In_Class_Spectral Reflectance ASTRO

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Red Rocks Community College *

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101

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Geography

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Oct 30, 2023

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In-class Assignment - Spectral reflectance 32pts Objectives: To understand and gain experience using :  the Electromagnetic Spectrum (EMS)  spectral reflectance curves  discrimination of vegetation and other targets in specific wavelength bands of the EMS  interpretation of true and false-color composite images  relationship between spectral reflectance and spectral signature in composite images Spectroscopy is the study of techniques used to determine the composition of a material based on the presence of atomic, molecular, or ionic elemental species. Instruments that measure such elemental concentrations are called spectrometers or spectrographs. Spectroscopy is used, for a variety of purposes in analytical chemistry to identify substances through the amount of energy or reflectance emitted or absorbed by materials across a range of wavelengths in the EMS. Spectroscopy is the fundamental remote sensing technique used in astronomy and planetary science. Most large telescopes or planetary probes have spectrometers as a part of their imaging equipment. These instruments can be used to measure either the chemical composition, physical properties of astronomical and planetary objects, or to measure their velocities from the Doppler shift of their spectral lines. Every material, man-made or natural, has its own unique spectral curve . This curve is defined by a series of points that show the correlation between wavelength (along the EMS) and the intensity or level at which that material reflects or absorbs light. Laboratory spectra record the reflectance intensity of materials at enough small, discrete wavelength increments to produce a “continuous curve” ( Figure 1 ). Remote Sensing instruments (spectrometers) often only record the level of reflectance intensity from a surface at widely spaced wavelength intervals (called “ bands ”, see Figure 2 ) due to several factors: 1) cost, 2) the amount of time needed for the instrument to collect enough reflected energy to measure, 3) the nature of the intended target (composition), and 4) the result or information desired from the data.

Absorption features are diagnostic dips in reflectance intensity at specific wavelengths produced by the type of atomic bonding, electron valence states, and/or vibrational energies of atoms in a substance. The effect these chemical properties have on a material’s reflectance energy at particular wavelengths can be used to positively identify cation configurations and elemental and molecular composition of a material. For example, the steep fall-off or “shoulder” in reflectance intensity seen between 0.45 and 0.65microns in the curve shown in Figure 1 is due to the presence of the cation Fe +3 . Likewise, in the same curve, the three dips or absorption features in the spectral curve from about 1.8 to 2.5microns are due to the presence of hydrated clay minerals. From comparisons with lab spectral curves for pure substances, a skilled spectroscopist can identify elemental compositions based on the shape and wavelength position of an absorption feature. When interpreting the spectral signatures of materials in true- and false-color images recorded by spectrometers, one needs to examine the separation of individual curves at specific wavelengths to determine if enough separation between the reflectance intensity of different substances enables a correct identification to be made. Typically, the separation required for discrimination between two substances is between 7 and 10 percent reflectance . In the following exercises you will learn to estimate these differences and determine which materials can be discriminated on a satellite image.

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Instructions: Vegetation Compare the various curves at the midpoint of the spectral band (wavelength range) presented in each of the plots below. Assume that there must be at least a 7 % difference between the reflectivity of any curves (features) at the midpoint before they can be separated or distinguished from one another. Question 1. (2) An 8-bit, black and white digital image has a numerical range (called the Digital Number) of 256 shades of gray, with DN 0 = total black (ie. No reflectance) and DN 255 = total white (i.e. total reflectance). If two materials must have a 7% reflectance difference at a given wavelength to be discriminated from one another, what is that difference in DN? If two materials must have a 7% reflectance difference at a given wavelength, then the difference in DN is 17.85. Figure 3 Every line in this line in this figure will have no discrimination.

Figure 4 At 550nm, there will be a clear discrimination between the very top dotted line and the very bottom solid line. Figure 5 At 650nm, there will be a clear discrimination between the very bottom dotted line and the above 3 lines. There will also be no discrimination between the 2 nd , 3 rd and 4 th line.

Figure 6 At 800nm, there is a clear discrimination between every single line. Question 2: (4) Using the plots above, how many targets could be detected from the spectral reflectance curves at the mid-point in the following wavelength ranges: 400 to 500 nm____ 0 ______ 500 to 600 nm____ 2 _______ 600 to 700 nm____ 2 _______ 700 to 900 nm____ 4 _______ Figure 7

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Question 3. (2) Figure 7 is a composite of the separate spectral reflectance curves from the question above. Which single wavelength 450nm, 550nm, 650nm or 800nm would you choose if you wanted to distinguish between the four vegetation targets? I would choose the wavelength of 800nm if I wanted to distinguish between the four vegetation targets. Question 4. (4) a) Using the 800nm wavelength approximate the percent reflectance for the four different types of vegetation in Figure 7. B) Now calculate what DN value of that reflectance would be in an 8-bit image for each of the four targets. C) Is the difference between the four DN values greater than the 7% DN value? D) Does this confirm your conclusion for Question 3 as to which wavelength would be best to discriminate the four targets? A. At 800nm, grass is about 85% reflectance, birch is about 55% reflectance, pine is about 30% reflectance and fir is about 20% reflectance. B. The DN value of grass, birch, pine and fir is respectively about 216.75, 140.25, 76.5 and 51.

C. Yes. The difference is greater than the 7% reflective, or 17.85 DN, for all the 4 types of vegetation. D. Yes, this does confirm my conclusion for Question 3 as to which wavelength would be best to discriminate the four targets because I am able to discriminate between every type of vegetation at a wavelength of 800nm. Question 5. (3) If the 800nm wavelength is considered the “vegetation wavelength” for identifying vegetation signatures or targets what material do you suppose the reflectance is “seeing”? If the 800nm wavelength is considered the “vegetation wavelength” for identifying vegetation signatures or targets, then the material that the reflectance is seeing are vegetation.

Using the ETM color spectral plot of 5 materials and the corresponding ETM false-color image above to answer the following questions. Question 6. (3) Is there any one wavelength that you could use to easily discriminate between all 5 targets on a gray digital image? If so, which one? If not, which one comes the closest? There is not any one wavelength that one could be used to easily discriminate between all 5 targets on a gray digital image. The wavelength that comes the closest to discriminating between all 5 targets on a gray digital image would be 1.45nm. Question 7. (10) Choose two of the spectral curves and make a table to a) record their approximate percent reflectance at their intersection with the three wavelengths indicated by the vertical, colored lines (R,G,B). Calculate and input into the table, the approximate DN value for each of the percent reflectance values for the two targets. c) Are the DN more than 7% apart for the two targets in each of the 3 wavelengths? The two spectral curves that I chose are Basalt and Quartz. A. Basalt: R=.08, G=.1, and B=.1 || Quartz: R=.8, G=.78 and B=.7 B. Basalt DN: 20.4, 25.5 and 25.5 || Quartz DN: 204, 198.9 and 178.5

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C. Yes, the DN are more then 7% apart for the two targets in each of the wavelengths. Question 8. (4) Now, based on the DN values in each of the three wavelengths for the two targets, a) predict what color each target should be on the false-color image. Based on this prediction, b) identify and label/locate an area on the false-color image that represents each of the two materials. A. In the false color image, Quartz will look white and Basalt will look black. B. On the 3 rd quadrant of the false-color image is a large black spot. This black area will be composed mainly of Basalt. On the right half of the false-color image, specifically near the middle, there will be white steaks along a ridge. The white area along this ridge will be mainly composed of Quartz.