Principles of Remote Sensing  Using Spectral Information

Principles of Remote Sensing Using Spectral Information PowerPoint PPT Presentation


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From Spectra to Product. The spectral response of an unknown can help us establish theidentity of what we are observing much like a fingerprint canhelp us establish the identity of the person who made the print . Product A set of values that is used to describe, in a consistentway, physical pro

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Principles of Remote Sensing Using Spectral Information

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1. Principles of Remote Sensing Using Spectral Information

2. From Spectra to Product

3. Here we start with some spectra made under laboratory conditions of a single type of leaf. We can use know spectra from lab observations to help us identify the unknown surfaces we see from remote sensing platforms. The difference between the two samples is that the left one is green and the one on the right is yellow. If we only have limited spectral range, as is shown at first, we cannot tell the difference between the two. When we have a wider spectral range the additional information can help us in many ways. Here it allows us to separate these two colors of the same leaf type.Here we start with some spectra made under laboratory conditions of a single type of leaf. We can use know spectra from lab observations to help us identify the unknown surfaces we see from remote sensing platforms. The difference between the two samples is that the left one is green and the one on the right is yellow. If we only have limited spectral range, as is shown at first, we cannot tell the difference between the two. When we have a wider spectral range the additional information can help us in many ways. Here it allows us to separate these two colors of the same leaf type.

4. The top two spectra are once again from laboratory samples. Here what allows us to separate them is the degree of response, represented as reflectance in the range of 2.0 – 2.5 microns. The bottom two spectra are from forests. Note the reduced reflectance response throughout the spectra as we are now looking through the atmosphere. Also note the gaps in the response due to absorption bands from various atmospheric gasses (more on this later).The top two spectra are once again from laboratory samples. Here what allows us to separate them is the degree of response, represented as reflectance in the range of 2.0 – 2.5 microns. The bottom two spectra are from forests. Note the reduced reflectance response throughout the spectra as we are now looking through the atmosphere. Also note the gaps in the response due to absorption bands from various atmospheric gasses (more on this later).

5. Some additional spectra. Note that the characteristic shape we have seen up until now changes as we go to mixed land cover types, on the left, and is drastically different for Cheatgrass.Some additional spectra. Note that the characteristic shape we have seen up until now changes as we go to mixed land cover types, on the left, and is drastically different for Cheatgrass.

6. Note the man made substance is radically different from vegetation. The bottom two samples include snow melt. This is one of the most difficult signals for us to properly identify.Note the man made substance is radically different from vegetation. The bottom two samples include snow melt. This is one of the most difficult signals for us to properly identify.

7. Although one might think that the absorption bands are only a cause of difficulty due to loss of signal, they can actually provide us with a lot of information. I use this slide to point out that it is the challenge of a good scientist to make use of all information. On a simple level the absorption bands can tell us about the atmospheric gasses. When used is a more complex way they can tell us about cirrus clouds (using a simple ratio of absorbing and non-absorbing bands) and cloud heights using the technique of CO2 slicing.Although one might think that the absorption bands are only a cause of difficulty due to loss of signal, they can actually provide us with a lot of information. I use this slide to point out that it is the challenge of a good scientist to make use of all information. On a simple level the absorption bands can tell us about the atmospheric gasses. When used is a more complex way they can tell us about cirrus clouds (using a simple ratio of absorbing and non-absorbing bands) and cloud heights using the technique of CO2 slicing.

8. Slant-Path Absorption of the Atmosphere & Location of Primary Atmospheric Windows King, M. D., D. M. Byrne, J. A. Reagan, and B. M. Herman, 1980: Spectral variation of optical depth at Tucson, Arizona between August 1975 and December 1977. J. Appl. Meteor., 19, 723–732. Another view of the absorption bands.King, M. D., D. M. Byrne, J. A. Reagan, and B. M. Herman, 1980: Spectral variation of optical depth at Tucson, Arizona between August 1975 and December 1977. J. Appl. Meteor., 19, 723–732. Another view of the absorption bands.

10. We have dealt with the upper left image by looking at entire spectra of different surfaces. Now we are going to switch things around and look at a movie of complex surfaces one band at a time using all of the MODIS bands. As the movie plays note that the features like land, ocean, and clouds are more or less prominent in particular bands.We have dealt with the upper left image by looking at entire spectra of different surfaces. Now we are going to switch things around and look at a movie of complex surfaces one band at a time using all of the MODIS bands. As the movie plays note that the features like land, ocean, and clouds are more or less prominent in particular bands.

11. We have examined spectra in the visible to near IR range for a few surfaces going from relatively uniform to mixed surface types. Now let’s look at one wavelength at a time for an entire MODIS scene. As the film plays notice how various features become more or less easy to distinguish from each other as we change from band to band. The film includes the thermal bands which we have not yet discussed.

13. We have dealt with the upper part of this slide. Now let’s move on and give a few examples of how we put spectral information together to give information about geophysical parameters as we do in our products.We have dealt with the upper part of this slide. Now let’s move on and give a few examples of how we put spectral information together to give information about geophysical parameters as we do in our products.

14. Examples of Using Spectral Information for Clouds and Aerosols Choosing a single band to find cirrus clouds Using multiple bands to separate smoke, dust and surface Using multiple bands to separate cloud, land and ocean surfaces.

16. Extracting Information by Specific Band Usage King, M. D., Y. J. Kaufman, D. Tanré, and T. Nakajima, 1999: Remote sensing of tropospheric aerosols from space: Past, present, and future. Bull. Amer. Meteor. Soc., 80, 2229–2259. Note that the shorter wavelengths in the image on the left are sensitive to the small smoke particles. The longer wavelengths are not sensitive to smoke and allow us to see the land surface. By choosing which parts of the spectra to use we can begin to extract the information we want. This is the beginning of building a geophysical product.King, M. D., Y. J. Kaufman, D. Tanré, and T. Nakajima, 1999: Remote sensing of tropospheric aerosols from space: Past, present, and future. Bull. Amer. Meteor. Soc., 80, 2229–2259. Note that the shorter wavelengths in the image on the left are sensitive to the small smoke particles. The longer wavelengths are not sensitive to smoke and allow us to see the land surface. By choosing which parts of the spectra to use we can begin to extract the information we want. This is the beginning of building a geophysical product.

17. Spectral optical properties of aerosol

18. Spectral optical properties of aerosol

26. I give the audience time to look this over and think about it. Some issues are: The dates are a clue that one of the difficulties is changing land cover with different seasons.You can see sediment in the ocean on the left image near the shoreline. Glint is a problem in the middle image. Distortion as you approach the edge of the image is a problem for all three. Reg spots in the image are fires which are a post processing color enhancement.I give the audience time to look this over and think about it. Some issues are: The dates are a clue that one of the difficulties is changing land cover with different seasons.You can see sediment in the ocean on the left image near the shoreline. Glint is a problem in the middle image. Distortion as you approach the edge of the image is a problem for all three. Reg spots in the image are fires which are a post processing color enhancement.

27. Just a little more to think about here. I don’t spend as much time on this slide. You can see that when there is heavy aerosol and a lot of cloud it becomes very difficult to distinguish the two by eye. This adds emphasis to the difficulty in creating product and the need for careful choices in the proper use of spectral information.Just a little more to think about here. I don’t spend as much time on this slide. You can see that when there is heavy aerosol and a lot of cloud it becomes very difficult to distinguish the two by eye. This adds emphasis to the difficulty in creating product and the need for careful choices in the proper use of spectral information.

28. The next several slides point out some of the difficulties in separating components in a mixed signal and identifying noise and signal.The next several slides point out some of the difficulties in separating components in a mixed signal and identifying noise and signal.

29. If you want information about the surface this is all noise. If you only want information about the atmosphere it is all signal.If you want information about the surface this is all noise. If you only want information about the atmosphere it is all signal.

30. Mixed information containing both signal and noise.Mixed information containing both signal and noise.

33. Yet another series of complications that must be taken into account to properly use the remote sensing information. This presentation is followed by and exercise using the Hydra tool developed by the University of Wisconsin. This exercise shows how several wavelengths are used to identify cloud, land and ocean.Yet another series of complications that must be taken into account to properly use the remote sensing information. This presentation is followed by and exercise using the Hydra tool developed by the University of Wisconsin. This exercise shows how several wavelengths are used to identify cloud, land and ocean.

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