|It's time I get some "best case" images in order to consolidate the WV2 fundamentals! |
"Best Case" would be
- near Nadir viewing, or at least looking away from the sun
- reasonable glint and clouds, gentle or no wind
- at least some bright coral or quartz sands apart from corals or submerged vegetation/algae
- all depths reasonably represented accross the whole shallow depth range
- clear and homogeneous waters
- bright solar illumination
- some land areas in the image, some vegetation on land
- optically deep waters available in the image
As of mid-2012, quite many investigators and service providers struggle to experiment with WV2 images for shallow water work: bathymetry and bottom typing.
I have the experience of processing three WV2 images with 4SM: one in Bahrain, one in Western Australia, and one at Oahu, Hawaii.
Bahrain, processed in march 2011
This should have been a winning case.
Alas, dredging activities all over the place resulted in very few usable output.
Still, some remarquable results were obtained:
excellent but weird glint regressions under an overcast sky. "Deglinting" here mostly subtracts adjacency effect in this very stuffy atmosphere (no wave-modulated glint is observed)
excellent optical calibration in OIII coastal water type (OIII and C1 are virtually the same water type)
excellent seatruth using a multibeam DTM: R2=0.3 m in the 4-9 m depth range
NoNeed: under control of seatruth: coefZ=0.96 ==> WLgreen could be increased a bit (hardly worth noting). Seems that NoNeed for field data applies, just like with SPOT, IKONOS and CASI data.
as for system noise: not a problem in the absence of sea surface glint
Western Australia processed in november 2011
This should have been a winning case. Alas shallow bottoms are extremely dark.
no truely deep waters in the image: this is a bad problem for bands 1, 2 and even 3
excellent but weird glint regressions ; glint is very strong; all the glint is generated at the sea-surface; bands 1, 4 and 6 are poorly correlated to band 7
hardly any bottom reflected signal in the purple band; only bands 2 and 3 exhibit good bottom detection; no bottom detection in bands 8 to 4 (too deep and too dark)
as for system noise: not so noisy after all. But striping cannot be accepted: should be corrected for by data provider
optical calibration extremely difficult and questionable ; OI oceanic water type
NoNeed: under control of Lidar seatruth: coefZ=1. Seems that NoNeed for field data applies, just like with SPOT, IKONOS and CASI data.
Waimanalo Bay in Oahu, Hawaii processed in july 2012
This should have been a winner.
Alas, the image is marred by extremely strong glint,
and there is some kind of pollution of Red and Yellow bands.
weird glint regressions: bands 1, 4 and 6 are poorly correlated to band 7, bands 2, 3, 5 and 7 are poorly correlated to band 8: it is absolutely necessary to account for that
this is easily explained by the time lapse of ~0.14 second between imaging of legacy bands 2, 3, 5 and 7 and newer bands 1, 4, 7 and 8, as demonstrated here
as for system noise: glint in bands 7 and 8 are offset , and the marine signal is extremely noisy : poor deglinting conditions and very heavy smoothing required;
I tend to blame it , not on the system noise per-se, but rather on adverse imaging geometry which caused very strong and noisy glint: the sensor looks right into the sun's direction and 37° offNadir: this is very bad, call it "worst case".
==>> For shallow water work, we want near-Nadir viewing, so as to (1)minimize the glint and (2)ensure that upwelling bottom-reflected photons captured by the sensor followed a near vertical path through water 2K~=2a see Jerlov quotation.
optical calibration : quite difficult in spite of the clearest of waters : OI oceanic water type
- all visible bands exhibit excellent bottom detection, including the purple band 1.
- NoNeed: under control of Lidar seatruth: coefZ=0.96. Seems that NoNeed for field data applies, just like with SPOT, IKONOS and CASI data.
- RMSE is bad: but now we know RMSE can be very good under proper imaging conditions