User Manual - pancroma

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accordance with the accompanying Landsat metadata) without loss of precision.DNs have only 8 bits of dynamic range and this is of course limits the precision ofthe TOA reflectance values derived from them.Using the LSA with surface reflectance data proceeds almost exactly as with thecorresponding DN bands. Select ‘File’ | ‘Open and open either six Landsatsurface reflectance band files, band1 (Blue), band2 (Green), band3 (Red), band4(NIR) band 5 (SWIR) and band 7 (LWIR) or alternatively include the thermal IR(TIR) band by opening band1 (Blue), band2 (Green), band3 (Red), band4 (NIR)band 5 (SWIR) band6 (TIR) and band 7 (LWIR). Now select ‘Spectral Analysis’ |‘Landsat Spectral Analyzer’ | ‘Six/Seven Reflectance Bands’ | ‘<strong>Manual</strong> Method’.The Spectral Criteria Form will be displayed as described above. The settingsare made the same as described previously. After accepting (clicking ‘OK’) theLSA will compute the image as before.A couple of notes about the TIR band. Thermal data is archived in I16 format asscaled degrees Celsius. The integer values should normally be multiplied by ascaling factor of 0.01 to convert the I16 data to degrees Celsius. PANCROMA TMinstead multiplies the data by a factor of 0.0001, the same scale factor as is usedto convert the I16 band data to surface reflectance. The advantage of doing thisis that the data stored in the thermal band is of the same order of magnitude asthe reflectance data, which simplifies data display. Since the band data can beconsidered as orthogonal vectors, it is not possible to combine them as scalarvalues anyway so it does not really matter how they are scaled from a processingstandpoint. However, if thermal ground truthing data is used to calibrate or verifythe results, the measured temperatures should be divided by 100.0 in order tomatch the values that PANCROMA TM computes.Note that processing times for surface reflectance data will take somewhat longerthan using DN band data. This is because the integer reflectance files are twiceas large as the corresponding DN band files, and decoding the 16 bit data andconverting it to float type takes longer for each file.Another application for Landsat reflectance data is combining channels to maketrue color or false color RGB composite images and even pan sharpenedimages. Because atmospheric effects are removed, this data can make imagesof exceptional quality. Example RGB color composite and pan sharpenedimages of the massive Chuquicamata mine in northern Chile made with Landsatsurface reflectance data are shown below.243
The pan sharpened image was created by downloading a standard Landsat Path1 Row 75 DN panchromatic band. The reflectance band files had to beconverted from 16 bit to 8 bit format. Then the corner coordinates wererationalized using the ‘Compute Maximum Common Extents’ utility. The scales244
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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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100
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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
Page 193 and 194: A section of a SPOT metadata file s
Page 195 and 196: Temperature (measured in degrees Ke
Page 197 and 198: Calibration requires multiplication
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Page 201 and 202: and 1 (Brightness, a measure of soi
Page 203 and 204: X-Y Band Scatter PlotsA scatter plo
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Page 207 and 208: PANCROMA TM has a utility for regre
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Page 211 and 212: You can adjust weighting factors fo
Page 213 and 214: 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 231 and 232: SPOT ® Point Spectrum Generator TM
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Page 237 and 238: Digital spectra are recorded for mi
Page 239 and 240: The next step is to overlay the Lan
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Page 243: Although the run was not successful
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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
Page 259 and 260: The idea is to adjust the included
Page 261 and 262: In addition to Landsat 7, Spectral
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Page 267 and 268: Note that the band 6 (TIR) track ba
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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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The following is an example of an i
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In order to deconvolve using fixed
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63. Writing an Index File for an SR
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It will be saved as a .dat file. A
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64. Processing Huge Files and File
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My area of interest for this image
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306
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Now we will start the pan sharpenin
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66. Tutorial - Pan Sharpened Image
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The next step will be to create an
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The panchromatic image is the one i
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And my result looked like this:As y
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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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