Knowledge about the heat demand (MWh/area/year) of a respective building, district, city, state, country or even on a continental scale is crucial for an adequate heat demand planning or planning for ...

Abstract: State-of-the-art open graph visualization tools like Gephi, KeyLines, and Cytoscape are not suitable for studying street networks with thousands of roads since they do not support ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

Background: There is interest in the use geospatial data for development of acute stroke services given the importance of timely access to acute reperfusion therapy. This paper aims to introduce ...

Maps of our cities have been around since the 15th century, but today's merge technology and art like never before One of the challenges facing urban scholars and planners is that their ‘lab’ is the ...