Diabetic eye disease (DED) is a leading cause of vision impairment worldwide, yet the molecular mechanisms underlying its progression remain incompletely understood. In this study, we applied a dual-platform spatial metabolomics strategy integrating air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) and matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) to characterize spatial metabolic alterations in the eyes of diabetic rats. Data-driven segmentation of retinal micro-regions using SCiLS Lab software enabled fine-scale mapping of metabolic heterogeneity. Physiological, biochemical, and histopathological analyses were combined with spatial metabolite mapping to construct a metabolic atlas and evaluate the regulatory effects of ferulic acid. We established a comprehensive spatial metabolome atlas of the rat eye, identifying 135 annotated metabolites and revealing significant region-specific metabolic heterogeneity. Unsupervised k-means clustering was further applied to the high-resolution MALDI-MSI data, successfully delineating distinct functional micro-regions of the retina solely based on endogenous metabolic profiles, demonstrating the power of data-driven tissue segmentation. In diabetic eyes, 39 metabolites were significantly dysregulated, involving amino acid, glucose, lipid, and redox metabolism. Notably, lysine, arginine, carnitine, and GSH were depleted, while glucose-6-phosphate (G6P), glycerol-3-phosphate (G3P), and pro-inflammatory lipids were elevated, highlighting profound metabolic reprogramming across ocular compartments. Ferulic acid treatment restored nine key metabolites, alleviated oxidative stress, normalized lipid and glucose metabolism, and improved retinal structural integrity in a dose-dependent manner. This study shows that integrating mass spectrometry imaging with data-driven tissue segmentation reveals spatial metabolic reprogramming in DED and highlights ferulic acid as a promising therapeutic candidate.