Spectral Unmixing Applied to Desert Soils for the - Naval ...

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small concentrations making them un-useful for target detection. If, however, higher resolution imagery were available it may still prove to be a useful target based on the fact that positive hits were detected and BSCs were found to exhibit similar changes in spectral characteristics as soils when exposed to impact-related surface disturbances. What seems, at this point to be the most successful test, was the disturbed creek soil endmember in the f110623t01p00r10 data set. This was a bit of a surprise because the expectation was that the higher resolution imagery would be more successful which is why it was utilized for both the initial and repeatability tests. The lower resolution imagery was only utilized when results in the repeatability test were too inconclusive to be considered a valid test and further testing was required. The fact that the f110512t01p00r08 data set was not successful and the f110623t01p00r10 was can also serve as a positive reflection on the test. The issue was that the distribution of positively identified pixels was confined to steep slopes for the most part with a few in what looked like runoff areas in the higher resolution data set. This could mean that the circumstances creating the spectral characteristics specific to the disturbed creek endmember were not present in the imagery. This theory is further supported by the lack of a substantial creek feature within the 110512t01p00r08 imagery. The f110623t01p00r10 data set however, had several features that appeared to be drainage basins. The result was significant successful identification of areas that appear to be drainage basins with OHV trails in them not always visible in the imagery. In almost every case, a pixel with a value between 5-11% was a positive match to an area with an OHV trail or a drainage basin. While 5-11% seems a lower range than other data sets, one must remember to take into account the fact that a larger pixel size means similar features will take up less of a percentage than in smaller pixels. The positive identification range is consistent with the expected percentage of a pixel that a trail/OHV route should occupy. C. COLOR COMPOSITES Color composites using the user supplied endmembers in conjunction with imagery derived endmembers provided useful results. While the composites illustrate 78
potential failures in endmember ability to accurately identify target material beyond a certain threshold, they also illustrate the success of these endmembers in identifying features such as trails. Use of the color composites filled in gaps between pixels that were difficult to correlate alone, such as s shaped feature seen in Google Earth. This feature did appear to be part of a trail that continues up a ridgeline and around the back side of the peak identified by the camp road endmember. These color composites serve as an example of the potential for this method in identifying features not readily seen in true color satellite imagery. D. FUTURE WORK Given more time, further work on this topic should include going to the imagery flight locations to physically ground truth the MTMF results and trying the experiment again on other types of available Hyperspectral imagery. Hyperspectral systems of interest would be those covering a 380-2500 nm wavelength range, and higher spatial resolution if possible. Lower resolution imagery should also be explored due to the surprising success using the disturbed creek soil endmember in the f110623t01p00r10 data set. Studies utilizing BSC spectral changes should also be further explored. Endmembers for BSCs from areas with higher concentrations of the organisms should be collected as well as those with better species matches to the areas under analysis. While the California collection sites were chosen to be as close to the Colorado sites as possible, there are other areas outside of California that have soil components more closely matched to the Colorado locations. Spectral libraries from other similar locations to the study sites should be collected and tested. Libraries should also be collected from the actual study areas while ground-truthing. The same analysis should be run with site spectra and compared to the California endmember results to test for accuracy. This could also serve in developing a difference threshold between collection and imagery sites that would still allow for successful target material identification. Another potential area of study is the amount of variation in feature depths as a response to disturbances. The amount of variation across a given soil component may help in establishing a baseline to judge how much/what type of disturbance has occurred in the 79
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NAVAL POSTGRADUATE SCHOOL MONTEREY,
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REPORT DOCUMENTATION PAGE Form Appr
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Approved for public release; distri
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ABSTRACT Desert areas cover approxi
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TABLE OF CONTENTS I. INTRODUCTION..
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LIST OF FIGURES Figure 1. The above
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spectrum by atmospheric effects. Re
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emoved function showing an absorpti
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LIST OF TABLES Table 1. This table
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LIST OF ACRONYMS AND ABBREVIATIONS
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I. INTRODUCTION A study published b
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II. THE PHYSICS BEHIND REMOTE SENSI
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sensitive a given sensor is to diff
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Figure 3. From Green et al. (1998),
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analyzing imagery spectra, it is mo
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After data have been converted to r
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Collins et al. (1997) was able to s
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These purposes include, but are not
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III. DESERT ECOSYSTEM CHARACTERISTI
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sagebrush of Utah, Montana, and the
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in desert regions include argids, o
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2. Biological Soil Crusts (BSCs) Bi
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2004), especially in cases where ma
Page 47 and 48: IV. STUDY SITES The focus area of t
Page 50 and 51: Figure 13. This figure illustrates
Page 52 and 53: Following the uplift that occurred
Page 54 and 55: the Mazourka Canyon OHV park betwee
Page 56 and 57: wavelengths being analyzed to obtai
Page 58 and 59: 2. Field Spectroscopy An Analytical
Page 60 and 61: A spectral library was then built a
Page 62 and 63: after atmospherically correcting th
Page 64 and 65: where: is the mean corrected and no
Page 66 and 67: also be seen in Figure 23. The leve
Page 68 and 69: Figure 24. This figure is a compari
Page 70 and 71: Figure 25. This figure shows ASD co
Page 72 and 73: Looking at Figure 25 it is apparent
Page 74 and 75: A. IMAGERY DERIVED ENDMEMBERS The i
Page 76 and 77: Figure 28. The above shows some of
Page 78 and 79: spectrometer, reflectance values we
Page 80 and 81: such an inference can be made (Ben-
Page 82 and 83: While this is lower than the hoped
Page 84 and 85: While the lower value would initial
Page 86 and 87: Figure 33. This figure shows the ad
Page 88 and 89: Inset C of Figure 35 is the same da
Page 90 and 91: However, the presences of BSCs are
Page 92 and 93: A B C Figure 37. Inset A shows the
Page 94 and 95: A B C Figure 38. Inset A shows a co
Page 96 and 97: differences in the studies by other
Page 100 and 101: area making it possible to tell wha
Page 102 and 103: Clark, R. N., Swayze, G. A., Livo,
Page 104 and 105: Kruse, F. A., Boardman, J. W., and
Page 106 and 107: Sharp, R. P., and Glazner, A. F., (
Page 108: INITIAL DISTRIBUTION LIST 1. Defens
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