A time series of Landsat 8 images
at San Lorenzo Channel, Baja California


LANDSAT 8 OLIP 
 
Using the Panchromatic band for water column correction
to derive water depth and spectral bottom signature:

Landsat 8 OLIP bandset used for this work

Purple=1Blue=2Green=3PAN=4Red=5NIR=6 and SWIR1=7
Collaboration with 
Fabio Favoretto, Ph.D Student, Coralline Algae Ecology
Grupo Interdisciplinario de Ciencia Ambiental, Universidad Autonoma de Baja California Sur
Carretera al sur km 5.5  | La Paz
favorettofabio@gmail.com
Using pan sharpened images in this study
Pan sharpening  using Rstudio with Brovey method

work done october-november 2016
Procedure/flowchart for operating  4SM.7.00

home
 
 

visit Combining Depths in the Bahamas out of 14 instances

Combining nine 4SM Depths at SLC
No smoothing at all.
For each pixel, first I compute an averaged depth (N<=9).
Then I exclude depths outside of +-standard deviation,

and compute a new averaged depth with a condition on N.
N>=4 out of 9 depths yields clean DTM.

N>=1/9
all sorts of outliers produce fancy pixels
N>=2/9
N>=3/9

N>=4/9
clean DTM, even in Bay of La Paz
 
 
Fabio's Sonar DTM                  and       4SM Combined Depth
Fabio's sonar DTM 15 m GSD is very crude:
  • note the depth contour lines abutting the shoreline
  • no tide correction
  • Fabio's DTM is most useful, but needs to be refined
Combined depth 15 m GSD is appealing
N>=4, no tide correction, no smoothing


 



 
Combining depths along Profile_Black


 
   
Standard deviation on combined depth

Standard deviation on combined depth
most pixels have STD<=0.5 m
Standard deviation on combined depth
most pixels have STD<=0.5 m

N on combined depth
most pixels have N=5-6 used instances

N on combined depth
most pixels have N=5-6 used instances


 



see legend for depth



Comments on Histograms and Regressions
" the regressions graphs ZC vs ZR (from my DTM) in each scene, the % of retrieved depths within 1.0 m is different from the one reported on the histogram, why? Feb 25th 2017"


October 19th 2013
Histogram:
  • accounts for all depth points: 0.18 million points with both Z4SM and ZDTM
  • your DTM lacks depth points in the 0-3 m depth range
  • result: within 1.0 m: 40.7% over 0.18 million points
Regression graph:
  • accounts for one in N depth points (N=1 where step=1; N=2 where step=2, etc)
    • should not significantly alter the statistics
  • plus RED outliers are excluded
    • depths are binned into decimeters ==> depth pairs which are poorly represented are excluded form the statistics (nbMIN=2)
    • this is intended to improve the statistics by excluding arguably bad points
  • result: within 1.0 m: 45.2% over 0.134 million points
 
 
 

Comments on Combined Depth
" if i understood it correctly, in the regresion graphs for the depth combined, the ZR are the mean combined values for each pixel (excluded the one with high standard deviation), i like this, but, i have a doubt... isn't it obvious that the correlation is better because all the eventual artifacts or bad retrieved depths create a model that correlates better with the retrieved depths from one of the images that compose the average?  Feb 25th 2017"

YES it is obvious because
  • your DTM is very crude and limited indeed! (although has been very useful, as it demonstrated I was getting the calibration correct as I expected)
  • my result on any one single image is bound to reflect the conditions (atmospheric, hydrological, blooms, wind, alien boats sailing the ROI, ...) at the time of imaging, which we both now know exhibit many weird and transient features
It would be much less obvious if your DTM was faultless, like LIDAR or MBES, as it would have shown undisputably and quantitatively how much things improve through the TimeSeries CombinedDepth final result.
 
 




Download from my GoogleDrive
slcOLI_cz.zip 63 MB
slcOLI_cz.zip 66 MB updated Nov 23rd 2016
Datum and Ellipsoid: WGS83   UTM zone 12

4SM depth in centimeters for each of 9 scenes, no smoothing, GSD 15m


Channel Descriptor    file="slcOLI_cz.pix";                  File header for 23 channels
 1 Z4SM_cm_slcOLI_20131019_15m/slcOLI_20131019.041 
 2 Z4SM_cm_slcOLI_20131104_15m/slcOLI_20131104.041
 3 Z4SM_cm_slcOLI_20140107_15m/slcOLI_20140107.041
 4 Z4SM_cm_slcOLI_20140208_15m/slcOLI_20140208.041
 5 Z4SM_cm_slcOLI_20141022_15m/slcOLI_20141022.041
 6 Z4SM_cm_slcOLI_20160129_15m/slcOLI_20160129.041
 7 Z4SM_cm_slcOLI_20160301_15m/slcOLI_20160301.041
 8 Z4SM_cm_slcOLI_20161011_15m/slcOLI_20161011.041
 9 Z4SM_cm_slcOLI_20161027_15m/slcOLI_20161027.041

10 DTM            Fabio's DTM 
11 void

12 NNNN_on_Combined_Z------N>=1
13 STDZ__on_Combined_Z_dm---N>=1
14 CZ_____on_Combined_Z_cm---N>=1

15 NNNN_on_Combined_Z------N>=2
16 STDZ__on_Combined_Z_dm---N>=2
17 CZ_____on_Combined_Z_cm---N>=2

18 NNNN_on_Combined_Z------N>=3
19 STDZ__on_Combined_Z_dm---N>=3
20 CZ_____on_Combined_Z_cm---N>=3

21 NNNN_on_Combined_Z------N>=4..............N...............on Combined Depth result for N>=4
22 STDZ__on_Combined_Z_dm---N>=4...........STD in dm..on Combined Depth result for N>=4
23 CZ_____on_Combined_Z_cm---N>=4............CZ...in cm...on Combined Depth result for N>=4

Plus miscellaneous items



go to Combined Depth vs Fabio's DTM
continued to SAM
go to Combined Depth vs Fabio's DTM

Enforcing Combined Depth



 



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