Q:

Sentinel-1A and Lansat-8 Resolution difference

Sentinel-1A level-1 high resolution GRD data have 20X22m resolution (rgXaz)with 5X1 number of looks. While Landsat-8 data have 30m resolution. My question is how can I compare the resolution differences between them? In other words, which one of them has higher resolution? When I digitize a lake size from the two sensors, lake size  from  Landsat-8 is always greater than Sentine-1A. Note that its a same lake; images were taken on the same acquisition date or with not much of time difference. What could be the reasons behind for differences in the lake sizes? Is it because of resolution difference? If yes, How can I  interpret the results?

A:

This is a bit of an apples and oranges comparison. The Sentinel-1A sensor is an active radar system carrying a  C-band synthetic aperture radar array. Whereas, Landsat 8 is a passive spectral system with 16-bit radiometric resolution across 0.43 - 2.29 micrometers (excluding the 100m2 IR bands). The characteristics of the sensors will dictate the feature resolution of the objects being detected. 
Because the Landsat 8 sensor is carrying a blue edge band (0.43 - 0.45 um), it is likely able to discriminate water/wetland features more effectively than the backscatter signal from Sentinel-1A. This would account for the differences in feature size, regardless of the on the ground cell resolution differences. If you want to use radar SAR data for water/wetland classification it would be better to use L-band data from ALOS PALSAR. This would provide much better discrimination than Sentinel-1A C-band data.
I would have to add here that you really need to consider a classification algorithm. It is impossible to visually Elucidate information contained in both of these data. There could very well be information contained in the data that is providing feature discrimination that is not readily apparent in a visual assessment. The difference in the results could be associated with user bias and not information content. This is particularity relevant in a multivariate context where there may be very relevant information, contained across multiple bands that are not being used in and RGB composite, comprising the image backdrop being used in heads up digitizing. You are effectively throwing away data. In the radar data there is likely a pixel gradient that is not apparent in your visual interpretation. The image can also be seriously compromised based on the type of stretch used in display.           

