Tell Us About Yourself:
Greetings! My name is Jan Paul Miene – I enjoy working with GIS and geodata. Since my last appearance in the GeoHipster Calendar, I have completed my Master’s degree in Geodata Technology at the Technical University of Würzburg-Schweinfurt in Germany.
I am now Head of the Digital Base Map Division for the City of Leipzig, responsible for developing, maintaining and coordinating the city’s official base map and related geospatial data.
My work and interests lie at the intersection of GIS, spatial analysis, and cartography. I enjoy working with complex spatial datasets, identifying patterns and translating them into maps that are analytically robust and visually engaging. Spatial thinking and data-driven analysis are central to my approach to geospatial problems.
Tell us the story behind your map:
This map is part of my Master’s thesis and builds on a question that has been on my mind for quite some time: while accessibility is a well-established topic in spatial analysis, what does the opposite look like? In other words, where can we find places that are not defined by how well they are connected, but by their isolation?
This idea developed from my interest in combining different spatial dimensions into a single analytical framework. Rather than focusing on a single indicator, I wanted to explore how infrastructure, mobility networks and environmental context shape a sense of remoteness together. What started as a GIS-based methodological exercise quickly turned into a more conceptual exploration. Defining ‘remoteness’ proved to be not just about distance, but also about the interaction of multiple factors, such as transport connectivity, terrain and the surrounding spatial structure.
One of the key findings was that remoteness is highly relative and scale-dependent. While some areas that appear isolated at first glance are well integrated into transport or settlement networks, other locations feel significantly more detached despite not being far away in absolute terms. In my conceptual framework, I distinguish between positive and negative forms of remoteness: areas perceived as remote due to natural or structural conditions and areas where isolation is the result of limited accessibility or infrastructure. This distinction forms part of the underlying research approach, even if it is not explicitly visualised in this particular map. The most interesting aspect of the project for me was discovering how GIS could be used not only to measure spatial relationships, but also to question and reinterpret them. The map is therefore an analytical output and an attempt to make a more abstract spatial concept visually tangible.
Tell is about the Tools, data, etc., that you used to make the map
The map was created using ArcGIS Pro, which I used for data processing, spatial analysis and cartographic design.
The analysis is based on multiple geospatial datasets that describe different aspects of accessibility and infrastructure in Germany. These include road and railway networks, public transport accessibility, and additional spatial layers representing settlement structure and environmental context. These datasets were combined to capture the various factors that contribute to perceived remoteness. To make the different variables comparable, standard GIS-based preprocessing steps were applied, such as distance calculations, rasterisation, and normalisation. The individual indicators were then weighted and integrated using the Analytic Hierarchy Process (AHP), enabling a structured and transparent derivation of a composite remoteness index. The final map is the result of this multi-layer spatial analysis, focusing on clearly communicating complex spatial relationships in a visually accessible way.