Final Project for the Programming and Geostatistical Analysis course (MSc. Earth Observation and Geoanalysis)
This Script was written as a final project for the Programming and Geostatistical Analysis course MB2 which is one of the courses that I took during my MSc. in Applied Earth Observation and Geoanalysis (EAGLE) at JMU Würzburg
The purpose of the project is to evaluate Sentinel 1 and Sentinel 2 Data for Land Cover Classification using Machine Learning "Random Forest(RF)" in the area of Antwerp, Belgium. The data were dowloded from copernicus open access hub and the Preprocessing steps were conducted using the open source software SNAP
Six land cover classification maps were generated according to the data integration method; Sentinel 1 only, Sentinel 2 only, Sentinel 1 with its VV and VH GLCM bands, Sentinel 1 with Sentinel 2, Sentinel 2 with its Vegetation Indices (VI) (NDVI, SAVI, MSAVI2, NDWI2) and finaly all the data together. All the RF land cover classification models were evaluated by the accuracy assessment.
Walid Ghariani MSc. Student in Applied Earth Observation and Geoanalysis (EAGLE) linkedin E-mail: walid.ghariani@stud-mail.uni-wuerzburg.de
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