Mathias Gröbe

In preparation for a new Alpine Club map by the Institute of Cartography of the TU Dresden around Mt. Ushba in Georgia in the Great Caucasus, the decision was made to use OpenStreetMap as the primary data source for the map. As a result, the fieldwork in place contributed to OpenStreetMap to use gained information for map production by using OpenStreetMap. In the past, data import and organized mapping had already happened, leaving gaps only fillable by fieldwork. Mapping campaigns took place in 2021 and 2022. In preparation, it was necessary to identify missing or uncertain information. The catalogue of objects which should be mapped was derived from existing Alpine Club maps and the feature tags of OpenStreetMap. Several trails currently missing in OpenStreetMap were identified by collecting and comparing openly available GPS tracks, hiking guides, and old maps. The comprehensive information collection summarized the knowledge of all the sources. It became central for planning the office work on the data and organizing the extensive on-site mapping. Based on the collected information, the routes were planned in advance and during the fieldwork assigned to the mapping teams. On tour, new data was collected, which could not be obtained from aerial images such as small paths, hiking routes, guideposts, and POIs. The collection of geographical names worked similar to the collection of missing paths. After reviewing and selecting various sources, an updated set of names has been compiled. Old maps play an important role because they sometimes contain names that need to be added or allow updates for more recent documents. Combined with background literature on the region, uncertainties in assigning geographical features can frequently be solved. Asking locals helped in finding the ideal spelling. The result is a much more consistent toponym base both in the OpenStreetMap database and in the derived produced map. The presentation will share the knowledge on preparing and organizing the fieldwork for such a project. Significant aspects are how to identify missing ways and to collect geographic names.

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MapComonents is an open-source framework extending React for mapping applications. It can be used to develop browser-based applications that do not require any backend, as well as web clients that use an arbitrary number of backend services. MapComponents uses MapLibre for rendering, raster, and vector tiles. It provides working defaults wherever possible enabling the usage with minimal parameters. At the same time, it exposes the entire MapLibre API allowing very granular control of the result where it is needed. Solutions for more complex and common requirements such as PDF export, a feature editor, layer tree, WMS loader, measure tools, or bookmarks are provided as ready-to-use and highly configurable drop-in components. Exotic requirements include the swipe tool, the magnifying glass that partially shows two synchronized MapLibre instances or components that render 3D meshes or deck.gl. Layers on the map are covered by several components and example codes in our lab repository. It can be combined with a backend for managing a more extensive data set. In addition, it also works as a progressive web app offline with most functions. Creating dashboards and complex user interfaces that combine maps and diagrams MapComponents is more straightforward than traditional approaches, given the declarative nature of React and its vast ecosystem of existing components. The presentation will show and explain an actual example and its function. MapComponents framework is available under the MIT license and developed by WhereGroup GmbH.

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Generalization is a crucial topic in the map production process, describing the derivation of a map of a smaller scale from another one. It combines maintaining essential features and removing less important ones to offer a readable map. Often, this complex topic is reduced to a selection of attributes, creating label geometries, and simplifying line and area geometries. The presentation shares the knowledge of the cartographer's toolkit by introducing the whole set of available generalization operators and showing less-known approaches for creating better maps. The entire collection of operators consists of simplification, smoothing, aggregation, amalgamation, collapse, merging, refinement, exaggeration, enhancement, and displacement, which can be implemented by algorithms. The goal is to go behind the standards of creating centroids for labelling and using a Douglas-Peucker Algorithm for line simplification. A showcase of polygon simplification and creating label geometries are shown, demonstrating how to implement the operators using PostGIS with OpenStreetMap data. Several existing and working solutions for simplifying geometries and labels are presented to showcase possibilities.

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Eine praktische Anleitung zur Umsetzung von anspruchsvollen Reliefdarstellung mit QGIS und Erweiterungen.

Eine Schummerung ist schnell im QGIS berechnet – aber ist das wirklich schon eine gute Geländedarstellung? Der Workshop soll aufzeigen, was nötig und möglich ist, um gute Visualisierungen zu erzeugen. Anhand von anschaulichen Beispielen soll auf die verschiedenen Möglichkeiten, Problemstellungen sowie Lösungen in Abhängigkeit vom Zielmaßstab eingegangen werden.

Ideen für eine bessere Geländevisualisierung mit aktuellen Methoden und altbekanntem Wissen: Ein Überblick über Potential, Fehlerquellen und Möglichkeiten.

Wie man Gelände in Karten visualisiert, ist bekannt; Höhenschichten, Höhenlinien und Schummerung sind längst im digitalen GIS-Zeitalter angekommen. In Kombination mit freier Software und freien Geländemodellen kann sich jeder selbst daran versuchen. Das damit verbundene Potential birgt aber genauso auch Risiken: Falsche Verwendung von Werkzeugen und Methoden sowie wenig ästhetische Ergebnisse. Der Vortrag soll einen Überblick gegeben, wie es besser gehen kann: Geländemodelle für die verschiedenen Visualisierungsmethoden aufbereiten, aktuelle Erkenntnisse von Studien anwenden und eher unbekanntes Fachwissen einem breiten Publikum zugänglich machen. Es werden Lösungen vorgestellt, wie sich mit wenig Aufwand mittels freier Werkzeuge und bekannter Methoden bessere kartografische Visualisierungen erzeugen lassen.