Basic remote sensing concepts: electromagnetic spectrum; atmospheric diffusion and absorptions; spectral signature; spectral windows (VIS, NIR, SWIR, TIR); active and passive sensors.
Satellite data: LANDSAT, ASTER, SENTINEL, SRTM, LIDAR, aerial data
Digital data: raster and vector files; data formats; spatial, radiometric, spectral and temporal resolutions;
Data Processing: filters; Principal Components (PCA); Tasseled Cap; vegetation index NDVI
QGIS exercises: working with raster data (stretching, color bar); vector file with points, lines and polygons; RGB virtual real and false color; attribute table; terrain profile tool; QGIS2three; georeferencing; Semi-Automatic Classification
Case studies: examples of published application of remote sensing to archaeology projects.
Preparation of the QGIS archive for the final examination
