Producing a CASI panchromatic band
Optical calibration of the Panchromatic band
Profiles Red, Yellow and Bue
Seatruth
Bottom type training sites
Bottom typing process in 4SM
Bottom typing result
home



 

page menu

PANchromatic band	NOT using the "PAN solution"
Producing a CASI panchromatic band Optical calibration of the Panchromatic band Profiles Red, Yellow and Bue	Seatruth Bottom type training sites Bottom typing process in 4SM Bottom typing result Command line

Producing a CASI panchromatic band

Panchro in an OLI or WV2 image The use of a Panchro band for OLI and WV2 imagery has already been presented this panchromatic band is badly affected by a lack of synchronicity with other bands this causes a high level of system noise, and badly affects the potential for deglinting please refer to my Panchro page

Panchro with an hyperspectral image By aggregating all bands of this hyperspectral image in the Green/Red/Nir wavelength range, I create a Panchromatic band, which ought to exhibit water optical properties similar real OLI or WV2 panchro bands. Naturally, this new band is strictly synchrone with all other bands unlike the Panchro bands of OLI and WV2 sensors which exhibit adverse properties caused by non-synchrone image acquisition I store it in place of the original band_16, as this band is not of much use because of likely in-water fluorescence, or so I suppose

Image bandset So my CASI bandset for this HYPHOON dataset is now as follows:

High S/N ratio This new panchromatic band has a fairly low level of system noise, much higher actually than that of OLI or WV2 sensors this shows in calibration diagram, and should allow for proper deglinting

Optical calibration of the Panchromatic band
Based on K_3=blue/K_7=green=0.62 observed in the image for WL_blue=478.9 nm and WL_green=547.1 nm,
we get the following operational diffuse attenuation coefficients 2K in m^-1

The PANCHRO band is band 16 Calibration diagram for Blue, Green, Red and PAN bands

The PANCHRO band is band 16 A specific routine has been written in order to derive the BPL curve for the Blue/PAN pair of bands for this hyperspectral image I shall not elaborate on how this is done other than by stating that in takes plain advantage of the simplified RTE As seen in the X3 vs X16 plot, the linearized BPL line model is distinctly a curve, which appears to be quite similar to the curve obtained when using the OLI or WV2 panchromatic band This BPL line model is obtained experimentally, subject to the particular waveband arrangement of the current hyperspectral image: see that this CASI bandset does not represent a continuous coverage of the visible range see that there is no real NIR bands This calibration is entirely based on this kind of plots, as it makes no use whatsoever of the "seatruth" dataset

Water type OIB+0.5 of Jerlov This entirely relies on precise wavelength  of narrow band_3 and band_7 ratio K3/K7=0.62 observed in the image data adjustment of 2K values for other bands in order to achieve a strict fit with observed linearized BPL pixels

Calibration diagram for bands 1, 8, 11 and 15 No need for field data The following demonstrates that this calibration does not need any field data, thanks to narrow hyperspectral wavebands

All results below involve smart-smoothing of the image data before modeling.
This, I think, explains why DTM depths are so noisy in comparison.

Profile RED	RED profile is "seatruth" depth retrieved by U. of Queensland a tide height of 0.30 m was added BLACK profile is 4SM retrieved depth
Not using the PAN band Not using the PAN band: all shallow pixels are modeled by band_j against all_seven_band_1_to_band_7 see that , as depth increases ,  band j shifts from band_15 (brown) to band_14 (orange) to band_13 (red) ... through to band_7 (green) see that , deeper than ~17 m, "seatruth" depths are extremely noisy and confined to ~18 m: this is an artifact of the ALUT method: Hedley et al write: "Hence the maximum retrievable depth is 20 m"	Using the PAN band Using the PAN band: all shallow pixels are modeled by band_PAN against all_seven_band_1_to_band_7 see that , as depth increases ,  band j remains the  PAN band 16 (light grey)
SEATRUTH A tide height of 0.30 m was added to the "seatruth" depths, based on this kind if profile This is the only "use" of the "seatruth" dataset Hedley et al used tide corrected recorded depth points for control of their model: "with tide-corrected sonar depth transects used for ground-truth"	SEATRUTH The depth profiles are virtually identical this is most remarkable, as it tends to validate both 4SM and ALUT methods this indicates that the calibration of the PAN band is properly mastered But, in the very shallow depth range, there is still room for improvement I want to exclude bands beyond 670 nm from the PANHRO band agregation
Using Jerlov's data for calibration with hyperspectral images This is a strong confirmation that , using Jerlov's data along with an narrow_bands hyperspectral image just yields the correct values for the spectral operational diffuse attenuation coefficient 2K This is also a confirmation that the 2K values between 575 and 600 nm, 2K values must be lowered significantly: -0.02 m-1 for band_8  at 564 nm -0.02 m-1 for band_9  at 574 nm -0.07 m-1 for band_10 at 596 nm -0.03 m-1 for band_15 at 675 nm ? No proper calibration may be achieved unless this tweaking is accounted for This confirms what was established in the early days of using CASI datasets Gezirat Siyul Prince Edward Island Porquerolles	No need for field data for calibration when using hyperspectral images This is a strong confirmation that , using Jerlov's data along with an narrow_bands hyperspectral image just yields Therefore : no need for field data when using narrow_band images   The reason why this is not really true for WV2 or OLI data is : these are very_wide_band images

Profile Blue                                Profile Yellow

Profile BLUE Not using the PAN band

Profile YELLOW using the PAN band