[GRASS-dev] compile 6S library in GRASS

Thu Jun 28 05:46:54 PDT 2018

On Thu, Jun 28, 2018 at 12:17 PM, Roberta Fagandini <robifagandini at gmail.com>
wrote:
>
>
>
> 2018-06-28 10:26 GMT+02:00 Moritz Lennert <mlennert at club.worldonline.be>:
>>
>> On 27/06/18 15:40, Roberto Marzocchi wrote:
>>>
>>>
>>>
>>> Il giorno mer 27 giu 2018 alle ore 15:25 Markus Metz <
markus.metz.giswork at gmail.com <mailto:markus.metz.giswork at gmail.com>> ha
scritto:
>>>
>>>
>>>
>>>     On Wed, Jun 27, 2018 at 3:06 PM, Roberta Fagandini
>>>     <robifagandini at gmail.com <mailto:robifagandini at gmail.com>> wrote:
>>>      >
>>>      >
>>>      >
>>>      > 2018-06-27 14:24 GMT+02:00 Markus Metz
>>>     <markus.metz.giswork at gmail.com <mailto:markus.metz.giswork at gmail.com
>>:
>>>      >>
>>>      >>
>>>      >>
>>>      >> On Wed, Jun 27, 2018 at 2:16 PM, Roberta Fagandini
>>>     <robifagandini at gmail.com <mailto:robifagandini at gmail.com>> wrote:
>>>      >> >
>>>      >> > I'm trying to create an automatic procedure to retrieve all
>>>     the input parameters for the control file of i.atcorr.
>>>      >> > I need py6S because I want to automatically read and compute
>>>     AOT at 550nm from an AERONET file.
>>>      >>
>>>      >> With AOT you mean aerosol optical thickness right? This is user
>>>     input to i.atcorr. There are various sources for AOT at 550nm, e.g.
>>>     MODIS.
>>>      >
>>>      >
>>>      > Right!
>>>      >
>>>      >>
>>>      >>
>>>      >>
>>>      >>
>>>      >> Anyway, it is probably much easier to to write your own routine
>>>     to read the AERONET file and get the corresponding formula for AOT
>>>     than to fight with 51821 lines of Fortran source code that is
>>>     numerically unstable. Maybe I can help with getting AOT at 550nm
>>>     from an AERONET file avoiding the Fortran version of 6S.
>>>      >
>>>      >
>>>      > Ok but I'm not able to create this kind of routine on my own. If
>>>     someone, more expert than me, can help me in translating the 6S/Py6S
>>>     functions I can go on in this way otherwise for me it's easier to
>>>     use the fortran source code.
>>>
>>>     Apparently the AERONET data are simple CSV files. You can import
>>>     them with r.in.xyz <http://r.in.xyz> or v.in.ascii.
>>>
>>>     Still, I think it is up to the user to decide on the source of AOT
>>>     values. AERONET is one of many possible sources.
>>>
>>>
>>> Ok but I know that Roberta  want try to simplify the procedure for
atmospheric correction. In particular she would like to add an option (not
the only one) to read automatically the AOT at the wave length of 550 nm
from the AERONET file.
>>>
>>> The steps to do this IMHO are:
>>>
>>> 1) read the file (using GRASS or maybe better Python)
>>>
>>> 2) a formula to calculate the AOT550
>>>
>>> Unfortunately I have no idea about the 2nd point :-(
>>
>>
>> I'm not sure either, what exactly the necessary calculations are.
>>
>> Superficially reading through the relevant class in Py6S [1], I
understasnd that it does two things:
>>
>> 1) Get the value of AOT550
>> 2) Create a continuous profile by interpolating values
>>
>> If all you need is 1), then all they do (see _get_aot() method at the
end) is to read all the AOT_* columns and chose the value of the line with
the timestamp closest to the one asked for and the wavelength closest to
550.
>>
>>
>> As the code is GPL you could probably just extract the necessary parts
and integrate them into your code. The only thing I'm not to sure about is
their use of pandas which creates yet again another dependency which I
don't really think necessary and desirable.
>
>
> Yesterday I studied the library better and I understood that it only
extracts the available AOT values closest to the wavelength 550 for the
specified timestamp. No calculation is made so I'm trying to write my own
routine avoiding any dependency.
>
>>
>>
>>
>> It should be enough to extract from the file the date and time (or maybe
easier to work with: year and the Julian day) and all AOT_* columns, parse
the AOT_* columns for their wavelength value and then identify the value
which has closes time and wavelength to the time requested and 550nm.
>
>
> That's exactly what I want to do and I'm working on it!

open the file with your preferred spreadsheet program and copy the
corresponding value;-)
>
>>
>>
>> Moritz
>
>
> I know that AERONET is not the only source and obviously in my module
there will be both an option for providing manually the value, as Markus
and Stefan suggested, and an option to extract the AOT from an AERONET
file. I'm not an expert in MODIS data so if someone wants to give
suggestions about how to retrieve the AOT from these data, I will
definitely add this option too.

about your module: it is concerned with Sentinel-2 cloud and shadow
detection. As a general rule, a module should do one thing, and should do
it right. In this sense, importing AERONET data should be a separate
module, and your module should do Sentinel-2 cloud and shadow detection,
nothing else, this is already complex enough.

Regarding a new module e.g. v.in.aeronet:
It should interpolate AOT at 550nm considering the closest wavelengths with
valid data. Unfortunately most of the AERONET data are nodata.
Interpolation can be a simple linear interpolation, see
https://aeronet.gsfc.nasa.gov/new_web/V2/climo_new/explain/explain_new.html

It should perform spatial interpolation because the stations are scattered
with large distances in between. Spatial interpolation can be done with any
of the v.surf.* modules.

It should offer temporal interpolation in case there are no data for the
required date. This can be done with the temporal GIS framework or with
r.series.lwr.

Regarding MODIS data, r.in.gdal can import MODIS data, and there is r.modis

Putting it all together:
that would be a wrapper script that helps to
1) import visibility as a map or estimate a fixed visibility value
2) perform atmospheric correction with i.atcorr
3) detect clouds and shadows

Markus M

>
> Thanks
> Roberta
>
>>
>>
>>
>>
>>
>> [1]
https://github.com/robintw/Py6S/blob/master/Py6S/SixSHelpers/aeronet.py
>
>
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