Image rectification's main usefulness is being able to use multiple images from different sources to produce one comprehensive output. The main pitfall is human intervention! As we know, automation can produce pinpoint accuracies but the data is dependent on human input to identify and locate suitable control points. Like digitizing, the human factor diminishes the reliability of the data. Of course, the image may not help as it may be difficult to identify accurate points - we all assume there will be nice road intersections and giant 'X marks the spot' runways to set as control, but what if the image is in the wilderness or contains hundreds of water features? Also, unless the image has been corrected beforehand to account for distortions such as terrain, this may account for some further error in accuracy. The future looks bright though: increasingly higher spatial resolution data is being acquired that should ease the rectification process.
Subscribe to:
Post Comments (Atom)
No comments:
Post a Comment