Mastering Geospatial Analysis with QGIS

The "Mastering Geospatial Analysis with QGIS" course employs a multi-disciplinary approach, covering essential aspects of geospatial analysis and QGIS software through nine structured modules. Module One introduces learners to QGIS, encompassing installation, QGIS 3.0 basics, and interface exploration including toolbars, panels, and plugins. Module Two focuses on practical geospatial data handling within QGIS, covering shapefiles, vector and raster data styling, and attribute management using calculators and selection tools. Module Three explores cartographic techniques such as coordinate systems, projections, and map creation including choropleth and graduated symbol maps. Additionally, it includes data integration tools like basemaps, GPS data handling, and measurement tools. Module Four delves into georeferencing and digitization methods for toposheets and online sources like Open Street Maps and Google Earth. Advanced spatial analysis techniques like buffer and overlay analysis are detailed in Module Six, while Modules Seven to Nine cover satellite data handling, terrain analysis, and advanced mapping and application development using QGIS and tools like Qfield and BIM integration. Join us in mastering QGIS for geospatial analysis and applications development, preparing to excel in this dynamic field. Target Learners: • Undergraduate students of Civil Engineering • Post-Graduate Students in Geoinformatics/ Remote Sensing/ Geospatial Engineering. • Practicing Engineers involved in geospatial applications in construction. • Faculties in Civil, Geospatial and Environmental Studies. • Professionals in GIS and Remote Sensing fields • Engineers and project managers involved in spatial data analysis Prerequisites: • Basic understanding of GIS principles and spatial data • Familiarity with computer operations and software usage • Software: QGIS

• Introducing QGIS
• This module introduces the fundamentals of QGIS (Quantum GIS), a popular open-source Geographic Information System software. Learners will be guided through the installation process of QGIS 3.0, exploring its features and graphical user interface (GUI) components such as toolbars, panels, and plugins.
• Working with Shapefiles
• This module focuses on practical skills for working with geospatial data in QGIS. Learners will learn to download and work with shapefiles, including styling vector and raster data. The module also covers handling attribute data using tools like the Field Calculator and selecting features within QGIS.
• Exploring Maps
• This module covers cartographic techniques and tools available in QGIS for map representation and styling. Learners will explore coordinate systems, projections, and create various thematic maps such as choropleth, graduated symbol, heat maps, and dot distribution maps. Additionally, the module covers map layout techniques and essential data integration and analysis tools within QGIS.
• Georeference & Digitization of Toposheets
• This module focuses on georeferencing and digitization techniques using QGIS. Learners will understand the process of georeferencing toposheets, including downloading and setting transformation parameters. They will also explore digitization techniques for creating point, polyline, and polygon datasets from toposheets.
• Georeference & Digitization of Open Street Maps and Google Earth Images
• This module focuses on advanced techniques for digitizing and georeferencing spatial data from online sources using QGIS. Learners will explore methods for digitizing point, polyline, and polygon datasets from OpenStreetMap and Google Earth images. The module covers downloading and georeferencing Google Earth images, and using the QuickMapServices plugin for accessing map data.
• Spatial Analysis
• This module explores advanced spatial analysis techniques available in QGIS. Learners will delve into buffer analysis methods including multi-distance buffers, overlay analysis techniques, and network analysis using tools like the ORS (OpenRouteService) plugin. The module equips learners with skills to perform sophisticated spatial analyses for diverse applications.
• Feature Class Analysis
• This module focuses on acquiring and classifying satellite data using QGIS. Learners will explore various satellite data downloaders including USGS, Copernicus, NASA Earth Data Search, and Bhuvan. The module covers supervised classification techniques using the Maximum Likelihood Algorithm, unsupervised classification methods such as K means clustering, and temporal analysis techniques for change detection.
• Terrain Analysis
• This module covers terrain analysis and surface modeling techniques using QGIS. Learners will explore elevation and slope analysis, hillshade, aspect, contour generation, watershed analysis, surface analysis, viewshed analysis, and profiling and cross-sectioning techniques for detailed spatial analysis and visualization.
• Visualization of World
• This module explores advanced topics in geospatial mapping and application development using QGIS. Learners will learn techniques for extracting building footprints, creating 3D maps, and developing web and mobile maps. The module also covers integrating QGIS with Building Information Modeling (BIM) for creating digital twins.