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Mixed land-use and higher population densities are endorsed in many urban planning concepts as crucial elements for urban vitality. They are said to make urban streets active due to the presence of people, leading to public vigilance and improved feeling of safety on streets. Moreover, higher densities and mixed land-uses are also said to promote social interactions and walkability. Indian cities are inherently mix and dense, and therefore, the noted benefits in the literature need to be verified in this local context. In this research, through the empiric al study of eight study areas of Pune, India, the efficacy of social benefits of mixed land-uses and population densities is established. A mixed land-use index for the selected study areas was computed to represent the mixed land-use intensities. Satisfaction levels of the residents regarding the presumed social benefits were surveyed and collated as urban vitality. The relationship between urban vitality and mixed land-uses and population densities is established through curvilinear (quadratic) regression analysis explained by parabola shape. The results of this study reveal that mixed land-uses and higher population densities initially lead to an increase in urban vitality to an extent and then reduce again with intense mixed land-use and high population density. Population density between 12000 to 14000 persons per square kilometer is most suited to achieve urban vitality.

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Mixed land-use is a popular concept in urban planning due to its expected role in improving environmental sustainability as well as citizen’s quality of life. Land use planning and regulations are not stringent in many cities like those in India, and policies are liberal towards mixed land uses. In these cities, mixed land-uses are a natural phenomenon manifesting under various influencing parameters. However, for studies on mixed land-uses, these cities pose data insufficiency challenges, as vital comprehensive spatial information related to land-uses is not available. Moreover, there is no standardised methodology established to assess the spatial distribution of mixed land-uses at the city level. This research has developed a GIS-based model using Weighted Overlay Analysis to predict and visualise the probability of mixed land-use at the macro or city level for the case of Pune, India. The model uses the easily available spatial data of influencing parameters of mixed land-use as input for prediction instead of comprehensive real land-use data. The model is validated by comparing the predicted mixed land-use intensities with established indicators of mixed land-use for four neighbourhoods. It is found that parameters that influence mixed land-use such as connectivity, grain pattern, population density and access to amenities can be used to predict the probability of mixed land-use. Around 35 per cent of the city area of Pune has more than 0.67 probability of mixed land-use. The model can produce the probable mixed land-use distribution across the city and can be used to compute mixed land-use intensities for neighbourhoods. Highlights for public administration, management and planning: • Mixed land-use probability distribution for Pune City, India is generated using Weighted Overlay Analysis in GIS. • As vital spatial data of land-use was unavailable, the prediction model uses data of influencing parameters of mixed land-uses such as population density, connectivity, grain pattern and access to amenities. • The mixed land-use probabilities predicted can be used to compute mixed land-use intensities of neighbourhoods. It is validated by comparing with traditional mixed land-use indicators.