The organization and properties of the neural receptive fields in the visual cortex is a prominent factor in understanding the mechanism of neural coding. Here, we perform a systematic and standardized analysis of the structure, organization and properties of the receptive fields in the pan-excitatory neuronal population in the mouse primary visual cortex (area V1). We collected and analyzed a large-scale 2-photon volumetric imaging dataset from an 800x800x600 μm^3 volume in V1 of two mice. The visual responses from were recorded during presentation of a locally sparse noise stimulus to efficiently reconstruct the neural receptive fields. The locally sparse noise stimulus consisted of 9 degree black or white spots on a mean luminance gray background presented at ~3Hz. We designed and implemented a computational pipeline to identify responsive trials, ON and OFF subfields and their geometric properties. Using these experimental and computational pipelines, we found that OFF subfields tended to have larger areas than ON subfields, particularly in layer 2/3. On average, OFF subfields were 15.6 degree^2 larger than the ON subfields across all imaging depths. We also found that the average receptive field area decreased as a function of cortical depth. ON and OFF subfields in layer 5 were on average 22% (ON subfields) and 31.5% (OFF subfields) smaller than those in layer 2/3. Additionally, we found that the responsiveness rate to the sparse noise decreased in deeper layers of cortex. Neurons in layer 2/3 were about 4 times more likely to respond to our visual stimulus compared to neurons in layer 5. Our results provide a systematic and standardized survey of the receptive field properties in V1. The dataset and computational pipeline could serve as a valuable resource to the community to further study the visual responses of neurons in V1.