QGIS for Earth Observation and Geospatial Applications

Learn to access open source data platforms, download Landsat and SRTM data, and use QGIS to georeference maps, prepare vector data, and perform clip, mask, buffer, merge, and spatial analyses.

Master layer stacking in QGIS with the SCP plugin to fuse Landsat 9 bands into natural and false color composites, including vegetation indices and pan sharpening considerations.

Learn to pan-sharpen Landsat 8/9 multispectral data in QGIS by fusing bands 2–7 with the 8 panchromatic band to achieve 15‑m resolution via a virtual raster workflow.

Learn to georeference unreferenced maps in QGIS using freehand raster georeference, aligning scanned or downloaded imagery with reference layers for watershed and land cover mapping.

Learn to prepare vector data in QGIS by creating separate point, line, and polygon shapefiles, defining fields, digitizing features, editing attributes, and joining CSV data for a complete GIS workflow.

Apply geoprocessing and spatial analysis tools in QGIS to work with vector data, performing clip, buffer, and union. Reproject layers for meaningful distance measurements and generate grids for sampling.

Learn to work with digital elevation models using SRTM DEM data, mosaic and subset rasters, reproject to UTM zone 43, and delineate watersheds with raster by mask in QGIS.

Delve into watershed delineation in QGIS by filling sinks, computing flow direction, applying Strahler order, and extracting drainage basins and streams for a defined catchment.

Open QGIS to capture the ROI and collect spectral signatures for land cover classification, then save your session as a qgz project to preserve your work.

Use Landsat and Sentinel satellite data in QGIS to perform land cover classification and vegetation health assessment using spectral signatures and Ndvi and Ndwi, via the semi-automatic classification plugin.

Learn Landsat data preparation in QGIS using the semi-automatic classification plugin: download from USGS Globis, select bands 2,3,4,5,8, perform pan sharpening, and clip by a watershed mask.

Create ROI training data in QGIS with Landsat bands, define land cover classes, and apply maximum likelihood classification to generate a land cover map.

Compute ndvi and other spectral indices in qgis using the raster calculator with near infrared and red bands; interpret ndvi values from -1 to 1 to assess vegetation health.

Compute the ndwi from Landsat bands 3 and 5 using raster calculator to extract water bodies. Create color-coded maps and align results with projection and dates.

Create map composition in QGIS by layering land use, boundaries, roads, and rivers, then classify with colors and legends. Add print layouts with scale, north arrow, grid, and data sources.