The scientific evaluation and optimization of neighborhood walkability play a pivotal role in enhancing urban vitality and fostering green development. A model was initially constructed for evaluating urban neighborhoods walkability, which encompassed five dimensions and eighteen indicators based on Maslow's demand theory and Kano model. Subsequently, a combination of multi-source data and the improved CRITIC-entropy method was employed to assess the neighborhood walkability of Hefei City. Then the hotspot analysis was conducted to identify the spatial clusters of high and low values in each dimension, and the reasons for the creation of these clusters were analyzed. Finally, the concept of neighborhood vitality was introduced to explore the spatial matching relationship between the walkability and vitality using the bivariate Moran's index, and the methods for optimizing walkability were proposed. The results indicate that walkability can be evaluated based on Maslow's demand theory and Kano model from five dimensions: accessibility, convenience, safety, richness and comfortableness. What is more, significant spatial heterogeneity and autocorrelation of walkability are observed within the study area, along with disparities between walkability and neighborhood vitality. Building upon these findings, an optimization strategy of neighborhood walkability is proposed, which can provide a reference for the future design and renovation of walking space in Hefei City.