In this article, we describe the design of a method for measuring walkability and its application in two medium-sized cities in Germany. The method modifies the established Walk Score with regard to the needs of older people. While the original Walk Score takes a 2D approach by calculating the reachability of service facilities on a flat road network, we include 3D information by taking into account slopes and stairs. We also pay attention to the longer walking times of the elderly and adjust the selection and weighting of supply facilities according to their relevance for elderly people. The implementation results in a concentric walkability pattern, with a high Walk Score in the inner-city area that is decreasing towards the periphery, but with many anomalies resulting from local inhomogeneity in population and facility distribution and topography. The study shows that it is possible to refine the Walk Score to meet the needs of older people, as well as to implement the methodology in Germany using a combination of voluntary geographic information and high-quality official datasets. We see our research as a step forward on the way to more realistic walkability metrics for senior-sensitive urban planning.

Many single-family homes built in Germany in the first decades following the Second World War are now occupied by elderly residents. If local conditions are unfavorable, a large number of these buildings may enter the real estate market in a short period of time and put pressure on the local housing market. Planners and decision-makers therefore need detailed spatiotemporal information about these neighborhoods to effectively address and counteract such developments. We present the design and implementation of a planning support system that can generate the required information. The architecture of this newly developed software consists of a composite, multitier framework to perform the complex tasks of data importation, data processing, and visualization. Legally mandated municipal population registers provide the key data for the calculation of indicators as a base for spatiotemporal analyses and visualizations. These registers offer high data quality in terms of completeness, logical consistency, spatial, and temporal and thematic accuracy. We demonstrate the implemented method using population data from a local government in a rural area in southwestern Germany. The results show that the new tool, which relies on open software components, is capable to identify and prioritize areas with particularly high levels of problem pressure. The tool can be used not only for analyses in a local context, but also at a regional level.

Walking is a sustainable, safe, and active mode of transportation. The benefits that the elderly in particular gain from outdoor walking are manifold, be it free andindependent access to stores and services of all kinds or the opportunity to socialize, enjoy parks, et cetera. This article depicts one particular factor that affects outdoor walkability,namely the gradient of walking paths. Steep slopes can be a serious obstacle to walkability, primarily for older people. The evaluation of available geospatial data sources formedthe basis for a geospatial analysis of walkability in the larger city of Kaiserslautern, located in southwest Germany. The concept of Walk Score was used to quantify the resultsobtained. The results demonstrate that the Walk Score can be refined to better address the mobility needs of older adults. The methodology was implemented for the German cityof Kaiserslautern by integrating volunteered geographic information with high-quality official datasets.

Star-based schemes, such as the 5-star Linked Open Data model and its geospatial extensions, are widely used to characterize openness and interoperability. However, in practice, higher star ratings are often assigned on the basis of technical properties such as RDF exposure or schema publication without requiring the satisfaction of foundational metadata quality conditions. This weakens the monotonic interpretation of star levels and can produce ambiguous signals for data users. To address this issue, we propose the LETTER framework, a multi-dimensional evaluation model in which seven independent binary dimensions describe metadata readiness for reuse: Provenance (P), Access (A), Structure (S), Connections (C), License (L), Identifiers (I), and Quality (Q). The framework is aligned with FAIR principles and mapped to ISO 19115 and ISO 19157 concepts. We evaluate it through an exploratory comparative case study of four purposively selected datasets from the German Spatial Data Infrastructure (GDI-DE): Municipal Points of Interest (Trier), Thuringia Digital Elevation Model (DEM), Administrative Units (VG250), and INSPIRE Digital Land Model (DLM). The results show that datasets receiving comparatively high star ratings may still lack machine-actionable provenance, quality evidence, stable identifiers, or robust access conditions. In particular, the analysis highlights a recurring ‘PDF Trap’, where relevant trust information exists only in narrative documentation and therefore remains inaccessible to automated reuse workflows. We conclude that LETTER provides clearer diagnostic power than scalar star ratings by exposing which metadata functions are actually satisfied and which remain missing.