Old maps are more than a cultural artefact: they are data. Data about the past still hold value for science and decision‐making today. Libraries and archives have come a long way in digitising their inventories of thousands, sometimes millions, of historical maps using high‐resolution scanning. Unfortunately, even with digital images the rich spatial and semantic information is inaccessible for people without a strong background in history and cartography. Only with georeferencing can historical maps be used in GIS and thus processed and compared with modern geospatial data. We introduce content‐based image retrieval to automatically localise and georeference map images from topographic map series. We align the maps by extracting a subset of their symbols and cross‐referencing them with online reference data from OpenStreetMap. We demonstrate our method with the Karte des Deutschen Reiches at 1: 100,000 scale, obtaining 96% correct location predictions and a median georeferencing error of 101 m.

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Abstract. In recent years, libraries have made great progress in digitising troves of historical maps with high-resolution scanners. Providing user-friendly information access for cultural heritage through spatial search and webGIS requires georeferencing of the hundreds of thousands of digitised maps.Georeferencing is usually done manually by finding “ground control points”, locations in the digital map image, whose identity is unambiguous and can easily be found in modern-day reference geodata/mapping data. To decide whether two symbols from different maps describe the same object, their semantic and spatial relations need to be matched. Automating this process is the only feasible way to georeference the immense quantities of maps in conceivable time. However, automated solutions for spatial matching quickly fail when faced with incomplete data – which is the greatest challenge when comparing maps of different ages or scales.These problems can be overcome by computing map similarity in the image domain. Treating maps as a special case of image processing allows efficient and robust matching and thus identification of geographical regions without the need to explicitly model semantics. We propose a method to encode worldwide reference VGI mapping data as image features, allowing the construction of an efficient lookup index. With this index, content-based image retrieval can be used for both geolocating a given map for georeferencing with high accuracy. We demonstrate our approach on hundreds of map sheets of different historical topographical survey map series, successfully georeferencing most of them within mere seconds.

In a complex urban scenario with a growing number of stakeholders and high dynamic developments, decision makers rely heavily on public data to make informed decisions. Often though, the available data is heterogeneous and stems from incomplete or inconsistent sources. The planning process, especially the definition of planning goals/needs, is often delayed due to time-consuming data procurement and assessment. This paper describes the development of the Cockpit Social Infrastructure (CoSI), a GIS-based planning support system that serves as an easy-access interface between Hamburgs Urban Data Platform GIS data infrastructure and the municipal planners for social infrastructure, bridging the gap between disciplines and facilitating communication and decision-making between stakeholders. CoSI takes full advantage of the UDP infrastructure and aims to introduce a city-wide tool for planners to conduct holistic, evidence-based planning, grounded in the latest and regularly updated statistical data. The paper outlines the project genesis and underlying technical and administrative structures.

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, 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.