Repo for the Master course on Advanced Remote Sensing in the faculty of Geoinformatics at the Munich University of Applied Sciences
Authors: Yrneh Ulloa, Severin Herzsprung
Learning basic pre-processing of raster data using Python.
Atmospheric correction of satellite images.
Segmentation of a satellite image. Creation of training data.
Supervised classification using Random Forest.
After downloading a Night Light Image product, you need to convert the format from HDF5 to GeoTIFF. Afterwards, you can explore the data in QGIS.
Harvest some Twitter data and analyse the trends of the data.
Extra information on how to use the library Pandas for dataframe analysis. This is the core datatype of many products, including some text and raster data.