slcOLI_20140107-15m

January 07th 2014
15 m resampled resolution

Ground truth

Regression January 7th 2014 vs Sonar Depths RMSE=1.76 m	Sonar Two Days seatruth depths raster not corrected for tide 15 m GSD see depth legend
Regression January 7th 2014 vs DTM	DTM from U. of La Paz, Mexico resampled to 15 m GSD see depth legend
	ZDTM+0.5m - Z4SM DTM - January 7th 2014 see legend

GREEN solution or PAN solution?
15m resampling or not?
15 m PAN-sharpening or not?
Smoothing or not?
One more trick: apply ZDTM

15m GSD PAN sharpened by 4SM
Dec 7th 2016:
this was a gross mis-understanding
of the Brovey magic formula!
but nonetheless: it worked fine!

GRASS tutorial: with a Brovey pan sharpening,
each of the 3 lower resolution bands and panchromatic band
are combined using the following algorithm
to calculate 3 new bands at the higher resolution (example for band 1):

    band1

new band1 = --------------------------------- * panband

  band1 + band2 + band3

One oldband1 30 m GSD pixel is split into four 15 m GSD newband1 pixels:
Final touch requires to return pansharpened bands to original scaling of Landsat 8 data.
I achieve that in 4SM, as follows:
newband1=newband1*oldband1/average(four newband1)
This means that I can calibrate
any pansharpened radiance into reflectance (0-1)

New SAM in 4SM

previous version only mapped GREENish spectral angle bottom signatures
- in the range type10 to type30: shades of green
- "PURPLEish" bottom signatures did not pass the test
  - they were mapped a type10, which is brightest bottom type
from now on, purple signatures are mapped
- in the range type30 to type 50: shades of purple

Green Coastal_1 water
This image offers an opportunity for calibration of a Coastal water type
Seems that this water has a disctintly green colour
-Lw/5.0/10.0/3.5/3.0/0/0/0

Now I want to

process all SanLorenzoChannel images at 15 m GSD
- using 4SM pansharpened data
redo all SAM mapping for
- SanLorenzoChannel
- Caicos Bank time series
- LeeStockingIsland time series

Data and Deglinting

TOA TCC: raw image logarithmic enhancement	BOA TCC deglinted image logarithmic enhancement
Co-registration 30 to 15 m resampling of MULTI bands no pan-sharpening Image shows SWIR1 band over open waters it has been resampled from 30 m GSDto 15 m GSD by splitting one pixel into 4 identical pixels no pan-sharpening has been applied Red vector shows which 15m GSD panchro pixels have high glint signal So good co-registration has been achieved this required offset by one PAN pixel in both row and line Maybe deglinting a pan-sharpened image is a bad idea, as it is bound to produce a very noisy deglinted image. Or should the sharpening be applied on deglinted images?	Two distinct water bodies Bay of LaPaz..........vs.......LaPaz Basin WEST: BayOfLaPaz: hardly any seasurface glint deep water radiances are higher in the blue-green range CENTER: crosses the SanLorenzoChannel EAST: LaPazBasin: a lot of seasurface glint deep water radiances are lower in the blue-green range
Sea surface glint glint is fairly strong over the LaPaz Basin	Sea surface glint deglinting by SWIR1 is fairly good, as shown by R2 values deglinting by NIR exhibit lower R2 values deglinting of the pansharpened image reveals that co-registration is good 4SM Brovey pansharpening did not damage the radiometric quality of the original data deglinting shall be quite noisy (is this because of pansharpening?
Glint regressions using SWIR1 No pan-sharpening applied R2 values are fairly high 15 m resampling does not increase noise	Glint regressions using SWIR1 Pan-sharpening applied R2 values are low 15 m pan-sharpening increases noise

Optical calibration for the whole image
16U data are scaled to allow for comfortable screen display

Calibration diagram for the whole image for bands Blue, Green, Red and NIR	Calibration diagram for the whole image for bands Blue, PAN, Red, NIR CoefKPan=1.05
Coastal waters 0-5 m KB_BLUE/K_RED=0.33 KB_GREEN/K_RED=0.36 K_BLUE =0.245 m^-1 K_GREEN=0.268 m^-1 K_RED =0.744 m^-1 KB_BLUE/K_GREEN=0.91 this is evidenced here This is Coastal 1 water type of Jerlov Blue BPL pixels are located at the beach SOIL LINE is represented by small white dots it runs from the LsM point all the way to a black body point its shape offers a way for us to estimate the water volume reflectance, and therefore also the atmospheric path radiance this assumes Lsw=La+Lw it also assumes that Lw_RED~=0	Deeper waters are clearer KB_BLUE/K_GREEN=0.737 K_BLUE=0.163 m^-1 K_GREEN=0.221 m^-1 This is Oceanic OII+0.4 water type of Jerlov This stratifification of water clarity is not big deal is observed in all three images I worked on so far was the cause of "saturation" in my preliminary results may be confirmed by visual observation, maybe by underwater photos, maybe also using Secchi disk (horizontal sighting??)
Calibration diagrams are just as good for a 15m GSD pansharpened image as it is for original 30 m GSD data 0-5m: K_BLUE/K_GREEN=0.95 Jerlov water type Coastal_1 5-30m: clearing progressively to OII+0.3	Greensish Coastal_1 water Thanks to abundant coverage of low_altitude mountainous desertic dryland with many very dark shaded areas, the following can be estimated with reasonable confidence: atmospheric path radiances water volume reflectances The result hints at a fairly low water volume reflectance in the COASTAL band, a fairly high water volume reflectance in the GREEN and PAN bands This is a remarquable result, it is consistent with Coastal water type in the 0-5 m depth range this bodes well as we wish to ascertain water column correction in view of SAM botttom typing Failing to detect and account for that entails frustation of the practioner
"Stratified waters" The central channel exhibits clearer waters	"Stratified waters" Profile Blue location backdrop is a BOA TCC WCC The RED and NIR bands exhibit higher deep water radiance where Coastal water type rules: this is suspended particles load North: from water line to WP2 South: from WP3 to water line