10.24355/dbbs.084-202109061403-0