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GSoC 2018 GRASS GIS module for Sentinel-2 cloud and shadow detection

Title: GRASS GIS module for Sentinel-2 cloud and shadow detection
Student Name: Roberta Fagandini, Ph.D. student at Politecnico of Milano
Organization: OSGeo - Open Source Geospatial Foundation
Mentor Name: Roberto Marzocchi, Moritz Lennert
GSoC proposal: GRASS GIS module for Sentinel-2 cloud and shadow detection
Repositories: Github for development:


Unlike Landsat images, Sentinel-2 datasets do not include thermal and Quality Assessment bands that simplify the detection of clouds avoiding erroneous classification. Moreover, also clouds shadows on the ground lead to anomalous reflectance values which have to be taken into account during the image processing. To date, only a specific module for Landsat automatic cloud coverage assessment is available within GRASS GIS (i.landsat.acca) while regarding shadows, no specific module is available. Therefore to date, the detection of clouds and shadows has to be manually performed for Sentinel-2 images.


The aim is the coding of a specific module for GRASS GIS application which implements an automatic procedure for clouds and shadow detection within Sentinel 2 images. The module has to provide a tool which can be easily used by inexpert users, taking advantage of the suggested parameters, or by more expert users that can modify default values according to their needs.


Community bounding period Improvement of my knowledge about GRASS Python Scripting Library and tests in order to reach a final procedure version
MAY 14 - 18
MAY 21 - 25
MAY 28 - JUNE 1
JUNE 4 - 8
JUNE 11 - 15 First evaluation
JUNE 18 - 22
JUNE 25 - 29
JULY 2 - 6
JULY 9 - 13 Second evaluation
JULY 16 - 20
JULY 23 - 27
AUGUST 6 - 10
AUGUST 6 - 14 Final evaluation