Coupling coordination degree of spatial variation between fuzzy logic integrated level of development and Public Utility and Service Facilities (PUSFs) in Urban Delhi

The public utility and service facilities (PUSFs) provide all the basic and necessary services that are used in daily life by households and industries. Adequate distribution of PUSFs determines all functional activities associated with public services like healthcare, education, police, and postal services, etc. is essential for a good standard of living in every society. The demand for PUSFs rises with rapid population growth especially in urban areas, and the adequate distribution of necessary public utility and services with quantity and quality is of paramount importance to the government and urban planners. Therefore, the present study intended to investigate the coordination between the spatial disparity of PUSFs and the fuzzy logic integrated level of development model. The geographical concentration and inadequacies of PUSFs in CEUs were analyzed using the Location of Quotient (LQ) and Gini Coefficient in this research. The Lorenz curve was used to investigate the disparity in PUSFs distribution. The LQ was combined with spatial clustering using the getis-ord approach to highlight the spatial disparity of PUSFs quantitatively. We also built the level of development model using fuzzy logic. The coupling coordination degree model was also utilized to investigate the degree of coordination between the two systems. The sensitivity of the model was investigated using a machine learning approach called random forest. The results show that some CEUs in terms of PUSFs are more developed like Kalkaji, and Defence Colony. In contrast, others are average developed like Preet Vihar, and Vasant Vihar-NDMC, and the rest are less developed like Najafgarh, and Saraswati Vihar. This uneven distribution among PUSFs in Urban Delhi shows that there is an imbalance in the planning and development of CEUs with respect to PUSFs. The present study would aid urban planners and policy makers in distributing PUSFs more evenly and realizing the smart city vision of the Indian government.

Keywords: Public Utility and Service Facilities, Coupling Coordination Degree Model, Lorenz Curve, Fuzzy Logic, Random Forest, Level of Development