Autophagy is a major protein degradation system, which targets primarily long-lived cytoplasmic proteins. A large body of evidence indicates that impaired autophagy is implicated in the onset and progression of human pathologies such as heart disease, neuro-degeneration and cancer. Central to the functional role of autophagy is the successful fusion event of autophagosomes with lysosomes, forming and autophagolysosome. Although substantial progress has been achieved in understanding the molecular machinery of the autophagic pathway and its regulation, a fundamental challenge remains to identify the driving forces that govern the fusion event. This however requires a highly resolved detail that describes the fusion process morphologically. By utilizing superresolution structured illumination microscopy (RS-SIM) techniques, the aim of this study was to characterize the three-dimensional morphology of autophagosomes and lysosomes in single mammalian cells, and to assess the fusion region between these 2 organelles. Rodent derived cardiac myoblast H9c-2 cells were grown in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 10% foetal bovine serum (FBS), and incubated under 5% CO2 conditions. The light-chain 3 (LC3) and lysosomal associated membrane protein (LAMP) were utilized as markers for autophagosomes and lysosomes respectively. Cells were transfected with 800 ng of the LC-3-GFP-DSred tandem plasmid, GFP-LC3 as well as LAMP-YFP using GenJuice® Transfection Reagent (Novagen®) according to the manufacturer’s protocol. SR-SIM image acquisition and processing was performed on a LSM-780 Elyra system and z-stack image acquisition was utilized to capture both autophagosomes and lysosomes at high resolution in three dimensions. Surface rendering was performed to assess the fluorescence signal distribution. This study reveals a highly heterogeneous morphological distribution of both autophagosomes and lysosomes, indicating the dynamic membrane turnover process during autophagosome and lysosome formation. Moreover, a morphologically highly complex fusion zone is observed. These data indicate a previously unknown complexity of membrane morphology and dynamics of both organelles. Importantly, this study highlights the strength of SR-SIM in deriving numerical geometrical data that allow the prediction and modelling of the likelihood for a complete or incomplete fusion event to take place. This approach provides insights that may result in novel means to exploit the autophagic machinery for therapeutic purposes.