[GRASS-dev] GSoC 2018 report week 07 - GRASS GIS module for Sentinel-2 cloud and shadow detection

[Stefan Blumentrath]

Ciao Roberta,

Thanks for all your excellent work and comprehensive documentation and information also on dev list.

In the light of the discussion around the Sentinel-2 pre-processing wrapper script, I was wondering if you plan / were considering to add a multi-temporal approach to cloud detection [1,2,3] to your module?

If your GSoC was a "pick and choose event”, I would personally be more than satisfied with an “i.atcorr.params” module (or the like) that compiles 6s input file (maybe just with simple user input on geometrical conditions, aerosol model, …) instead of a wrapper for a full preprocessing chain, if that allows you to work on a (at least preliminary) multitemporal could detection procedure…

Maybe you discussed this already with your mentors. So, I have no intentions to interfere here, just indicate my personal preferences 😉 …

As for AOT estimation, this paper might be of interest?
http://www.mdpi.com/2072-4292/9/12/1230/htm


Kind regards,
Stefan

1: https://www.sciencedirect.com/science/article/pii/S0034425710000908
2: http://www.cesbio.ups-tlse.fr/multitemp/?p=6832
3: https://forum.step.esa.int/t/maccs-maja-now-distributed-as-binary-code-for-non-commercial-use/5500


From: grass-dev <grass-dev-bounces at lists.osgeo.org> On Behalf Of Roberta Fagandini
Sent: søndag 1. juli 2018 11:23
To: soc at lists.osgeo.org; GRASS developers list <grass-dev at lists.osgeo.org>
Subject: [GRASS-dev] GSoC 2018 report week 07 - GRASS GIS module for Sentinel-2 cloud and shadow detection

Hi all!
I'm Roberta Fagandini and I'm working on my GSoC project, a GRASS GIS module for Sentinel-2 cloud and shadow detection.
This is my report for the seventh week of coding.

1) What did I complete this week?
· Continued coding the GRASS python script to execute i.atcorr for all bands of the input image changing accordingly the requested input parameters and control file [0]
· Changed some lines of the code according to the i.atcorr manual page (e.g. lon/lat retrieved from the computational region and not from metadata file) [0]
· Added the automatic computation of mean target elevation from the input dem [0]
· Wrote and added the python script for retrieving the aerosol optical thickness (AOT) value from AERONET data using Py6S library [1]
· Discussed with dev community about the need to write my own routine to retrieve and compute AOT at 550 nm avoiding too many dependencies [2]
· Started writing my own routine to extract and compute AOT at 550 (one of the parameters of the i.atcorr control file) [3]
2) What am I going to achieve for next week?
· Finish writing the routine for AOT computation
· Understand how to automatically retrieve some parameters for the control file like aerosol and atmospheric models
· Finish defining the automatic procedure for retrieving all the last missing parameters for the control file

3) Is there any blocking issue?
No at the moment but the coding of the routine takes more time than expected.

Here the links to my GitHub repository [4] and wiki page [5]

Kind regards,
Roberta

[0] https://github.com/RobiFag/GRASS_clouds_and_shadows/commit/52ede2e0e8d157f5b19fbb414c29bbde0e728b13#diff-d42beca70d363fcee5a6ec17260c5129
[1] https://github.com/RobiFag/GRASS_clouds_and_shadows/commit/a8757bfaae04c283daab1b03216b3e0d7ed4c885
[2] https://lists.osgeo.org/pipermail/grass-dev/2018-June/088814.html
[3] https://github.com/RobiFag/GRASS_clouds_and_shadows/commit/568164ea4f093a3045b2562404ece544d1ff6f0f
[4] https://github.com/RobiFag/GRASS_clouds_and_shadows
[5] https://trac.osgeo.org/grass/wiki/GSoC/2018/CloudsAndShadowsDetection

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