Removing ocular artifacts from EEG signals I have read the following paper , which is try to remove EOG artifacts from EEG signal , the authors give the following figure .


The authors claim that components 1 and 2  represent electro-oculographic (EOG) artifacts. This is because its scalp map refers to locations very near to eye. My first question is how we map an ICA component to a certain location on scalp map. Secondly, how do we know a component lies on the front of the head, and not on another location, for example the center?
In short: we know that eye-blinks are reflected frontally in the EEG data and we use that knowledge to identify which components reflect for example eye-blinks. It would not make sense to identify a component related to eye-blinks on the back of the head - there would be something wrong with your data. 

What ICA does is (data driven) estimate a number of statistically independent components (if you have 64 channels you get 64 components) based on your data. The input data is usually in the form of channels X timepoints X trials. 

Eventually the output of ICA gives you, for each component, a weight for each channel which you can use to create the component scalp map. Together, the component scalp maps, the time course of the components, and frequency information of the component provide supplementary information that you can use to identify artifacts such as (but not limited to) eye-blinks, horizontal eye movements and heart beat.

In the above figure component 14 and 15 do not seem to be eye artifacts. (1) they are very focal, which is probably related to noise specific to that channel. (2) They look to be completely uncorrelated with the eye blinks in the original signal.