the file
Contents
1. LIF Cell x 3 000000 REUS Ce y 1 000000 Hep Registration Coordinates E astings zh4335 534283 Marthings fool 350 651 343 11 Estimate how many pixels the ASTER image is displaced from the Landsat If the ASTER image is too far west you need to move it east as in the example above Here the registration point was first changed to 3 0 and this became the cell associated with the eastings and northings listed The entire image shifted to the east Next the image was too far to the north so to move it south the registration point was changed to 3 1 The rule is ve X moves image east i e you want to assign the e n coordinate to a point further to the west than 0 0 ve x moves image west i e you want to assign the e n coordinate to a point further to the east than 0 0 ve y moves image north i e you want to assign the e n coordinate to a point further to the south than 0 0 ve y moves image south i e you want to assign the e n coordinate to a point further to the north than 0 0 12 Save the changes and assess your image again You may need to repeat the process to get an exact fit this is a trial and error process 13 Repeat this process for your corresponding SWIR dataset The displacement amount will be half the value of the VNIR as SWIR pixels are twice as large as VNIR pixels e g in the example above make the2. Output Size Width 4980 Height 4600 File Size 65 54 MB Piels Pizel Sidi 15 me D Pixel Height i5 E e 25 Dpi Display 96496 hd f Uni vM Maintain aspect ratio v Delete output transforms write world file Help B Construct the SWIR dataset 1 Open a new algorithm window or a new image window You should have one Pseudo layer in the empty algorithm Load your crosstalk corrected HDF file into the pseudo layer Duplicate the layer five times total of six layers Select SWIR band 4 for layer 1 and rename the layer to reflect the original band number e g B4 NB Be careful not to load band 3B into band 1 of your algorithm the real SWIR band 4 is actually called band 5 in the HDF dataset Select SWIH band 5 for layer 2 and repeat for the other layers up to band 9 Rename the layers Save the dataset as an ER Mapper raster dataset ers The dataset should be saved as an 8 bit unsigned integer with 30m pixels Ensure output transforms are deleted C Construct the TIR raster dataset 1 2 3 4 5 6 Open a new algorithm window or a new image window You should have one Pseudo layer in the empty algorithm Load your crosstalk corrected HDF file into the pseudo layer Duplicate the layer four times total of five layers Select TIR band 10 for layer 1 and rename the layer to reflect the original band number e g B10 Select TIR band 11
3. taster icons aleks tir HDF to TIR bands only BATCH aleks tir aster icons aleks rgb Produce RGB 321 algorithm BATCH aleks rgb321 wizard Name of tif a Helpful w name of batch script The first file in the list is the icon without the tif ending All the icons in this case are stored in the aster_icons subfolder of the icons folder The second column is the helpful text that will appear next to the button when you move your cursor over it The final column holds the associated batch scripts that will run when the icon is activated Note that no file path is necessary when the scripts are stored in the Batch directory since this is the default for all scripts A file path is only necessary if you put your icons or batch scripts into subfolders Back to Contents 39
4. the most variation nearly all in fact is recorded in MNF band1 A smaller amount is recorded in B2 then 3 4 and so on until the line becomes just about flat The last MNF band will look very speckled and will be mainly noise gl MNF Eigenvalues E 2 ol x File Edit Options Plot Function Help MNF File AST L1B SWIR 5254 dkpix T E 4 Eigenvalue Number 32 6 In the Available Bands List window select RGB color and then choose MNF bands 1 2 3 for R G B respectively or any other combination you like although this one will probably be the most useful as it shows the greatest amount of variation Click Load RGB to view the image Bil Available Bands List E 1 R MNF Band 1 AST_L1B_SWIR_5254_dkpin G MMP a File Overlay Enhance Tools Window File Options E E nod S wIH MMF rab pel 23 ien MNF Band 1 AST_L1B_S WIR e Oo MNF Sie wd m iiA eA m MNE Bond d AST LIB WIR sen O MNF Band 5 AST LIB SWR see O MNF Band 6 AST_LIB_S WIR H Map Info E P AST LIB SWIR_S254 dkpiw n B4 n Bp a m C Gra Scale AGE Color Bn MNF Band 1 amp 5T L1B SwIH 52 MNF Band 2 amp 5T L1B SwIH 52 ei 1 Scroll 0 09719 E E x ES 41 Zoom 2x C B MNF Band 3 457 LIB sWwiR_5S2 Dims 2777 2616 Floating Point BIL Load RGB Mo Display Three image windows appear They are all geolinked The main window is the mage window from which you can control image enhancement etc
5. The Scroll window allows you to view the entire image and select a part of it to view in the mage window by moving the red box The Zoom window allows you to zoom in on areas of the image 7 In the Image window go to Enhance image linear 2 to apply a simple transform You can see the variation in the image through the different colouring For example areas that are red are similar to each other but different to areas that are blue or green or yellow So for example red could indicate carbonate rocks and blue silicate rocks Green could indicate dense vegetation You won t know until you do some ratios and band combinations in ENVI or ER Mapper to find out what these areas represent Also try overlaying the geology maps You can also classify or vectorise the principal component images to overlay on other images 8 You can import vector files e g geology or export the image as a bil to use in Arcmap or as an ERMapper ers dataset Go to the main toolbar File gt Save As gt select your file type Note unlike ER Mapper ENVI does not set null values to 0 so you may have to do this manually back in ER Mapper Back to contents 33 15 Principal components Use Principal Components to produce uncorrelated output bands to segregate noise components and to reduce the dimensionality of data sets Because multispectral data bands are often highly correlated the Principal Component PC Transformation is used to produce unco
6. Type Pima Files dep fos C ASD Files asd From the main File menu select Open Files The Select and Sort Spectral Files window will pop up asking what to do Press the Add Files sort by name button and select the Data Files option A file chooser window will now appear Select the file s you want in this case they are all dsp and select Open The file chooser disappears and you are left once again with the Select and Sort Spectral Files dialog box Press the OK Return to Application button 24 Select and Sort Spectral Files OF Return To Application SIT Dmm reign Add Files Younger Files First Cancel do NOT modify elit Add Files Older Files First TESTES anne Review Sorted Files Start Mew File List Add Filles DO NOT Sort Select Type Of File Data Files C Library Files 4 The names of the files you selected now appear in the white subwindow which you can maximise of the main application window You can click on one the file names to display the associated spectra in the same window 10 x 18 x Se SpecWin2 File Edit View Window Math Functions PlotSpecs Help Difco tl Sele amp vv zr A vt zs vw 2 4 S 5s I 140603G3 DSP 140603G1 DSP Pseudoreflectance 1800 2000 Wavelenath nm For Help press F1 NUM Coords 2118 3047 18 5 Now the files must be converted to text files Go to the View menu on
7. complete z Restart wizard Finish Shop Close A disadvantage of using this wizard is that you can t set the method by which the dataset is saved i e 8 bit 4 byte etc It does save a bit of time but doing the same process manually is not particularly difficult or time consuming and therefore could be a better option Back to contents 10 4 Image Rotation At the moment the images you have loaded are in satellite orientation i e they are rotated with respect to the surface because the satellite does not travel exactly N S on its passes The image must be therefore be rotated back into map orientation it is already projected generally in WGS84 and UTM You need to find what angle the image must be rotated through before using the Geocoding and Orthocorrection Wizard to rotate the image Note if you used the HDF Import Wizard to convert your HDF files to ER Mapper format and you have already rotated your datasets then you can skip this step Go to File Open or press the i i button in the main toolbar Highlight the VNIR dataset you made in the previous section but don t open it 3 Click on the nfo button a new window will pop up with some metadata about the image see below 4 Find Rotation in the list and take note of the angle Close all of the windows Dataset Information E Bl x Data Type Rasher File Name M acres projectz raster l immgl mtgordons AST LTB VMNIF Geodetic Dat
8. intro html 3 You will need to obtain a login follow the instructions 4 On the website you will find the document Procedures for accessing ASTER satellite image data on ACRES Digital Catalogue This contains complete instructions on how to find your data The ASTER scenes are stored on DVD at Geoscience Australia contact an ACRES or RSA person to gain access to the DVDs 5 Copy your selected scene s to your hard drive or CD generally it is better to have the scenes on your hard drive to speed up processing 2 Crosstalk Correction Crosstalk is an effect in ASTER imagery caused by signal leakage from band 4 into adjacent bands 5 and 9 The primary band causing most of the cross talk problem is band 4 What they believe is happening is that some of the incident photons onto the band 4 detector plane are reflected not a surprise since even a perfect single detector can reflect as much as 30 of the incident light The problem is that there are no baffles or other structures blocking light from band 4 bouncing around to the detectors for the other bands Basically the detectors are arranged in a rectangular geometry and the top of the rectangle contains all of the filters for all of the bands The bottom contains the detectors for all bands and all of the detectors have the same spectral response Once an incident photon enters it is basically trapped until some detector collects it If the band 5 detector gets a photon through t
9. new SWIR registration pixel 1 0 14 You probably won t need to repeat the process for the TIR dataset the pixel size is too large to show much effect The TIR dataset needs to be moved by 1 6 of the amount that the VNIR image is moved Usually the overall shift is less than 6 pixels so the TIR dataset doesn t usually need to be moved 19 Example The linear N S features in green Landsat and red ASTER VNIR band 3 represent a road As you can see in the top left image the ASTER scene is offset to the west from the Landsat scene It must be moved to the east to align with the road as depicted in the Landsat scene In the top left image the registration cell is 0 0 one 1 Algorithm Not Yet Saved The registration cell coordinates have been changed to 5 0 in the image on the top right As you can see the images are now more closely aligned although not yet completely In the bottom left image the scenes are now well aligned E W with a registration coordinate of 8 0 but you can see they are not properly aligned N S The ASTER scene is slightly too far north and must be moved south oe 1 Algorithm Not Yet Saved The bottom right image shows the two aligned scenes The registration cell coordinates for the ASTER scene are now 8 2 Using this information the corresponding ASTER SWIR image can be aligned to the Landsat image by changing its registration cell coordinates to 4 1 divide by 2 b
10. of the image 34 HPC Eigenvalues File Edit Options Plot Function Help Eigenvalue 7 In the Image window go to Enhance image linear 2 to apply a simple transform You can see the variation in the image through the different colouring For example areas that are red are similar to each other but different to areas that are blue or green or yellow So for example red could indicate carbonate rocks and blue silicate rocks Green could indicate dense vegetation You won t know until you do some ratios and band combinations in ENVI or ER Mapper to find out what these areas represent Also try overlaying the geology maps You can also classify or vectorise the principal component images to overlay on other images 8 You can import vector files e g geology or export the image as a bil to use in Arcmap or as an ERMapper ers dataset Go to the main toolbar File Save As gt select your file type Note unlike ER Mapper ENVI does not set null values to 0 so you may have to do this manually back in ER Mapper Back to Contents 35 16 Decorrelation Stretch Decorellation stretch is another way to enhance images It is especially useful when viewing bands that are highly correlated e g combinations of the TIR or SWIR bands For example the TIR bands 10 12 and 13 are highly correlated and produce a fairly dull RGB image This sort of image is difficult to interpret and not particularly useful Applying deco
11. right resampled to ASTER bandwidths same wavelength range shown Si Spectral Library Plots File Edit Options Plot Function Help 1 4060361 txt B 16 20 2 2 2 4 4 16 18 20 2 2 2 4 Wa length Wavele ength Back to contents 3 14 Minimum Noise Fraction MNF MNF minimum noise fraction rotation using principal components calculations is used to show the variation between bands in an image This is a statistical method which works out differences in an image based on pixel DNs in various bands Mathematically this uses eigenvectors and eigenvalues to work out the principal vectors and directions of the data cloud collection of data values for the image The idea is to show the differences rather than the similarities between bands So in principal component images you are looking at the maximum differences between what the sensor is picking up in different bands rather than where different bands are recording the same thing i e reducing redundancy The calculations also identify noise in the image After doing this analysis you can then go and do some band ratios compare to your MNF or principal components image and perhaps assign each MNF band to some feature or characteristic Remember that these are statistics and do not indicate any specific mineral merely differences between areas of the image This method works best for SWIR images For more information look in the ENVI or ERMapper help Use the MNF Rotation t
12. the main toolbar and select DSP2ASCI dsp to ASCII i e text format A new application window opens Press the Get and Convert Files button Again a file chooser Opens Bienvenidos Convert Pima dsp Files to Text Get AND Convert Fies SPECTRAL d pean Code Author Bill Peppin bill peppin reno nv us 775 826 5816 voice March 2000 6 Select the files you want to convert and then exit the conversion application New ascii files txt are automatically created in the same folder as your original dsp files 25 and with the same name The files are created instantly so no other windows or dialog boxes appear 7 You can now close SpecWin This is mainly a display tool but there are a few things that you can do with your spectra in this progam The most useful of these at the moment is the ability to view the spectra and to convert them to ascii files for import into ENVI Back to contents 26 11 Creating a Spectral Library in ENVI from PIMA data ENVI is an image processing program similar to but more advanced than ER Mapper One of the chief advantages is the ability to import PIMA and library spectra and to compare these to spectra from your image whatever the sensor you happen to be using For example you can import PIMA spectra from field sites match them against a spectral library to find out what end members can be identified and resample the original spectrum to ASTER resolution This i
13. 0 662000 0 862000 J VNIR3B Incl Offset 0 862000 0 862000 SVVIBRA Incl Offset 0 217400 0 217400 SVVIBb Incl Offset 0 069600 0 069600 SVVIBb Incl Offset 0 062500 0 062500 Offset 0 059700 0 059700 Offset 0 041700 0 041700 Offset 0 031800 0 031800 TIRTU Incl Offset 0 005882 0 006882 0 006780 0 006590 0 005693 0 005225 MphMethod UTH 4 Open a new image window and the algorithm window 5 Load your VNIR rectified dataset into the algorithm and assign each band to a new layer layer1 band1 layer2 band2 etc Rename each layer to represent the original data band B1 B2 B3 Algorithm 4 ES E m rj x View Mode Normal D Feather Smoothing T Feather T Smoothing Feather al Smoothing Close Description Ma Description E dit v X x e w s e e ale ajeje mj E amp Ps Default Surface Coordinate System Surface Laver AST LIB VANIR 5254 rect ers E B383 WNIR 076 086 15m m dE X gt Emi 6 Select the first layer and open the formula editor 14 7 Type in the formula Input 1 x UCF in this case the UCF for VNIR band 1 is 0 676 Press Apply Changes Repeat this process for every band in the algorithm inserting the appropriate unit conversion factor each time Formula Editor Te xj Principal Components Patios Standard Seismic Description Default Fo
14. ASTER Processing Manual Compiled by Aleks Kalinowski and Simon Oliver Remote Sensing Applications Geoscience Australia October 2004 Contents i Introduction ii Useful References Processing steps for L1B scenes Obtaining ASTER scenes Crosstalk Correction Importing into ER Mapper Image Rectification Radiance Calibration Dark Pixel Correction Registering ASTEH images to Landsat Tips ASTER Band Ratios 0 10o001O0InN Some Useful Hints for Beginners 10 Changing Format of PIMA Spectra Using SPECWIN 11 Creating a Spectral Library in ENVI 12 Using ENVI s Spectral Analyst to Determine Mineralogy 13 Resampling Library Spectra to ASTER Band Resolution 14 Minimum Noise Fraction Images 15 Principal Components Images 16 Decorellation Stretch Images 17 Writing Scripts with ER Mapper i Introduction ASTER is the Advanced Spaceborne Thermal Emission and Reflection Radiometer a multi spectral sensor onboard one of NASA s Earth Observing System satellites Terra which was launched in 1999 ASTER sensors measure reflected and emitted electromagnetic radiation from Earth s surface and atmosphere in 14 channels or bands There are three groups of channels three recording visible and near infrared radiation VNIR at a spatial resolution of 15m six recording portions of shortwave infrared radiation SWIR at a spatial resolution of 30m and five recording thermal infrared radiation TIR at a res
15. Construct the VNIR dataset 1 Start ER Mapper and open the algorithm window with a new image window You should have one Pseudo layer in the empty algorithm 2 Load your crosstalk corrected HDF file into the pseudo layer 3 Duplicate the layer twice total of three layers 4 Select VNIR band 1 for layer 1 and rename the layer to reflect the original band number e g B1 5 Select VNIH band 2 for layer 2 and VNIR band 3 3N not 3B for layer 3 and rename the layers argon E ini x View Mode Normal Y D Feather Smoothing ro a Llose Description No Description o i X w e w e e e e ale mjmje a Ps Default Surface Coordinate System Surface Laver Coordinate System Surface Layer 457_L1B_003_087 92000012003 031820603035254 cha ht G B3vNIR BandsN 076 086 15m v Be XX 6 Save the dataset as an ER Mapper raster dataset ers The dataset should be saved as an 8 bit unsigned integer with 15m pixels pixel width amp height Make sure output transforms are deleted and be sure to give the file a meaningful name for example reflecting the level of processing that has been applied Eb Ioj x EE Output Attributes 9 I tit What Ok Output Type Multi Layer f Current view pou z Data Type II nisignedeBitl nteger C Entire Page ptione Mull Value 0 Defaults Save As ER Mapper Dataset
16. HDF Import Wizard Filename specification Please select the input dataset B uns 061 9200001 2009 09182003035254 hdf Produce compressed ECW image Please select the EAN output dataset i v Produce ers raster image Please select the output dataset Ntacres _project2test_5254 ers i z Back Nest Cancel 4 On the next panel you have the option of rotating the scene to true north accounting for the rotation of the image due to the orientation of the satellite as it makes its pass You can use this option or manually rotate the image later Here you also have the option of setting a null value for null cells in the image Type O into the Null Value text field if it isn t automatically there and tick the Use a null cell value box Click Next HDF Import Wizard Additional Options M Rotate image ta True Morth v Use a null cell value Mull value Back Next Cancel 5 The next panel allows you to set cell attributes Most importantly it allows you to set the output cell size which is chiefly useful if you are going to import bands with different resolutions into one dataset To do this tick the Custom cell size box For example if you are importing the VNIR and SWIR bands together you can set the cell size to 15m or 30m for all bands You then need to choose a resampling method cubic is recommended If you are importing bands with the same spatial resolution then don t check the Cu
17. In the algorithm window load the dataset into one layer Type in the formula in the formula editor Now duplicate the layer choose appropriate bands for each layer and rename the layers as required This saves you typing out the formula many times 5 Save the dataset as an ER Mapper Virtual Dataset put VDS in the filename so you can distinguish it from real datasets easily The virtual dataset is really an algorithm that is saved to look like a dataset but it actually references the original dataset s in this case the file you just created references your radiance calibrated dataset so any changes to that dataset will also be reflected in the VDS Alternatively save it as a 4 byte real dataset for future work Ensure rotation is 0 in the header file else there could be problems importing the image into ENVI see the Tips section at the back of this manual 6 Repeat this process for your other radiance corrected datasets SWIR and TIR Back to contents 17 7 Registering ASTER image to Landsat pan image Rotating ASTER scenes as described in previous steps puts the data in the correct orientation but not necessarily the correct position relative to the ground or to other ASTER scenes or bands One way of correctly rectifying the ASTER scene is to register it to the Landsat pan mosaic image of Australia The Landsat pan mosaic covers the entire continent and has been registered to differential GPS points around Australia As su
18. alg ending save algorithm Shdfalg println saved exit 1 try agam error message telling person to open an image in a window println error exit 1 38 Adding Buttons You can design your own button to put onto one of the standard toolbars The button is a tif which you can alter in any drawing package and save as a new button Once that is done you must insert a line into the script for the toolbar of your choice that will both install the button on that toolbar and run your script from that button The icons buttons are all stored in the cons subfolder of the ER Mapper 6 4 folder You can take any of these save as another button then modify in your drawing program The toolbar files are in the Config subfolder of the ER Mapper 6 4 folder There are other files in this folder so look for those that have the ending bar e g aster bar These are text files that store the information about what buttons and functions need to be on that toolbar Here is an example of the toolbar file for the ASTER toolbar E FILE SERMAPPER config aster bar CREATED 13 Feb 2002 AUTHOR Abdullah Mah PURPOSE ER Mapper ASTER config file HHH HH HHH HH FEE HH FEF tH FF ERE EE tH SF tH HE SF HH EF tH EF HH FEF tH HF aster icons aster bar icon ASTER Processing Wizard BATCH aster aster main aster icons aleks vnir HDE to VNIK banus only BATCH aleks vnir aster icone alekse swir HDF to SWIR bands only BATCH aleks_swir
19. also a good idea to set the y axis scale to adjust automatically Minerals with matches below about 0 5 shouldn t be considered matches usually the top few minerals are correct However you still need to match the spectra manually to ensure best results don t trust the software to do it for you Often there will be some odd minerals in the top few matches so don t be fooled by them Check peak or trough coincidence by running the cursor over the spectrum Check for relative depth of absorption features Back to contents 30 13 Resampling Library Spectra to ASTER Band Resolution You can do more spectral matching and mapping by comparing your PIMA results directly with ASTER results To do this the PIMA spectra need to be resampled to ASTER band resolution This also shows you which bands are likely to be the most effective at identifying various minerals 1 On the main menu main toolbar go to Spectral Spectral Libraries Spectral Library Resampling A file chooser will appear Select the library you want to resample and click OK The Spectral Resampling Parameters window appears 2 In the Resample Wavelength To part of the window select Pre Defined Filter Function A sensor list will appear click on the button Select ASTER from the sensor list 3 Display the resampled spectra You can run your mouse pointer over the spectra and click to find what spectral band you are looking at Below left original PIMA spectra Below
20. are PIMA spectra can be saved as text files when they are collected but this is a somewhat involved process It is easier to convert all the relevant files at once using a conversion tool such as Specwin which was developed and is provided free of charge by Spectral International Inc Below are instructions for obtaining installing and using the tool to deliver PIMA spectra to ENVI as text files 1 2 Follow the link to SIl s website at http Avww pimausa com specwin html Scroll to the bottom of the page and follow the download instructions You will need the files TextUtil exe SpecWin exe and DocWord exe When downloaded double click on each to extract the required files to the c Iwpbin directory In this directory you will find a file called specwin exe the actual application different to the original file you downloaded Put it on your desktop or double click to start it Bienvenidos B x Welcome to Specwin a general program for spectral analysis Your first step on launching the program is to select FILE SELECTION Do this by pressing the toolbar button that looks like this Specwin Revision 1 9 June 2001 Bill Peppin l fo 826 5616 Click Here For Brief Overview HIS peppin reno Av us Press the Launch the Program button From the popup window select Pima Files as shown below You should now have a main window with a white subwindow open on the screen Select a Spectral File
21. b with Wordpad this is best but other notepad type text programs should also work There is a reasonable help section associated with scripting in the ER Mapper reference manual although you will probably learn more by studying existing scripts You can run scripts from ER Mapper or from the command prompt Running a script from ER Mapper 1 Start ER Mapper 2 Goto the View menu and select Batch Engine Script Control from the drop down list An empty dialog box with the same name will open 3 In the dialog box click on the Run Script button An ER Mapper file chooser will appear automatically connected to the C ERMapper64 batch directory 4 Choose a script from the list and click OK The name of the script will appear in the blank window of the Batch Engine Script Control dialog box and the status will be Running Batch Engine Script Control E Ioj x Script Mame Status Llose aleks rgbi3z21 wizard erb Running a Cancel Script Hun Script m Help In the case of wizards or functions that require prompts e g inputs or outputs you will see dialog boxes pop up Otherwise you may not see anything until the process is finished Some processes require you to have your image open first You can run just about all of the processes that appear in the toolbar from the dialog above You can also easily design and add buttons to the toolbars to run your scripts from Writing Scripts Template scripts for simple fun
22. band combinations Features Vegetation and visible bands AIOH minerals advanced argillic alteration Clay amphibole laterite Gossan alteration host rock Gossan alteration host rock Decorellation envi Silica carbonate basic degree index Silica carbonate Silica Discrimination for mapping Discrimination in sulphide rich areas Discrimination Discrimination Silica Fe Enhanced structural features Comments by Hewson Red 3 3 2 or NDVI 5 6 phen 5x7 6 clay 4 2 goss 6 goss 13 11x11 10 12 silica 11x11 10x12 11 10 4 1 12 4 7 4 7 14 12 7 Equivalent to Landsat RGB 432 Alunite pyrophyllite mica kaolinite dickite Back to contents Green 2 7 6 musc 6 8 amph 4 5 alt 2 alt 12 13 14 carb 13 14 11 12 3 1 4 1 4 3 1 2 5 3 4 Blue 1 7 5 kaol 4 5 lat 5 6 host 1 host 10 12 13 basic 12 13 13 10 12 14 2 3 x 4 3 2 1 MNF Band 1 Reference Hewson CSIRO Bierwith Volesky Bierwith Bierwith Nimoyima CSIRO Abdelsalam Sultan Abrams USGS Rowan USGS Rowan USGS 10 Changing Format of PIMA Spectra Using SPECWIN PIMA spectra can be imported into ENVI for comparison with image spectra and groundtruthing However PIMA spectra must be in the correct format PIMA spectra must be imported as a text file and not as a dsp or fos file as produced by PIMA softw
23. ch it is accurately registered relative to the ground Because it has a resolution of 12 5m it is accurate enough to be used as a basis for registering other types of remotely sensed data such as ASTER The visible bands having pixels closest in size to the Landsat bands will be most obviously affected by displacement and will need the largest block shift The SWIR bands having pixels twice as large will be affected but only half as much as the VNIR bands and the TIR bands with pixels 6 times the size of the VNIR bands must be adjusted by 1 6 of the shift experienced by the VNIR which means they rarely need to be shifted Normally the displacement between the Landsat image and the VNIR ASTER image will be between O to 10 pixels E W and or N S 1 Open a new algorithm and image window 2 Change the colour mode to red green blue and delete the blue layer 3 Open Band 3 of the VNIR ASTER image into the red layer only and adjust the transforms or use the shortcut Refresh image with 99 clip button 4 Open the Landsat image O Mount_ Isa Working ETM pan mosaic DN ers or equivalent reference image into the green layer only and adjust the transform 5 With the two layers displayed together zoom in and pan around the image and identify areas with misaligned red and green pixels These are areas that show how much the ASTER image is displaced from the Landsat image Good areas to look at are roads airstrips and road intersections bad a
24. ctions as well as for wizards can be found in the Template subdirectory of the Batch directory A list of commands you can use in your code is in the back of the user manual or tutorial manual or in the online help More complicated functions must be written using these predefined simple functions One particularly important thing to remember when writing scripts is to include comments so that you or someone else will be able to understand what your script does how it does it and why you wrote it a certain way 2d Unfortunately many of the standard ER Mapper scripts are not commented very well and so you have to discover the functionality of some scripts through trial and error A few simple rules e Variables are denoted by a dollar sign in front of the variable name e g filename e Variables are assigned values using the sign e g number_of_files 6 note the equivalence test is represented by the double equals sign e Strings must be in double quotes e Comments are preceded by a hash e f condition then goto else goto is a useful construct Sample script Summary Takes vnir bands from an input hdf file and produces a pseudocolour algorithm with those bands only include lib BE Startup erb this script contains all the necessary startup info These are all variable definitions look for how they are used in the script Sstart Processing your HDF file please wait Sfinish Processing finishe
25. d Loading algorithm into new window Serror Error no input image Please open a HDF file in a new window then try again Ssaved Your algorithm has been saved Sextension VNIR alg if current window then goto make algorithm else goto try again if a window exists with an image then continue else print an error message make algorithm name of the routine brintln Sstart prints a line with the contents of the variable on it copy algorithm from window gets the dataset from the image window Shdfname get layer dataset assign the dataset to a variable new algorithm create a new algorithm for the VNIR bands set algorithm mode to pseudo set mode set layer dataset to Shdfname set layer description to Bandi first layer will be called bandl set layer input 1 to band 1 assing band 1 of dataset to layer 1 of algorithm duplicate layer copy the layer set layer description to Band2 assign band 2 to layer 2 and name the set layer input 1 to band 2 layer duplicate layer repeat the process set layer description to Band3 set layer input 1 to band 3 println Srfinish printing lines is a useful debugging technique go algorithm run the algorithm new window create a new window copy algorithm to window go window display the algorithm created Sstring Shdfname etilepath split Sstring at get the name of the hdf file without the Shdfalg S filepath 1 Sextension hdf ending and assign the
26. dow Back to contents gl Output Spectral Library Spectral Library Header Information 2 Plot Range tel 25 Ais Title wavelength Y Axis Title Value Reflectance Scale Factor fi Ur Wavelength Units Micrometers Input to Output Data Scaling Scale Factor OO Y Scale Factorf1 00 Output Result to Fie Memory Enter Output Filename Choose M APIMA Saw analysis files vunzVAleks test library DK Cancel 29 12 Using ENVI s Spectral Analyst to Determine Mineralogy Ground truthing is an integral part of remote sensing PIMA spectra obtained in the field or from field samples is a good way to ground truth ASTER or hyperspectral imagery First the PIMA spectra must be identified with a mineral or combination of minerals and then compared to the ratio results for that mineral in the image There are several programs capable of identifying PIMA spectra One of these is TSG The Spectral Geologist which is a very useful program Another method is to use ENVI s spectral analyst and is described below 1 Start Spectral Library Viewer from the Spectral menu and open your spectral library e g of PIMA spectra in a har file or sli file 2 Click on one of the spectra to display it 3 Start Spectral Analyst from the Spectral menu In the dialog box select the spectral library you want to use to compare to your spectra e g the USGS library and click 4 You can cho
27. ducing information loss Each ASTER HDF dataset contains scaling values unit conversion factors UCF which can be applied using the ER Mapper formula tool and the formula Input 1 x unit conversion factor To retrieve the UCF it is necessary to first download the ASTER Data Opener a tool which allows you to see the dataset s metadata 1 Download the ASTEH Data Opener from the website http www ads aster ersdac or ip dds www2002 service e u tools e set u tool ecro ss html 2 Start the data opener the executable In the dialog box click the Ref button to choose a dataset you must set file type to all files to see HDF format You will see some information about the scene as shown below ASTER Data Opener Short Name 457 L768 T Granule ID amp STLTB 01 03 01 09 0010269001 jJ ABO ASN FOU R Click REF button and specity the dataset eoe eraan E Detall button will display the detail information of the dataset Details gt Cancel Help 3 Click the Details button to obtain a more complete version of the metadata About halfway down the page you will see Unit Conversion Coefficients listed for each band The scaling factor you will use is the first positive number for each band 13 Details Quadrant Cloud Coverage 0 0 0 0 Unit Conversion Coefficients VNIHIT Incl Offset 0 676000 0 676000 VNIH Incl Offset 0 708000 0 708000 VNIR3H Incl Offset
28. ecause the pixel size is 30m i e twice that of the VNIR pixels You can also shift the TIR image by 1 pixel to the east Back to contents 20 8 Tips Occasionally after rotating your dataset back to zero there is still a tiny rotation angle in the metadata of the dataset like 0 0000001 This isn t a problem until you want to use the dataset in other software packages such as ENVI when the rotation angle prevents the software from reading the projection information correctly To fix this problem go to File Open gt Info Edit Coord Space Type 0 in the Rotation field This will get rid of any tiny fractions of a rotation angle that might be there It will not affect your dataset Make sure you save changes It is a good idea to make sure the pixel size of your dataset is an integer value i e 15m not 14 9999999m To fix the pixel size if it is not an integer value go to File gt Open gt Info Edit Raster Info Cell Size and adjust the cell size You may have to adjust the pixel size to be an integer when saving a dataset in the save dialog box When you create datasets in ER Mapper the Null value is automatically set to 0 If you import from some other programs such as ENVI the Null value may not be set it generally says none It can be very important to have the null value set properly to O especially when doing calculations with the data To set the null value to 0 go to File gt Open I
29. ffect of atmosphere 1 2 Load your radiance corrected dataset from the previous section into a new algorithm window Again assign each band to a different layer and rename the layers according to the original bands of the dataset On the main toolbar navigate to Process Calculate statistics In the dialog box select the dataset you want to calculate statistics on the one you ve just loaded into the algorithm window and set Subsampling Interval to 1 Just to be safe you can check the Force recalculate statistics box Press OK Calculate Statistics E I 3 CN rj x Subsampling interval ME Lancel Force recalculate stats Status Help Once ER Mapper has finished calculating statistics you can close the statistics windows or view the statistics and determine the minimum value for each band in the dataset select the first band in the algorithm and open the formula editor Type in the formula I1 RMIN H1 11 RMIN gives the minimum value for a particular band H1 specifies the region of interest in this case the whole scene and 7 specifies the input band Do this for each band 16 Formula Editor E E x Principal Components Patios Standard Seismic Description Default Formula 00 Close Apply changes File IMPLITT AMIN ADIT Edit i Comments Jt nputs Regions Datasets Variables INPUT 1 61 61 Tip
30. for layer 2 and repeat for the other layers up to band 14 Rename the layers Save the dataset as an ER Mapper raster dataset ers This dataset should be saved as 16 bit unsigned integer with 90m pixels Ensure output transforms are deleted Method 2 Using HDF Import Wizard The HDF Import Wizard allows you to convert ASTER HDF data to native ER Mapper format This tool allows you to import the dataset at different spatial resolutions for example importing VNIR data at 30m instead of 15m and combining bands with different spatial resolutions Note You can also do this manually using the algorithm window 1 You can start the HDF Import Wizard from either the Wizards or Batch Processing toolbar to add a toolbar to the main menu go to Toolbars tick Wizards or Batch Processing Click the button The HDF Import Wizard appears a HDF Import Wizard Welcome X This wizard supports the follaying HDF 4 products Aster Landsat 7 EThl Spot vegetation Modis EOSDIS Refer to the online documentation ta see which variants of these products are supported vvaould like to f Import one file C Import multiple files Back Mest Cancel 2 Select whether you want to import one or multiple files and click Next 3 On the next panel select your raw crosstalk corrected ASTER HDF input file and tick the box next to Produce ers raster image Type in a name for your output dataset and click Next
31. he band 4 filter cross talk occurs The basic problem is that the solar output in band 4 is considerably higher than the other SWIR bands Hence even a small number of band 4 photons leaking out can have a big effect in the other bands The effect is largest in bands 5 and 9 because those detectors are physically the closest to the band 4 detectors The correction at this point is assumed to be an offset based on the pixels location in the scene Essentially a Gaussian distribution is drawn around the pixel of interest in band 9 for example The band 4 scene is then examined to determine the radiance of each pixel within the Gaussian and then the contribution due to cross talk from each of these pixels is determined by the radiance of the pixel and the Gaussian value acting as weighting function Rob Hewson MMITG Exploration and Mining CSIRO 22nd ASTER Science Meeting http www cossa csiro au reports hewson 22aster htm 1 There is a handy tool that automatically corrects your scene for crosstalk Download and install the ERSDAC Crosstalk 3 tool from http www gds aster ersdac or jp gds www2002 service e u tools e set u tool ecro ss html You will need a zip file extractor that can handle Japanese versions e g Power Archiver 2001 or later 2 The tool comes with instructions in PDF but you may have to download the Japanese Language Package for Acrobat Reader from the Adobe site if the document isn t opening properly 3 Na
32. ible datasets such as geology and structural maps geochemistry PIMA analyses ground truthing radiometrics and any other available data should be used in conjunction with ASTER for best results The processing steps described in the first part of this manual are relevant only to ASTER level 1B scenes Level 1A scenes in a less processed form must be imported using image processing software such as Rastus li Useful References For tutorials on remote sensing and image processing e Canada Centre for Remote Sensing tutorial htto www ccrs nrcan gc ca ccrs learn tutorials fundan fundam_e html e NASA tutorial htto rst gsfc nasa gov e List of online tutorial sites http www geography eku edu Geo855 links htm e ENVI hyperspectral analysis tutorial http www ltid inpe br tutorial tut8 htm For more general information on ASTER e ERSDAC Hhttp www ersdac or jp e NASA TERRA website htto terra nasa gov e NASA ASTER website htip asterweb jpl nasa gov e CSIRO http www syd dem csiro au research MMTG Exploration AS TER ASTER htm Publications on ASTER and relevant authors e NASA reference list http asterweb jpl nasa gov publications aster biblio journals pdf e Hewson R CSIRO e Rowan L USGS Abrams Mars 1 Obtaining ASTER scenes 1 Identify and define the area you want ASTER scenes for either as a box or a point of interest in Lat Long 2 Goto the ACRES Digital Catalogue website hitp acs auslig gov au
33. nd 1 all If your values are around 2000 4000 6000 then the y scale factor is probably around 10 000 i e values have been multiplied by 10 000 27 3 The Spectral Library Builder window appears From the mport menu select From ASCII File Another file chooser appeas Select the txt file you re working on and click Open Another Input Ascii File window appears looking similar to but not quite the same as the Input Ascii File window from step 1 i Spectral Library Builder E olx E MIS ea Fie Import Options Help Output Wavelength 601 bands Selected Endmember Spectra fo Columns 2 Hows 601 1 300 3448 1 302 3431 1 304 3423 1 306 3399 1 3068 3384 A Axis Lalumn 1 E Y Asis Column 2 Wavelength Units Micrometers Y Scale Factor 0000 DK Cancel Delete Spectrum This time set the paremeters to the following and click OK a Xaxis column 1 b Y axis column 2 c Wavelength units micrometers W Spectral Library Builder o d Y scale factor 10 000 Same as previous File Import Options Help Back in the Spectral Library Builder window the EE file you just imported appears in the list Repeat this step for all of your files Output wavelength 601 bands f Selected Endmember Spectra E 4 From the Options menu on the Spectral Library ESOS Builder choose Plot End Members you will see your spectra plotted together To remove the continuum i e hull quotient go
34. nfo Edit Raster Info Type 0 for Null cell value Back to contents 21 Commonly used ratios Reference Rowan CSIRO Rowan Bierwith Volesky CSIRO Feature Band or Ratio Comments Ferric iron Fe 2 1 Ferrous iron Fe 5 3 1 2 Laterite 4 5 Gossan 4 2 Ferrous silicates 5 4 Fe oxide Cu Au biot chl amph alteration Ferric oxides 4 3 Can be ambiguous CSIRO Carbonates Mafic Minerals Carbonate chlorite 7 9 8 epidote Epidote chlorite 6 9 7 8 Endoskarn amphibole Amphibole MgOH 6 9 8 Can be either MgOH or carbonate Amphibole 6 8 Dolomite 6 8 7 Carbonate 13 14 Exoskarn cal dolom Rowan CSIRO Hewson Bierwith Rowan USGS Bierwith Nimoyima CSIRO Silicates Sericite muscovite 5 7 6 illite smectite Phyllic alteration Rowan USGS Hewson CSIRO Alunite kaolinite 4 6 5 Rowan USGS pyrophyllite Phengitic 5 6 Hewson Muscovite 7 6 Hewson Kaolinite 7 5 Approximate only Hewson Clay 5x7 6 Bierwith Alteration 4 5 Volesky Host rock 5 6 Volesky Quartz rich rocks 14 12 Rowan Silica 11x11 10 12 Bierwith Basic degree index 12 13 Exoskarn gnt px Bierwith CSIRO gnt cpx epi chl SiO2 13 12 Same as 14 12 Palomera SiO 12 13 Nimoyima Siliceous rocks 11x11 10x12 Nimoyima Silica 11 10 CSIRO Silica 11 12 CSIRO Silica 13 10 CSIRO Vegetation 3 2 NDVI 3 2 3 2 Normalised difference vegetation index 22 Common ratio amp
35. olution of 90m The higher spectral resolution of ASTER compared to Landsat for example Fig 1 especially in the shortwave infrared region of the electromagnetic spectrum makes it possible to identify minerals and mineral groups such as clays carbonates silica iron oxides and other silicates An additional backward looking band in the VNIR makes it possible to construct digital elevation models from bands 3 and 3b ASTER swath width is 60km each scene is 60 x 60km which makes it useful for regional mapping Aster 15m Aster 30m Aster 90m VNIR V THERMAL Landsat bands TM 1 4 TM6 ASTER bands f 2 a 4 10 14 14d 17 20 23 26 6 9 12 WAVELENGTH IN MICRONS r e f j a c 1 a n c e Figure 1 Distribution of ASTER and Landsat channels with respect to the electromagnetic spectrum There are a few things to note when using ASTER imagery for regional mineralogical mapping Firstly cloud cover vegetation and atmospheric effects can severely mask or alter surface signals Secondly bands and band ratios do not indicate the occurrence of a mineral with absolute certainty or with any idea of quantity so ground truthing and setting appropriate thresholds is essential Thirdly every terrain is different so ratios which work in some areas for a particular mineral or assemblage may not show the same thing elsewhere As a result of these factors it is important not to look at ASTER images in isolation from other data If poss
36. ose which method you want to use for spectral mapping in the next dialog There are three choices Spectral Angle Mapper Spectral Feature Fitting and Binary Encoding You can also choose to use a combination of these In general the first two methods are recommended Here we will use Spectral Feature Fitting which is usually the best method to begin with so set the weighting to 1 for that method therefore O for all others and click OK Edit Identify Methods Weighting x Spectral Angle Mapper Weight 0 0000 Min 0 00000 Max 0 78540 Spectral Feature Fitting Weight 1 0000 Min 0 00000 Max 0 10000 Binary Encoding Weight 0 0000 Min 0 00000 Mas 1 00000 LIE Cancel 5 In the Spectral Analyst window click Apply to match your spectrum open in the library viewer window against those in the reference library Spectral Analyst won t work unless your spectrum is already displayed If more than one spectrum is displayed then you will be asked which is the one you want to match 6 You will see a list of possible minerals with ranking values the highest ones have the greatest probability of being correct To compare your spectrum directly with one of the matches click on say the first best matched mineral name in the Spectral Analyst window A new display window will pop up showing both the reference mineral spectrum and your spectrum you can show the plot key so that you know which is which It is
37. r green and B10 for blue Click OK In the Decorrelation Stretch Parameters dialog box choose Output Result to File and select a file to save to Press OK to begin the processing 6 When finished the three decorrelated bands appear at the top of the Available Bands List dialog box Assign the three bands to the same RGB layers as before ENVI has probably already done this for you and click OK to display the image Compare the colour and contrast in the resulting image below right with the original RGB 13 12 10 image below left a T TE ji a i s eum es X E crt BL a eh e E 1 EX ta cup TES WP ER 5 eos Ua a E H uu LE Er deri f LEM i EpL 1 E 7 je zi Back to Contents 36 17 Writing Scripts in ER Mapper One of the benefits of using ER Mapper is the ability to write your own batch scripts including wizards to automate some of your processing tasks particularly tasks that you do regularly and are mechanical or repetetive Batch scripts in ER Mapper are relatively easy to write and most of the time you can copy bits of code from other scripts that do part of what you want You can also easily add your own buttons to the toolbars to run your scripts more quickly All of the ER Mapper scripts are stored with the program in the Batch subfolder of the main ER Mapper 6 4 folder on your C drive Some are stored in further subfolders for example Aster library etc You can open the batch files er
38. ransforms to determine the inherent dimensionality of image data to segregate noise in the data and to reduce the computational requirements for subsequent processing The data space can be divided into two parts one part associated with large eigenvalues and coherent eigenimages and a complementary part with near unity eigenvalues and noise dominated images By using only the coherent portions the noise is separated from the data thus improving spectral processing results extract from ENVI help manual 1 Start ENVI 2 From the main toolbar go to the Spectral Menu MNF Rotation gt Forward MNF Estimate Noise Statistics From Data The MNF Transform Input File window appears 3 Goto Open File and select a raster file you want to work on The file information will appear in the window 4 Click OK on the window A new window Forward MNF Transform Parameters appears You don t have to choose output files for the statistics but you must choose an output file for the MNF image about to be created bottom most text field Also make the Select subset from eigenvalues box read yes The program will calculate statistics and perform the transform 5 When finished two windows appear showing you the amount of variation in each principal component the most in PC1 the least in PCn and the list of available bands The MNF bands are listed on the x axis and the amount of variation between bands is shown on the y axis As you can see
39. reas are water rivers lakes because water levels are prone to change and the images were almost certainly taken at different times and seasons Ignore clouds red Turn off the smoothing option to better see individual pixels 6 Zoom in on a feature where the red and green pixels are not aligned like a road below left As you can see the road that appears in the red image is offset to the left from the green Decide whether the feature is displaced to the east or west north or south relative to Landsat and by how many pixels zoom in to do this The feature will appear yellow when the two datasets are exactly aligned red green yellow below right Algorithm Not fet Saved 4 Algorithm Mot Yet Saved 18 7 In the algorithm window right click on the red layer containing the ASTER image and select Properties from the bottom of the list 8 Inthe Dataset Information dialog box click Edit In the Dataset Header Editor click Raster Info 10 In the Dataset Header Editor Raster Information box click Registration Point The Registration cell by default is 0 0 i e the top left cell in the dataset The Registration coordinates are the ground coordinates that the top left cell is assigned to It is possible to change the ground coordinates but much easier to pick a better registration cell Dataset Header Editor Registration E al x Registration Cell
40. rmula 0 Close Apply changes File INPUT 1 0 676 Edit zi Comments mo Bl Inputs Regions Datasets Variables IMPLITT 61 61 VNTR 0 52 0 60 15m x B1 61 VNIR 0 52 0 60 15m Tip In the algorithm window load the dataset into one layer Type in the formula in the formula editor Duplicate the layer choose appropriate bands for each layer and rename the layers as required Finally go to the formula editor for the duplicated layers and edit the UCF to correspond with the band in that layer This saves you typing out the formula many times 8 When finished save the image as a raster dataset This time save it as a 4 byte real image This is to preserve the original data integrity especially given radiance decreases with increasing wavelength and band number The pixel size remains 15 30 or 90m depending on the dataset Ensure the Delete Transform button is checked 9 Repeat the process for the SWIR and TIR rectified datasets Back to contents 15 6 Dark Pixel Correction Dark pixel correction is a simple method used to account for the effect of atmosphere on image radiance related to additive scattering contributions there are also multiplicative transmission effects which won t be corrected by this This is a statistical method whereby the minimum value for each dataset is subtracted from the data This minimum value is taken to represent approximate the e
41. rrelated output bands This is done by finding a new set of orthogonal axes that have their origin at the data mean and that are rotated so the data variance is maximized PC bands are linear combinations of the original spectral bands and are uncorrelated You can calculate the same number of output PC bands as input spectral bands The first PC band contains the largest percentage of data variance and the second PC band contains the second largest data variance and so on The last PC bands appear noisy because they contain very little variance much of which is due to noise in the original spectral data Principal Component bands produce more colorful color composite images than spectral color composite images because the data is uncorrelated ENVI can complete forward and inverse PC rotations Richards J A 1999 Remote Sensing Digital Image Analysis An Introduction Springer Verlag Berlin Germany p 240 extract from ENVI help manual 1 Start ENVI 2 From the main toolbar go to the Transform Menu Principal Components gt Forward PC Rotation Compute New Statistics and Rotate The Principal Components Input File window appears 3 Go to Open File and select a raster file you want to work on The file information will appear in the window 4 Click OK on the window A new window Forward PC Parameters appears You don t have to choose output files for the statistics but you must choose an output file for the PC image abo
42. rrelation stretch essentially stretched each band such that the minimum correlation between bands is shown and therefore the decorrelation i e areas of the spectrum where the bands are not correlated are highlighted It is another way to reduce redundancy in the image Use Decorrelation Stretch to remove the high correlation commonly found in multispectral datasets and to produce a more colorful color composite image The highly correlated data sets often produce quite bland color images Decorrelation stretching requires three bands for input These bands should be stretched byte data or may be selected from an open color display Similar results to decorrelation can be obtained by using a sequence of forward Principal Components PC contrast stretching and inverse PC transforms extract from ENVI help Decorrelation stretch can be done in ENVI or in ER Mapper although if using the function in ERMapper it is necessary to have C compiler installed Without the compiler it is necessary to perform the function in ENVI as described below 1 Start ENVI 2 Open the image file you want to use in this process TIR datasets are usually the best by going to the File Open Image File select your TIR file The Available Bands List dialog opens 3 Go to the Transform menu and choose Decorrelation Stretch Another band chooser the Decorrelation Stretch Input Input Bands dialog box appears Select three bands e g B13 for red B12 fo
43. s useful both for comparing the validity of ASTER signals and groundtruthing as well as for seeing which features of the spectrum are distinctive for that mineral In this way you can see which ASTER bands combinations or ratios are likely to produce the best results in terms of correctly identifying and mapping the minerals of interest 1 Start ENVI From the Spectral menu on the main toolbar select Spectral Libraries gt Spectral Library Builder From the pop up box select Ascii file and click OK A file chooser appears From the file chooser select your ascii txt file one at a time for this process The Input ASCII File dialog box appears i Input ASCII File E x Input File M SPIBA Saw analysis Filessrunz 14050 a Columns 2 Rows BUT 1 308 3384 Wavelength Column fi E FWHM Column 2 Wavelength Unit Micrometers Y Scale Factor 0000 LK Cancel 2 Inthe Input ASCII File box set the parameters to the following and click OK a a9 Wavelength Column ENVI is asking you which column of your text file represents the wavelength normally should be 1 Leave the FWHM text space blank Change Wavelength units from unknown to Micrometres The Y scale factor is the amount that the reflectance in your spectrum has been multiplied by so have a look at the spectrum in SpecWin to find out what kind of values you re getting for reflectance In reality the reflectance value is between 0 none a
44. stom cell size box the wizard will automatically choose the cell size from the metadata Click Next HDF Import Wizard Output cell attributes Cell Attributes jw Custom cell size Custom cell size amp meters 5 Custom cell size Y meters i3 Resampling method Cubic x Back Next Cancel 6 The next panel is where you choose the bands you want to include in the final raster image You can either enter the band numbers or select them from the list click the button on the right Click Next HDF Import Wizard Band selection Product Aster LeveliB Which bands would you like to use Please see the batch status window for band dimensions 11 18 cS Enter a list in the form 1 3 5 7 Or press the band chooser button to make your selection z Back Next Cancel 7 The final panel and a batch status window appear Check the batch status window to see what is being done to the image Click Finish when the process has finished You can now go to Step 5 Radiance Calibration if you rotated your image to true north or go on to Step 4 Image Rectification if you haven t rotated your image yet HDF Import Wizard Complete EL EL Import completed successfully See batch status window for resultz HDF Import Wizard HOF Import started Beginning rotation Rotating 73 04 degrees counter clackwise Input file Wacres project 1_rasteraster_oriail HOF Import
45. to Plot_Function Continuum Removed or Normal as you prefer You can also change the plot parameters to block out part of the spectrum For example if you wanted to see only the 1 8 to 2 5 region of the spectrum go to Edit Plot Parameters A new window opens with a lot of options In the Range text fields about halfway down change Delete Spectrum the min and max values as you like You can also stack plots etc to compare them 28 ai Endmember Spectra Fie Edit Options Plot Function Help 5 Save your spectral library From the File menu select Save Plot As Spectral Library The Output Plots to Spectral Library dialog box appears Click the Select All Items button and click OK The Outout Spectral Library window appears Leave all the parameters as they are see right The only thing to do here is to select the file you want to save to at the bottom of the window Make sure the Outout Results to File is checked and click Choose to select the directory and filename you wish to save to Click OK to finish Close the next dialog box that appears 6 You can view your or any other spectral libraries by going to the Main menu main toolbar Spectral gt Spectral Libraries Spectral Library Viewer In the chooser that appears select which library you want and press OK In the smaller chooser click on a spectrum to display Each spectrum that you click will be displayed in the same win
46. um 584 Map Projection SUTMS Rotation 7 7370 degrees counterclockwise Data Value Type Unsigned 8 Bit Integer Mull Cell value O Number af Bands 3 Number of Lines 4600 Number of Cells per Line 4980 Cell Size 15 meters Cell Size 15 meters File Size Bar 4000 bytes E dit Close 5 From the Process menu on the main toolbar open the Geocoding Wizard The geocoding dialog box opens with several tabs see below 6 Click on the first tab Start if it isn t already selected Select an nput file and set the Geocoding Type to Rotation 7 Click on the second tab Rotation Setup Here you will need the rotation angle you noted earlier Type the rotation angle into the text box but multiply it by 1 i e if you originally had a positive rotation angle now it will be negative and vice versa This is to make sure the image Is rotated in the correct direction 8 Click on the final Rectify tab Select a meaningful output filename and pixel size by default the pixel size should already be set to be the same as your input dataset Cubic Convolution is the recommended Resampling method 11 Geocoding Wizard Step 3 of 3 1 Start 2 Rotation Setup 3 Rectity Output Info File project raster rectifiedimagel mtgordan s amp 5T LIB VNIR_ 5254 rect ers z E Cim Sie 83 15 MB e a Lines 5231 tae Compression Aati 20 Celle 5556 Geol lFFATIFF Ew Compress Edit E stents Cell Attributes Cell si
47. ut to be created bottom most text field Also make the Select subset from eigenvalues box read yes The program will calculate statistics and perform the transform A small dialog box showing you the percentage variation in each band appears midway through the process click OK and keep going 5 When finished two windows appear showing you the amount of variation in each principal component in one the most in PC1 the least in PCn and the list of available bands in the other The PC bands are listed on the x axis and the amount of variation between bands is shown on the y axis As you can see the most variation nearly all in fact is recorded in PC band1 A smaller amount is recorded in B2 then 3 4 and so on until the line becomes just about flat The last PC band will look very speckled and will be mainly noise 6 In the Available Bands List window select RGB color and then choose MNF bands 1 2 3 for R G B respectively or any other combination you like although this one will probably be the most useful as it shows the greatest amount of variation Click Load RGB to view the image you can also view each band in greyscale Three image windows appear They are all geolinked The main window is the mage window from which you can control image enhancement etc The Scroll window allows you to view the entire image and select a part of it to view in the mage window by moving the red box The Zoom window allows you to zoom in on areas
48. vigate to Start menu Programs Crosstalk3 Data IO Setup The dialog box below opens 4 On the left of the dialog box select your uncorrected input image s by clicking on the LJ button to the text field Only HDF or DAT file formats are accepted A corresponding output file name will appear on the right it is the same name but with chg appended to the name You can process up to 10 images at a time 5 Goto File Start Process to correct the images Close the dialog when finished Data I Setup File Input Outpul 8E DN EO BERE 8B DUM o 0 o 04 8E JI O l Back to contents 3 Importing Images Into ER Mapper A raw ASTER dataset contains all 14 bands However ASTER data consists of three types of datasets each with a different spatial resolution so each must be treated independently The three datasets are VNIH Visible and Near Infrared bands 1 3 SWIR Short Wave Infrared bands 4 9 and T R Thermal Infrared bands 10 14 They have spatial resolutions of 15 30 and 90m respectively Two ways of importing ASTER datasets into ER Mapper are described below The first method describes how to manually import the data while the second makes use of the HDF Import Wizard It is worthwhile going through the process manually at least once so that you know what is being done to the data every step of the Way Method 1 Manually importing the dataset A
49. ze x 15 Meters Cell size Y 15 vw Mull cell value o Resampling Cubic Convolution x Default Cell Size W Display rectified image Save File and Start Rectification Save Close Cancel 9 Click the Save File and Start Rectification button 10 Repeat the process for the SWIH and TIR datasets the rotation angle will be the same as your datasets came from one original dataset NB This process is not necessary if your rotation angle is originally 0 This happens for example when you ve processed the image from Level 1A to Level 1B using Rastus and ENVI Tip Occasionally after rotating your dataset back to zero there is still a tiny rotation angle in the metadata of the dataset which you can t see e g 0 0000001 This isn t a problem until you want to use the dataset in other software packages such as ENVI when the rotation angle prevents the software from reading the projection information correctly To fix this problem go to File Open Info Edit Coord Space Type 0 in the Rotation field even if it seems to say 0 already This will get rid of any tiny fractions of a rotation angle that might be there It will not affect your dataset Make sure you save changes Back to contents 12 5 Radiance Calibration Radiance calibration is a process of rescaling the digital values to observed top of atmosphere radiance values Scaling the sensor signal to 8 bit data is important for re
Download Pdf Manuals
Related Search