samsammurphy/6s_emulator

Atmospheric correction in Python using a 6S emulator

6s_emulator's Issues

adjacency effect

Hello! Thanks for creating this package. I am using it for LUT based correction of ASTER data. I was wondering, and perhaps this is more accurate to ask of the Py6S package, is there a switch or some capability to enable correction of adjacency effect in the atmospheric correction process? Or is it enabled by default? I can't seem to find any mention of it anywhere in the Py6S code unless it is encoded with the BRDF specification.

Cheers,
Joe

LUTs: pre-build and upload

It takes several hours to build LUTs but they are fairly lightweight. Should be supplied here.

Build and upload LUTs for the following satellite and aerosol profiles (at nadir for now)

• Landsat TM, continental
• Landsat TM, maritime
• Landsat TM, urban
• Landsat ETM+, continental
• Landsat ETM+, maritime
• Landsat ETM+, urban
• Landsat OLI, continental
• Landsat OLI maritime
• Landsat OLI, urban
• ASTER, continental
• ASTER maritime
• ASTER, urban

NB. iLUTs (i.e. interpolated LUTs), on the other hand, don't take to long to create (i.e. probably under 30 seconds) but do take up a lot of space (i.e. around 0.5 Gb for a Landsat mission). Probably best to let users interpolate LUTs on the client-side for now (?)

installaion instructions in README

need to add how to install in the README..

maybe just link to dependencies in the WIki:
https://github.com/samsammurphy/6S_emulator/wiki/Dependencies

GEE feature collection atmcorr

This is the basic idea:

Atmospheric Correction of Feature Collections in GEE (add to 6S_emulator repo as a wiki)

1. export the atmospheric correction variables (atmvars)

$ py export_atmcorr_variables.py {name} {lat} {lon}

2. download atmvars locally to .csv

• find .csv in drive
• right-click on it and select 'download'

3. run 6S emulator and update the variables

update_atmcorr_variables.py {name} {aerosol}

• {aerosol} is optional: default = 'CO' (continental)

4. upload 6S results to a fusion table

5. atmospheric correction in playground using fusion table

Image correction wiki

describe divide and conquer method for image correction

AOT retrieval

add in-scene AOT retrieval

atmospheric conditions from GEE

add module to extract atmospheric water vapor and ozone or a given time and place on the Earth's surface using Google Earth Engine

validation

Add validation to Wiki

add photos of collaborators to wiki home

aerosol model guidance

some guidance in choosing an aerosol_profile would be useful, for me at least. I assume CO is just the "default". DE and MA seem pretty self explanatory? When would you prefer NO? UR would be used for NYC? Raleigh?

dependencies

need to mention dependencies in wiki

e.g. Py6S, etc.

support view zeniths that are off-NADIR

combine iLUT outputs from 2 view zeniths and take the average

[solar ciew angle, satelite view angle, satelite zenith angle] in your LUT_build.py

dear dr. Sam Murphy:

I'm very happy to use your 6S_emulator,and still have some question about your code. how can you consider the factor of [solar ciew angle, satelite view angle, satelite zenith angle] in your LUT_build.py, and these fator are very important in atmospheric correction. hope for your reply.

your sincerely,
xiaosong ding

design trade-offs

talk about the necessity to trade-off performance with size..

The larger the LUT the better the performance can be.. of course this also depends on the positioning and selection of solution points within the LUT.

Expressing this clearly will help potentially interested users in seeing that they could boost performance (or decrease LUT size) if they want to..

Maybe you should make it easier for people to select there own input lists??

Changing range of valid values?

Hi Sam,

Stumbled upon your useful tool, and was hoping to conveniently be able to use the pre-built LUTs (specifically those for Landsat TM). Thanks for sharing it.

So far I've been happy with the current features, but now have an issue with the range of valid values. According to the the readme, the range of valid WVP values is 0 - 8.5 [g/cm2], and I am dealing with conditions that fall outside this range (~10 [g/cm2]).

If I edited LUT_build.py and tacked on some extra values to the H2O key in the dictionary on line 113, would that extend the range? Would the built table then break, and not work with LUT_interpolate.py anymore?

Regards,
Jigme

user-defined wavebands

add support for user-defined wavebands not already supported by 6S and/or Py6S..

e.g. Sentinel 2, Hyperion, etc.

can't see the figures referenced in Elliptical Orbit Correction

https://github.com/samsammurphy/6S_LUT/raw/master/table_elliptical_correction.png and https://github.com/samsammurphy/6S_LUT/raw/master/harmonic_function.png.

README is a bit wordy?

perhaps the README is a bit longer than it really should be..

might be a good idea to send some of that material to the wiki (using links to let people know there is more info if they want to see it)

conda installation refers to https://github.com/robintw/Py6S that doesn´t include LUTs

hi, i´m trying to use your tool here, but when install it, i get the Py6S env running, but this doesn´t include your adding functions to feed the 6S modelo with LUTs. What i´m doing wrong? (i have tried also docker installation without luck).
thanks!

Move data for look-up tables to separate CSV files.

I think it'd be a lot cleaner if we moved these large data tables to separate CSV files and then parsed those files. https://github.com/samsammurphy/6S_emulator/blob/master/bin/astronomical.py#L162 and https://github.com/samsammurphy/6S_emulator/blob/master/bin/astronomical.py#L399

Thoughts?

iLUT file structure

Explain how iLUT files are organized