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ASTER Nine Band Multispectral Analysis

There are several data options for analysis of multispectral satellite imagery. One of the more useful is ASTER. ASTER stands for Advanced Space borne Thermal Emission and Reflection Radiometer. ASTER is one of the five sensors on-board Terra, a satellite launched in December 1999. It was built by a consortium of Japanese government, industry, and research groups. ASTER spatial resolution ranges from 90m for the five Thermal Infrared (TIR) bands, 30m for the six Short Wave Infrared (SWIR) bands to 15m for the four Very Near Infrared (VNIR) bands. The ASTER SWIR sensors failed in April 2008 so data from this sensor is no longer usable. Data from the VNIR and TIR sensors continues to be available.

ASTER data is offered free of charge for the continental USA and is also offered for a relatively modest charge (USD $80) for the rest of the world. Some of the ASTER features that make it especially interesting for multispectral analysis include:

  • VNIR band resolution of 15m

  • Global spatial coverage

  • Temporal coverage dating back to the launch date to the present

  • Nine usable bands of >30m resolution

In addition, all bands are in the IR spectrum. Since these frequencies are much less susceptible to absorption by atmospheric aerosols than the visible bands, correction to Top of Atmosphere Reflectance is usually sufficient as this data will not be too much different from rather Surface Reflectance in many cases.

If your area of interest is in the USA, you can download ASTER data for free from the USGS GLOVIS website and from the ASTER Data Pool. Links to both of these sites are available from the PANCROMA Data web page. For international scenes, visit the NASA Echo Reverb website.

ASTER data is archived in compressed HDF format. The first step in processing the data is to convert it from the native HDF to GeoTiff format. There are several tools available for this task. One of the easiest is the free MultiSpec application. Another possibility is the free HEG application. MultiSpec is able to import a variety of satellite image formats and has its own set of classification algorithms and is easy to install. The conversion itself can be a bit tricky. Contact me for detailed instructions if needed.

For this example, convert the six SWIR bands and the three VNIR bands. Note that there are actually four VNIR bands Band3 images are taken from two angles in order to create a stereo pair for DEM generation. Choose the 3N (Nadir) image.

After the bands are converted you will have to rationalize the image sizes by either resampling the VNIR images down or interpolating the SWIR images up. I recommend interpolating the SWIR images up so that there is no net data loss from the scene. To do this, open each SWIR band one at a time in PANCROMA™ and then select 'Pre Process' | 'Resize Images' | 'Double Landsat or ASTER Band'. When the processing is complete, save the band in GeoTiff format. Repeat for each SWIR band.

At the end of this part you should have nine ASTER bands: three VNIR bands 1, 2 and 3N and six up-interpolated SWIR bands 4, 5, 6, 7, 8 and 9. These nine bands can be processed using the Point Spectrum Generator and Spectral Analyzer in the same way that six or seven Landsat bands are processed.

To start this example, open the nine files as usual by selecting 'File' | 'Open', opening the bands in the order 1,2,3,4,5,6,7,8 and 9. We will first generate the point spectrum for a feature of interest. Select 'Spectral Analysis' | 'ASTER Point Spectrum Generator' | 'Nine 8-Bit DN Bands'. The nine bands will be read into memory and the Band Display Selection Form will appear. I set the radio button to band1.

There are some very distinct crop circles with almost zero reflectance in band1 that I chose for this example, shown in the image below.

[Target Image]

Note the two crop circles to the right of the image. Their reflectances are zero in VNIR band1


After clicking on several of them, I clicked 'OK'. The TOA Reflectance form will become visible. I set the calibration parameters from the ASTER metadata file. PANCROMA computed the point spectrum for my target. These crop circles have a very distinctive spectrum thanks to their high reflectivity in VNIR band3 and should be easy to segregate. (I chose this example on purpose to illustrate the possible benefits of including the VNIR bands. This is a simple segregation exercise if they are included and a more difficult one if they are not due to the unique reflectance of the target in VNIR band3.)

[Point Spectrum]

This is the Point Spectrum for the ASTER scene. Note the high reflectance of the target crop circles in VNIR band3.


I next selected 'Close Graphics Window and Reset'. I then re-opened my nine ASTER bands and selected Spectral Analysis' | 'ASTER Spectral Analyzer' | 'Nine 8-Bit DN Bands' | 'Euclidean Distance'. As usual, the Point Spectrum reflectance values have been automatically entered into the Spectral Criteria form for the Euclidean Distance analysis. I clicked OK and the TOA Reflectance form will again become visible. (You will have to enter the reflectance data again as it is not saved between runs.)

[Spectral Criteria Form]

This is the Spectral Criteria form with the average band reflectance values automatically populated from the Point Spectrum Generator.


After a while the Euclidean Distance plot was computed. A section of the plot is shown below. The target crop circles are shown in red, which indicates minimum Euclidean Distance. Of course all similar crop circles and vegetation in the image had small Euclidean distances and also appeared red in the countour plot.

[Euclidean Distance Plot]

Euclidean Distance contour plot. The crop circles are highlighted in red, indicating minimum Euclidean distance and best match with the spectrum.


Of all the free multispectral data sets, EO-1 is the most capable. However, the spatial coverage across the globe is very sparse, so the data set is not very useful. ASTER, with its high-resolution VNIR bands and multitude of IR sensors is a very powerful instrument indeed. It has proven a true workhorse for many applications of multispectral analysis. This example used a very distinct ground feature to illustrate PANCROMA™ multispectral analysis tools for ASTER. The same techniques can be used to explore more difficult segmentation problems. The nine VNIR and SWIR ASTER bands provide an excellent tool for this type of analysis.



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