1. Remote Sensing Part 2 Atmospheric Interactions & Pre-processing

2. Review : Color Theory red+green=yellow green+blue=cyan red+blue=magenta red(255) + green (255) + blue (255) = white red(0) + green (95) + blue (0) = dark green red(255) + green (0) + blue (255) = purple red(0) + green (255) + blue (255) = cyan red(170) + green (170) + blue (170) = gray red(0) + green (0) + blue (0) = black

3. Review: Imagery / Raster Data Model 10 30 25 5 30 10 30 1.Space is covered continuously with cells 2.Each cell has one number PER SPECTRAL BAND indicating the amount of energy received from the cell 3.The cell is called pixel (picture element) 4.The size of the pixel is the spatial resolution sensor

4. Review: Spatial Resolution & Image Footprint 185 km swath 175km scene Landsat Satellite ground track 705km Spatial Resolution Pixel size= (30x30m)

5. Review: Temporal Resolution

6. Review: Spectral Resolution

7. Atmospheric Interactions Key Concepts –Scattering –Absorption –Atmospheric Windows

8. Interactions with the Atmosphere Particles and gases in the atmosphere can affect the incoming electromagnetic radiation. These effects are caused by the mechanisms of scattering and absorption.

9. Scattering Scattering occurs when particles or gas molecules present in the atmosphere interact with and cause the electromagnetic radiation to be redirected from its original path. sun

10. Scattering Scattering is affected by: –The wavelength of the radiation –The size of the particles or gas molecules that scatter the energy –The abundance of particles or gas molecules that scatter the energy –The distance the radiation travels through the atmosphere There are 2 major types of scattering: –Rayleigh scattering –Mie scattering

11. Rayleigh Scattering Occurs when radiation interacts with atmospheric molecules that are much smaller in diameter than the wavelength of the interacting radiation –Atmosphere composed mostly of N 2 (78 %) and O 2 (21%) –O 2 molecule diameter ~0.000316 * μm (μm = 10 -6 m) –Wavelength of green light is ~ 0.5 μm Shorter wavelengths are more readily scattered Responsible for blue skies and red sunsets Rayleigh scattering occurs mostly in the upper regions of the atmosphere (above the troposphere)

12. Rayleigh Scattering Short wavelengths are scattered by this mechanism more than long wavelengths http://en.wikipedia.org/wiki/Image:Rayleigh_sunlight_scattering.png

13. The sky is blue because of Rayleigh Scattering. Shorter wavelengths (i.e. blue) of the visible spectrum are scattered more than longer visible wavelengths. So why isn’t the sky indigo or violet? Rayleigh Scattering

14. Mie Scattering Mie scattering exists when atmospheric particle diameters essentially equal to or larger than the wavelengths of the energy Caused by water vapor, dust, pollen, smoke, etc. Affects all wavelengths of light Responsible for white clouds Mie scattering occurs mostly in the lower portions of the atmosphere where larger particles are more abundant

15. Absorption Absorption is the other main mechanism at work when electromagnetic radiation interacts with the atmosphere. In contrast to scattering, this phenomenon causes molecules in the atmosphere to absorb energy at various wavelengths. Ozone, carbon dioxide, and water vapor are the three main atmospheric constituents which absorb radiation.

16. Absorption (Cont.) Ozone serves to absorb the harmful (to most living things) ultraviolet radiation from the sun. Without this protective layer in the atmosphere our skin would burn when exposed to sunlight. Carbon dioxide is referred to as a greenhouse gas. It tends to absorb radiation strongly in the far infrared (heat) portion of the spectrum - the area associated with thermal heating. Water vapor absorbs much of the incoming long wave infrared and shortwave microwave radiation (between 22mm and 1m). O 2 and N 2 absorb very short wavelengths like X-Rays and Gamma Rays

17. Atmospheric Windows Those areas of the spectrum which are not severely influenced by atmospheric absorption and thus, are useful to remote sensors, are called atmospheric windows.

18. Solar Output, Atmospheric Windows, & Sensor Spectral Resolution

19. Energy Measured At Sensor

20. Image Pre-Processing Radiometric Corrections –Changing the image data BVs to correct for errors or distortions Atmospheric effects (scattering and absorption) Sensor errors Geometric Corrections (a.k.a. georectification) –Changing the geometric/spatial properties of the image data –Done to link pixels with locations on the ground using a coordinate system –Accuracy is determined using the Root Mean Standard Error (RMSE) Topographic Correction –Geometric correction that makes use of a 3-D surface (e.g., a DEM) Image Enhancement –Spatial Enhancement: Filtering –Spectral Enhancement: Stretching

21. Radiometric Correction: Atmospheric Correction Scattering conditions are not constant, so reflectance values recorded by a sensor might vary despite an unchanged surface and identical energy input (e.g., anniversary date imagery) Various algorithms are used to correct for each type of scattering. –Most common type = dark object subtraction Classifications can be made without correction. Often no correction is used. Atmospheric correction is especially important when the spectral characteristics of two images are being compared directly (i.e., not post-classification).

22. Geometric Correction Four Basic Steps of Rectification 1.Collect ground control points (GCPs) 2.“Tie” points on the image to GCPs. 3.Transform all image pixel coordinates using mathematical functions that allow “tied” points to stay correctly mapped to GCPs. 4.Resample the pixel values (BVs) from the input image to put values in the newly georeferenced image 5.The differences between the user-defined tie point locations and the associated point locations computed by the model are used to compute the RMSE

23. Geometric Correction Three Types of Resampling –Nearest Neighbor - assign the new BV from the closest input pixel. This method does not change any values. –Bilinear Interpolation - distance-weighted average of the BVs from the 4 closest input pixels –Cubic Convolution - fits a polynomial equation to interpolate a “surface” based on the nearest 16 input pixels; new BV taken from surface 1 2 3 4 1 2 3 4

24. Image Spatial Enhancement: Filtering Texture can add another dimension to imagery analysis Filters - emphasize or deemphasize spatial information –Low-pass filter – emphasize large area changes and deemphasize local detail –High-pass filter – emphasize local detail and deemphasize large area changes

25. Filter Examples http://rst.gsfc.nasa.gov/Sect1/Sect1_13.html Original Low Pass High Pass

26. Filter Examples Low PassHigh Pass 1 1 1 -1 -1 -1 1 1 1 -1 9 -1 Filters are applied to windows –Windows can be of many sizes (limited by the size of the image) E.g., 5x5, 9x9, 50x50, etc. Windows do not have to be square –In this example we’re using a 3X3 window

27. Image Spectral Enhancement: Stretching Can be temporary: –Pixel values are only changed for display –The pixels retain their original values OR Can be permanent: –The pixel values are changed and a new image is produced

28. Image Enhancement Example: Contrast Enhancement - “stretching” all or part of input BVs from the image data to the full 0-255 screen output range

29. Contrast Enhancement example: A linear stretch is one of the most common types of contrast enhancement Minimum BV is remapped to 0 Maximum BV is remapped to 255 0255127 0255 60108158 Original Stretched

30. Image Display Two types of linear stretches 255 0 Stretched Output Emphasizes middle “piece” of input range 255 0 Linear Contrast Stretch Piecewise Linear Stretch BV (input) BV (output) BV (input) BV (output)

31. Image Spectral Enhancement: Stretching

32. True-Color 321 Image No stretch applied True-Color 321 Image Linear Contrast Stretch