1. Atmospheric corrections

2. The atmosphere is evil Clouds Humidity Gasses Pollution/haze
Different sun angles

3. clouds Block pretty much everything in the V-MIR. Shadows.
Annoying as heck.
Only solution, radar data

4. humidity
Water absorbs. The more, the “hazier” the image. Not much you can do about it.

5. Pollution, dust, etc
Also blocks light. Also annoying. Also, not much you can do about it.

6. gasses Scatter – increases brightness Absorbtion Haze and dust Water
Raleigh Scatter, especially in blue. Decreases with increasing wavelength
MIE scatter – dust and smoke, in the red region (sunsets, etc).
Water
Nonselective scatter through whole range. Basically, white water!
Absorbtion
Water vapor and CO2. Biggest effects in the MIR.

7. Sun angle
Different angles = different shadows and different reflection.
Sensors *try* to collect as close to noon as possible to minimize these effects.

8. Radiometric corrections (or what to do about these issues)
Physical models of the atmosphere. Requires a LOT of data, often not available.
Look at reflections from known objects and compare to a library. Adjust each band according to differences from “truth”. Easy example is deep, clear water. Should have reflection of 0 in all bands.
Histogram equalization – shuffle each band such that they all have a minimum value of zero. Just basic subtraction. Simple. Statistically as good as the others….
Regression – another way of comparing reflectances and then shuffling them back to zero.

9. When to do?
Honestly, the only time it’s really worth it is if you are using data over the same area over different times and you want to compare. The histogram equalization will help minimize whatever different atmospheric conditions exist at the different times.

10. More info?
Book. Especially starting at page But there’s info scattered about.
ERDAS – raster – radiometric. Bunches of stuff.
Note – “histogram equalization” in erdas is NOT the radiometric correction noted here. It’s a contrast stretch.
The one real radiometric correction model requires additional software.

11. Sensor collection errors
Striping and line drop.

16. In erdas Again, in raster – radiometric Look at.
Note – all this stuff (and pretty much everything all quarter) are covered in your text. Be sure to look it up and read, especially while studying! The text is pretty clear.

17. Did you know?