Abstract: Flood disasters pose a significant threat to urban economic development and the safety of residents’ life and properties. Quantifying the resilience index of urban flood disasters can accelerate the construction of resilient cities and provide strong support for the high-quality development of cities. This study took Nanchang city in Jiangxi province as an example. The study area was discretized into 100m x 100m grid units. Multi-source data were used to construct an urban flood disaster resilience evaluation index system, based on PSR model, from four dimensions: nature, economy, society, and infrastructure. The AHP-entropy weight method was employed to explore the spatial distribution of flood disaster resilience at the pixel scale. Additionally, the main driving factors were identified using the geographical detector. The results revealed that the areas of extremely low and low levels of flood disaster resilience accounted for 5.9% and 5.7% of the total area, respectively. These areas were primarily located in Xihu District, Qingyunpu District, and Qingshan Lake District of Nanchang city. The primary contributing factors were identified as the large proportion of impervious surfaces and low vegetation coverage. The geographical detector analysis indicated that the main driving factors of flood disaster resilience in Nanchang City were the proportion of impervious surfaces, terrain humidity index, and the density of buildings. These findings provided a valuable basis for decision making regarding effective responses to prevent and reduce urban flood disasters.