I am a new learner of remote sensing. I am working with ERDAS Emagine 9.2. I want to know if it is important to make an atmospheric correction of an image before analysis. What procedure should I maintain to perform atmospheric correction? What are the advantages of atmospheric correction? I would like to understand its accuracy.
Well, thats a big topic. I'll start from the end:
1) You can measure the accuracy only with ground reference measurements at the time when the image was taken. But normally you can expect at least an improvement.
2) With atmospheric correction methods you correct your image from atmospheric disturbances like path radiance, scattering and sky irradiance.
3) If you have only a single image and no multitemporal aquisitions an atmospheric correction is only necessary if the image is very hazy. This is because normally all pixel values are influenced to the same degree and you can achieve good results with all standard classification methods.
4) There are different methods to correct the images. Empirical methods are Dork object substraction (Chavez 1988) or the empirical line method (for this you will need some reference data). More physically based models are so called "radiative transfer models" (Lowtran, modtran). If you are lucky your Erdas license includes also the ATCOR module with which you can apply this models.
Have a look in this paper, it gives a good overview:
SONG, C., WOODCOCK, C. E., SETO, K. C., LENNEY, M. P. & MACOMBER, S. A. (2001): Classification and Change Detection Using Landsat TM Data - When and How to Correct Atmospheric Effects? Remote Sensing of Environment, 75, S. 230-244.
I hope I could answer your question!
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