The landscape connectivity of the urban core and fringe is crucial for both the environment and human activities. However, urban development is causing fragmentation between urban cores and urban fringes. Landscapes are gaining importance in shaping urban form, especially in complex natural environments, post-industrial sites, and public infrastructure. Green infrastructure (GI) plays a vital role in enhancing connectivity, mobility, and urban health, counteracting the excessive growth of grey areas in cities and tackling urban sprawl. In urban fringes, unused lands hold significant potential for linking green spaces in different city zones.
This study provides a practical and replicable approach for assessing GI patterns and identifying the disparities in the continuation of greenery within urban cores. The methodology employs a mixed-methods approach, combining quantitative, qualitative, and prototyping methods. The methodology aims to bridge the gap between theoretical concepts and the practical implementation of GIs by combining data-driven analysis with design approaches. The first step in paving the way for this study is to detect changes within a specific time period at the case of interest, namely the former distillery location (Lihovar) extending northward, approximately up to the Andel district in Smichov, Prague, Czech Republic. Then, by analyzing the outcome of the change detection, it is possible to identify the disparities between GIs. Furthermore, a given web application/map will help the author of this study identify the qualitative aspects of the area, as well as citizens' knowledge about it. Finally, it is possible to deliver a bespoke design to enhance the status of green connectivity within a multi-scale area and connect it with regional green corridors. This study aims to develop a novel autonomous approach for classifying various parcels through supervised/unsupervised image classifications, which will provide more precise and high-quality clas
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