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The relation of time to space is ever changing. Innovations in transportation technologies such as High-Speed Rail (HSR) instantiate abrupt alterations on this relation. Within confined space constructs, the advent of HSR can cause distortions in the overall system of relational proximities. Usually, a HSR network is extended gradually with partial links that renders it a difficult task to meaningfully visualise the overall change in the time-space fabric. Therefore, better understanding of methods to operationalise the visualisation of effects of new transportation infrastructure on the timespace dimension is needed. This paper seeks to examine these methods through their strengths and weaknesses using the undertaken and planned German HSR network expansion from 1990 to 2030. The methods employed are choropleth, anamorphosis, spring and shriveling maps. Choropleth maps are the most widespread cartographic maps on a 2- dimensional scale visualising data often on administrative spatial units such as countries etc., using colours for differentiation. Anamorphic maps (cartograms) are maps that represent the geographic shape of areas adjusted for the size of a variable of interest per area. The administrative boundaries of areas are thus warped, stretched or shrunk. Spring maps, invented by Plassard and Routhier (1987) as well as Tobler (1997), show transport networks with fixed locations as nodes and edges (connections between nodes) in the form of springs that are the more sinuous the longer the (traveltime) distance is. Developments of the model have been made by Buchin et al. (2014). Shriveling maps, conceptualised by Mathis (1990) and implemented by L'Hostis (1996, 2009), also keep locations fixed at their geographical position and draw connections with length proportional to travel time by using the third dimension. We focus on the assessment and comparison of these four methods by exposing their advantages and drawbacks along the four properties of geographical time-space as identified by L'Hostis and Abdou (2021): 1) The acceleration causing the shrinking of geographical timespace with the introduction of faster transportation means over historical time. 2) The use of transportation networks to perform movements in geographical space. 3) The co-existence of transport modes characterised by different speeds. 4) The spatial inversion Tobler (1961) and Bunge (1962), caused by extreme forms of detour, where a journey starts in a direction opposite to the end destination; this phenomenon happens at all geographical scales, with for instance expressways, rail transport and aerial transport. [ABSTRACT FROM AUTHOR]

The monitoring of land cover and land use change is critical for assessing the provision of ecosystem services. One of the sources for long-term land cover change quantification is through the classification of historical and/or current maps. Little research has been done on historical maps using Object-Based Image Analysis (OBIA). This study applied an object-based classification using eCognition tool for analyzing the land cover based on historical maps in the Main river catchment, Upper Franconia, Germany. This allowed land use change analysis between the 1850s and 2015, a time span which covers the phase of industrialization of landscapes in central Europe. The results show a strong increase in urban area by 2600%, a severe loss of cropland (−24%), a moderate reduction in meadows (−4%), and a small gain in forests (+4%). The method proved useful for the application on historical maps due to the ability of the software to create semantic objects. The confusion matrix shows an overall accuracy of 82% for the automatic classification compared to manual reclassification considering all 17 sample tiles. The minimum overall accuracy was 65% for historical maps of poor quality and the maximum was 91% for very high-quality ones. Although accuracy is between high and moderate, coarse land cover patterns in the past and trends in land cover change can be analyzed. We conclude that such long-term analysis of land cover is a prerequisite for quantifying long-term changes in ecosystem services. [ABSTRACT FROM AUTHOR]