| || |
I see a potential for developing 4SM into an automatic process. we need to talk
I want to contribute to this effort. I also want to develop a graphic interface.
After many years in isolation,
I might as well release 4SM under some flavor of GPL license.
I just need some encouragements and support.
My wishlist (outdated)
accumulate experience and burn it into the 4SM project
- Some money/resources: your commitment as SuperUser requires that I am connected and supported
- Transfer: hopefuly someday I'll need to engage into a business plan with a business partner
- if I seem to be unable to meet your expectation/requirement
- if I get bogged down with 4SM code or my computer setup
- Computing: I need access to a computer proficient person as/when required
- for big upload or download, I need to go to a nearby internet lounge or Wifi spot
- from wherever I happen to be roaming, which includes France, Tahiti and New Zealand
- internet VOIP telephony,
- updating my WIFEO website on a regumar basis ,
- Communication: I need 3G mobile internet on my laptop, for email,
- Sea truth: that's what is most wanted.
- Your cooperation, commitment, resilience as a SuperUser: that comes next!
- Exposure: links from my website to your own reporting of climbing the 4SM learning curve on your own website.
- Worldwide: develop experience over a wide variety of shallow water environments worldwide.
- Band setting: develop experience over a wide variety of multispectral and hyperspectral imageries.
- Wavelengths: consolidate a database of specific operational wavelength for each waveband of all possible multispectral imageries.
- Reflectance: calibrate spectral LM=LsM-La in units of reflectance through offset and gain values, and vice versa.
- Spectral Soil Line database: map variations of operational spectral shallow water LM along the coasts worldwide, in units of reflectance. This shall take the form of a series of LMWL values in units of refelctance, to be attached to a particular location on site, or to a particular generic type of bright beach material (coral sand, etc). This should be enough to specify the local Soil Line for any spectral image down the line.
- Spectral Knir database: this exercise should yield a fairly secure set of Knir values for all wavebands involved.
- Bottom typing: this is the ultimate goal of 4SM, of course
- if we can prepare a bottom typing map ahead of any field work, sure the planning of that field work shall become much more reasonable and rational.
- provided the set of Ki/Kj ratios is secured from the image itself, then the bottom typing does NOT depend on any seatruth on computed depths.
- all that's needed then is to work out the labels for bottom types identified, and reduce/bin the list of arguably distinct types.
- develop bi-dimensional histograms under AOI polygon
- work at a printable version of 4SM website
- 32/64 bits computing
- compile 4SM in 64 bits
- someone to compile all 4SM calls and OpenEV in 64 bits
- OpenEV: someone to contribute to the project in order to
- improve some aspects of OpenEV that are frustrating, like
- relative path in .opf projects
- random order in imaqge/compose
- add functionalities that we need for 4SM
|Automatize the 4SM process |
- by all means, avoid images captured with oscillating mirror sensors, or face the consequences
- Lsw: develop a way to estimate Lsw automatically from the image. This is easiest in the red-nir wavebands.
- La :
- assuming atmospheric adjacency effect does not come into play
- assuming spectral LsM is available,
- assuming spectral Lsw is available,
- assuming La~=Lsw in the red-nir part of the spectrum,
- sampling the spectral Soil Line may be done automatically for the pair of red and nir bands of the image.
- this is what is done at present in 4SM under supervision: Soil Line by mSE mask value set manually at mSOIL by the practitioner : soil line
- for 4SM to do it on its own, it would need algorithms to:
- read applicable local spectral LM values for all wavebands of the image from the database of spectral soil line in units of reflectance.
- convert these values into units of DN of the image.
- derive the value of slope LMred/LMnir which applies to the image.
- this defines the Soil Line in a scatter plot for this pair of bands in the image. This soil line is the straight line which starts from spectral La (~=the TOA radiance of a black body at null depth) and reaches through spectral LsM=LM+Lsw (~=the radiance of the brightest shallow bottom type at null depth at the top of the atmosphere) with a slope value of LMred/LMnir.
- apply a tolerance of ~1.18 to the value of this slope: slope*1.18 and slope/1.18; in other words allow for a certain level of fuzziness of the soil line in the image, as it is well known that the system noise increases as the radiance level increases.
- select all spectral pixels of the image which plot inside this tolerance in a scatter plot of Lred=Lsred-Lswred versus Lnir=Lsnir-Lswnir.
- Note that all shallow water pixels plot on the red side of the soil line:
- this provides a mean for segmenting the image into dry lands, whether bare or vegetated, and marine areas
- we also need a similar way to segment clouds out.
- work out the average spectral soil line for all wavebands
- in the scatter plot of Li versus Lnir, determine spectral Lai for all bands i through a simple geometric construction.
- this is usually fairly straightforward provided the image exhibits some bare land, from dark to bright.
- in case the image is totally under water, chances are that the Soil Line may be set to be parallel to the Darkest Pixels Line: Davies Reef.
- Lw: derive spectral Lw=Lsw-La.
- Kgreen/Kblue and spectral K
- select the Brightest Pixels Line for all pairs of bands from cloud free marine areas of the image.
- this does not need the image data to be deglinted, through the LsNirMaxBPL parameter of the -Extract command line argument.
- linearize the Brightest Pixels Line data for all pairs of bands.
- work out the best fit of a straight BPL line with the observed BPL pixels for the Blue/Green pair of bands: its slope if the ratio Kblue/Kgreen.
- use Jerlov's data to interpolate the intermediate marine water type which applies to this slope.
- use this slope to derive spectral K for all visible wavebands.
- check that these values are acceptable.
- Automatic deglinting:
- provided there are some glinted areas over optically deep waters, it should be possible to ascertain the Glint parameters through some automated process.
- Modeling: 4SM should now be ready to
- apply the above spectral calibration parameters : WL, Lsw, La, LM, spectral K
- to deglint the current pixel
- and operate the inverse simplified RTE LBWL=LwWL+(LsWL-LswWL)*exp(KWL*Z)
- by increasing Z
- until the spectral water column corrected soil line LBWL
- is deemed to fit reasonably well onto the spectral Soil Line LMWL for that image
- for each shallow water pixel of the image.