I took a closer look at the entire image source — and concluded that it’s indeed a fused or pan-sharpened product. This is confirmed by moving objects being ‘ahead’ of the multi-spectral source objects, and those objects remaining ‘blurred’ from the resample to high-resolution.

There’s a number of key areas to look within the imagery, that demonstrate analytical consistency. The highways and bridge (I-35) are obvious indicators, due to constant flow of traffic in either direction. The train crossing the rail-bridge is also another consistent source due to linear travel direction. You can pick-out and match some of the vehicle movements within the lower-speed urban roadways, and occassionally even match a ‘ghost vehicle’ that has turned vs. its multi-spectral location on an adjacent roadway.

If we actually knew the exact time-lapse between the sensor capture, both multi-spectral and pan — we would be able to gain a rough estimate chart on speed variations for each vehicle travelling those distances.

So what we’re seeing, is that yes — it’s the exact same collect time — but the pan imagery was collected a number of miliseconds after the multi-spectral was captured. That would also give anyone with a trained eye an indicator as to who collected it and what sensor system was used.

This is actually an interesting anomoly to see, especially in aerial. We don’t typically see this kind of sensor and process taking place except with satellite sensors.

Now, I can’t wait for the various arm-chair security non-experts to wage opinions on the weirdness of the ‘ghost’ object anomolies within the press. Seems we have too much of that happening these days, mainly in relation to security.

If you look at the vehicles — you’ll notice that the semi-tractor/trailer and a couple of the cars are ‘blurry’ compared to the ‘ghosts’. But, those vehicles are aligned in the same lanes at visually the same distance (depending on which way traffic is moving, considering opposite lanes). This would indicate to me what I mention above.