Module 8: Thermal Infrared

This week in Photo interpretation we learned about thermal energy.  Thermal energy is heat emitted from objects.  Thermal energy waves are much larger than the waves we have previously discussed.  Due to the size of the waves there is very little scattering, but the range of measurable waves is limited by the atmosphere, by elements like water.  Stefan-Bolzmann law states radiation increases with temperature. 

In lab this week we worked between ArcMap (my ArcPro was not cooperating) and ERDAS.  We learned to create composite multispectral images in both ERDAS with layer stack and ArcMap with the composite band tool.

The map deliverable shows the difference in imagery displaying different bands in different colors.  I chose to look for three features recognizable by me: Interstate 10, Fairhope Pier, and the Grand Hotel.  Fairhope Pier is really only discernible in the True Color display and then only when zoomed very close.  The interstate gets lost under what I think are clouds in the Mobile Bay Estuary, but at least a part can be seen in the thermal layer (I think).  The False Color shows clearly the areas of high vegetation in dark red wich are also the lighter areas on the Thermal display as those are cooler than the urban areas.  The Grand Hotel grounds showed up very well in the False Color.

Multi Spectral Analysis

This week in lab we gain more information about spectral bands, band ratios, spectral properties of vegetation.  We explored some vegetation indices: NDVI, SAVI and EVI.  And we discussed spectral enhancements in the form of Tasselled cap and Principle Components Analysis.

In lab we continue to utilize ERDAS to explore Image Histograms.  We gained experience operating the inquire cursor, interpret histogram data, and identifying features by interpreting digital data.

I must admit that I am unsure of my results this week.  I worked through the lab instructions and made it to the deliverable assignment and read it and thought I do not know how to do that!  But I kept playing around in ERDAS.  I examined the histogram, and looked at the image in gray scale and as multispectral changing the band combination.  I looked at the histogram again, still not sure what I am supposed to be getting.  Then I remembered the histogram X axis is the brightness and the Y axis the frequency of that brightness.So then I had some clues directing to bright objects or dark objects and how frequent.  Then in grey scale I looked for changes to the imagery in different bands.  And I repeated that some with the multispectral and adjusted the bands (not so much time here because I could keep trying different combinations for days).  Then I utilized the Inquire Cursor to see if I had put the clues together in an area the meet the pixel values provided.  I could be totally wrong on this one.  But I tried to follow the clues as best I could and I came up with answers, and SOME COOL (may be correct) MAPS.

Module 6: Image Enhancement

This week we covered Radiometric Correction or Enhancements to account for effects of sensor-detector-and platform, atmospheric and illumination effects, and terrain effects.  We also looked at Spatial Enhancements with Pan-Sharpening (merging a panchromatic image at high resolution with an image at lower resolution) and spatial filters.  We were presented with:  types of radiometric effects that can impact remotely sensed data, differences between absolute and relative atmospheric correction, pan sharpening, convolution filter (high and low pass filters), and Fourier transform.

This week in lab we walked through the steps of downloading and importing satellite imagery from https://glovis.usgs.gov/  (which wasn't loading properly at the time), performed spatial enhancements in ArcMap and ERDAS and utilized Fourier Transform function.  The goal of the above image was to restrict the striping impact of the image while keeping the detail of the image.  I don't think mine is a very good example.  This was much more difficult and felt more of an art than a science.  The lab instructions included several enhancement techniques, a wedge mask, a low pass filter and then a sharpening.  From there the direction was our own.  I applied another low pass filter of 5X5 in addition to the 3X3 we used earlier and then sharpened again.  The second sharpening did not seem to enhance as much as the earlier.  And although the additional low pass toned down the striping I feel I lost significant detail in the process.  Previous to this exercise I would have though that image correction would involve specific calculations and then transformations to correct.  This was not my experience with this lab.  It was more of trial and error.  Maybe this changes with more experience or maybe the experiences shape the decisions of how to correct.