User Manual - pancroma

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cover types, a linear mixing model can be formulated. This linear mixing modelcan be used to determine the fractions of each cover type present in the image.For example, consider the six Landsat visible plus NIR bands. A reflectancevalue can be computed for each pixel in the image, a different (usually)reflectance for each band corresponding to that pixel. Let's assume that thesereflectances, measured by the satellite sensors are completely the result ofreflectances from four cover types. As a result, each cover type will contribute afraction F (referred to as endmember Abundance) of its individual reflectance Xat that wavelength to the measured reflectance B for each multispectral Landsatband.Let's further assume that we know the reflectances X in each multispectralwavelength for each of the four end members. These can be obtained fromlibraries as described in previous sections, or from actual ground measurements.F and B can be considered column vectors, F composed of the four unknownAbundances and B composed of the six reflectances (one for each multispectralband) measured by the satellite. We can write the linear relationship among X, Fand B as an equation as follows:X 00 * F 0 + X 01 * F 1 + X 02 * F 2 + X 03 * F 3 = B 0This is just the standard linear mixing equation. We can formulate a set of linearequations that relate the reflectances in each wavelength of the end members tothe measured reflectances Y. The relationship is shown in matrix form below.Endmember X i Type ImageLibrary Spectra Fraction ReflectancesX F Bend1 end2 end3 end4reflectance at wavelength 0 |X00 X01 X02 X03| |F0| |B0|reflectance at wavelength 1 |X10 X11 X12 X13| * |F1| = |B1|reflectance at wavelength 2 |X20 X21 X22 X23| |F2| |B2|reflectance at wavelength 3 |X30 X31 X32 X33| |F3| |B3|reflectance at wavelength 4 |X40 X41 X42 X43| |B4|reflectance at wavelength 5 |X50 X51 X52 X53| |B5|Note that if we had only four equations we could solve for the fractions F exactly.We can get a better solution by including all of the multispectral data we have,and then solving the set of over determined equations using linear regression.Note that the system of equations that we have to solve applies to one pixel only.We will have to repeat the solution process for every pixel in the image. This isobviously a computationally expensive task but it can be accomplished by thePANCROMA TM regression solver.The solution yields four sets of fractions F, one for each pixel in the image.These fractions are usually depicted graphically by scaling them so that therange from 0 to 255 and then rendering them as four grayscale images. The267
higher (whiter) the grayscale pixel value, the greater the fraction of that particularend member in the pixel.This process can be illustrated with an example. Consider the Landsat band1image below.For this example, lets assume that the reflectances measured by the satellite arethe result of reflectances from just four end members: Cheatgrass, , asphalt, drygrass and fresh oak leaves. We can obtain reflectance spectra for each of thesefrom the USGS Spectral libraries.Start by opening each of the six Landsat multispectral bands, that is bands1,2,3,4,5 and 7 (recall that band 6 is the thermal infrared band) by selecting ‘File’| ‘Open’ and selecting each of the six band files in succession.Now select ‘Spectral Analysis’ | ‘Landsat Spectral Unmixing’ | ‘Four EndMembers’. The files will be read and the TOA Reflectance Form will appear.268
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1. What Is PANCROMA TM ? ..........
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Compute Single Histogram...........
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67. Tutorial - Pan Sharpening Full
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2. What Useful Things Can PANCROMA
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4. PANCROMA TM Features____________
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5. System Requirements_____________
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7. Getting Started_________________
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Each color and NIR band channel con
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determine if one number is differen
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will be shown at the bottom of the
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12. File I/O_______________________
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13. System Variables_______________
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14. Display________________________
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15. The PANCROMA User Interface____
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not find this file , you will be pr
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If you check the ‘Generate Graysc
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19. Image Subsetting_______________
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IMPORTANT NOTE: There is a check bo
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IMPORTANT NOTE: Saving and opening
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When the Input Box becomes visible,
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20. Batch Subsetting_______________
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21. Quick Start - Pan Sharpening an
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During the internal processing of t
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is unlikely that the settings will
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The default method is checked. The
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around 4000 rows by 4000 columns. I
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the ‘Pan Sharpening Pre Processin
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lowerLimit upperLimitThe following
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Another type of unwanted artifact i
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matching algorithm to be applied. T
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25. ENHG Algorithm - Manual Method_
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The next image is the result of pan
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26. ENHG Algorithm - Automatic Meth
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Next, compute the XIONG file. Open
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The XIONG algorithm is one of the m
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29. AJISANE Algorithm______________
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An example of a pan sharpened image
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The spectral match is indicated by
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You must be careful when selecting
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31. ELIN Local Optimization Algorit
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IMPORTANT NOTE: Regions of high con
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Add the green band and the red band
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33. Pan Sharpen Batch File Processi
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34. Working with SPOT® Data_______
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the special image processing utilit
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35. Working with ASTER Data________
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36. Working with Formosat-2 Data___
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ALI data is similar to Landsat with
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38. Working with Digital Globe® Da
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spectral transmission of the telesc
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ow. Make sure you check this before
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40. Working with Landsat Surface Re
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41. Working with Landsat GEOCOVER D
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foreground and background applicati
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GEOCOVER can offer a very attractiv
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After navigation and selecting your
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Although not designed as a data sou
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44. Working with USGS DOQQ and NAPP
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46. Working with MODIS Surface Refl
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47. Working with RapidEye Data_____
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The Transfer method processes the f
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using the PANCROMA TM ‘Preprocess
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and band 5 (MIR) also be input. Thi
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134
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50. Automatic Image Registration of
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The next two images are the registe
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At the present time, PANCROMA TM ca
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Since only a portion of EMR reachin
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144
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‘File’ | ‘Open’. After your
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Haze reduction may be useful in con
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Save your image using GeoTiff file
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The correction is made according to
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54. Image Processing Utilities - Gr
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Input Channel Adjust Group Utility
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55. Image Processing Utilities - SP
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56. Image Processing Utilities - AS
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57. Image Processing Utilities - Pa
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Channel Level AdjustPANCROMA TM pro
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ENHG Scale FactorThe ENHG slider ba
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59. Image Preprocessing____________
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select ‘File’ | ‘Open’ and
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Analyzer. Doubling is done by first
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high pixel brightness in one image
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There are a few rules of thumb rega
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You will need three control points
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• image resampling• geometric m
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ROWS groupsFirst row of dataSecond
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Where QCAL are the calibrated image
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When you select ‘OK’ the surfac
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The rendering below shows a color t
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Q cal = Quantized and calibrated st
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A section of a SPOT metadata file s
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Temperature (measured in degrees Ke
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Calibration requires multiplication
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NIR band, band 2 (green) and band 3
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and 1 (Brightness, a measure of soi
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X-Y Band Scatter PlotsA scatter plo
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presented. Check the ‘Compute Lin
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PANCROMA TM has a utility for regre
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60. Image Post Processing__________
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You can adjust weighting factors fo
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Unsupervised ClassificationUnsuperv
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Page 217 and 218: Grayscale and Color Image TilingIt
Page 219 and 220: GeoreferencingPANCROMA TM has a uti
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Page 223 and 224: When you click ‘OK’, the select
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Page 227 and 228: PANCROMA TM computed that the cover
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Page 243 and 244: Although the run was not successful
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Page 247 and 248: Now select ‘Spectral Analysis’
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Page 251 and 252: Click ‘OK’. The TOA Reflectance
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Page 257 and 258: Euclidean Distance Fraction TM Anal
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Page 261 and 262: In addition to Landsat 7, Spectral
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Page 281 and 282: The parameters are as follows:Compu
Page 283 and 284: Object Oriented ClassificationPANCR
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Page 289 and 290: Landsat imageImage magnitude spectr
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Page 309 and 310: Now we will start the pan sharpenin
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67. Tutorial - Pan Sharpening Full
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68. Tutorial - Gap Filling using Tr
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You can use the 'Max Cloud' drop do
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'Enter' and the Adjust file will be
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PANCROMA TM does the rest after tha
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70. Tutorial - Gap Filling using Ha
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Another reason to keep the Search E
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Gap Filled Grayscale ImageGap Fille
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When you do so a batch processing d
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The images below show subsets taken
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340
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It is also apparent that the graysc
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73. Tutorial - Six File TERAS Batch
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common areas of both scenes. See th
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348
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Use the checked image processing ut
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IssuesAlthough the gap filling proc
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76. Tutorial - Pan Sharpening Lands
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77. Tutorial - Image Processing Wor
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From Next PageSection 13Subset One
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I again selected ‘Close Graphic I
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I then selected ‘Pan Sharpening
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the vegetation tones are still norm
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Reduction’ and then ‘Apply Cont
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acquired during different seasons o
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This image is better than the Trans
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I also prepared an image using the
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Full sized Landsat scenes can be pr
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78. Tutorial - Improving Image Qual
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The following image is the RGB colo
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Press ‘OK’. The transformed gra
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However it is close enough to illus
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The second image is a straightforwa
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It is also possible to combine the
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80. Pan Sharpened Image: Landsat Mo
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82. Pan Sharpened Image: Landsat De
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88. Pan Sharpened Image: EO-1 Mount
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Multiple Linear Regression, 205Mult
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