In this work we develop four new visualizations for identifying urban typologies and then type specific urban transition pathways. A) Network of similarities: This is a network map of how cities are similar to each other based on categorization along 26 different social, economic, scale and natural parameters. Each link is a similarity in type along one parameter and cities are grouped based on network modularity or strength of linkages. B) Footprint reduction trends map: Performance strain is defined as the slope of change in GHG emissions normalized to base year emissions. The colors show strain, the size of the bubble shows total base emissions. C) City actions profiles: Each city reports anywhere from one to tens of actions they are taking towards footprint reduction. These actions are then categorized along four parameters. The actions profile diagram for each city shows results for six of these parameters. D) Transition pathway for given city type: Based on what ?action profiles? appear to perform better at reducing emissions, first, second and third priority action recommendations for each city type constitute the ?transition pathway?. This will be used as a first input in a co-production process with city partners and shall be further refined through direct city engagement. We use data from Carbonn, the largest depository of self-reported, voluntary commitments, inventories and actions. Following is the analysis sequence. 1) Key parameters for classifying cities are identified based on expert and practitioner input. 2) Using the database of inventories the performance is estimated for cities. 3) Using the database of actions cities are taking the ?actions profile? of a city is developed. 4) A decision tree is developed to help cities self-identify their categories. 5) For each city type, based on which ?action profiles? result in best performance a ?transition pathway? is recommended with first, second and third priority action types as well as dependencies.