QGIS Mapping and Spatial Analysis Training Course

Participants can select, assign and transform coordinate reference systems correctly.

• Geographic and projected coordinate systems distinguished through practical measurement implications
• EPSG codes used to identify authoritative coordinate reference system definitions
• Datum transformations selected when combining datasets from different reference frames
• Layer CRS assignment checked before display, editing or geoprocessing
• On-the-fly reprojection interpreted without confusing display and stored coordinates
• Distance and area calculations validated using suitable projected coordinate systems

Participants can prepare and edit vector datasets for analysis-ready use.

• Point, line and polygon geometry matched to operational feature types
• Field types, aliases and domains designed for consistent attribute capture
• Editing tools used for feature creation, reshaping, splitting and merging
• Snapping tolerances and topological editing rules prevent geometry gaps
• Geometry validity checks identify self-intersections, duplicates and empty features
• Multipart features converted when analytical methods require singlepart geometries

Participants can clean attributes and connect operational tables to spatial features.

• Attribute tables filtered, sorted and selected using QGIS expressions
• Field calculator expressions create derived indicators and standardised categories
• Text cleaning resolves inconsistent codes, spacing and null values
• Unique identifiers assessed before joining spreadsheet and database records
• One-to-one joins connected through common fields and verified records
• One-to-many relations configured for inspections, surveys and transaction histories

Participants can produce readable maps that communicate a defined decision message.

• Visual hierarchy established through symbol size, colour, contrast and placement
• Graduated, categorised and rule-based symbology matched to data characteristics
• ColourBrewer schemes selected for sequential, diverging and categorical variables
• Labels configured with priorities, buffers, callouts and scale-dependent visibility
• Map layouts include titles, legends, scale bars, north arrows and sources
• Atlas generation produces location-specific map series from indexed features

Participants can convert scanned maps and imagery into usable spatial datasets.

• Ground control points selected from stable, identifiable reference locations
• Georeferencer transformation methods compared for map scale and distortion
• Root mean square error interpreted when assessing georeferencing accuracy
• Heads-up digitising captures features from georeferenced plans and imagery
• Topology checks verify shared boundaries, overlaps and unintended gaps
• Digitised features attributed using controlled values and source references

Participants can load, inspect and visualise raster data for analytical use.

• Raster cells, bands, resolution and extent interpreted for analysis suitability
• Digital elevation models, orthophotos and satellite scenes compared by purpose
• Raster statistics calculated before applying contrast enhancement or classification
• Single-band pseudocolour rendering reveals continuous surface value patterns
• Multiband composites created using visible, infrared and shortwave bands
• Raster clipping aligns source imagery with a defined study area

Participants can prepare field data structures and integrate collected observations into QGIS.

• Field survey forms designed around required attributes and validation rules
• QField project packages prepared for offline mobile data collection
• Default values and value relations reduce field-entry inconsistencies
• GPS accuracy, metadata and timestamp fields assessed during import
• Collected observations synchronised with master GeoPackage project datasets
• Photo attachments linked to features through documented file management

Participants can identify features that meet defined spatial and attribute conditions.

• Attribute queries constructed with Boolean operators, wildcards and null handling
• Select by location applies intersects, contains, within and touches predicates
• Spatial indexes created to improve query performance on larger datasets
• Distance-based selections identify features within operational service thresholds
• Expression-based selection combines spatial conditions with attribute criteria
• Selection results exported as documented subsets for further analysis

Participants can use standard vector geoprocessing methods to answer location questions.

• Buffer distances defined from policy thresholds, travel needs or risk zones
• Dissolve operations aggregate features using meaningful reporting categories
• Clip and intersection tools isolate features inside defined study boundaries
• Union and difference operations identify overlaps, exclusions and residual areas
• Spatial joins summarise nearby features, counts and measured attributes
• Processing outputs checked for geometry errors, fields and expected feature counts

Participants can assess access, service coverage and route-based relationships.

• Euclidean distance surfaces measure straight-line proximity to target locations
• Nearest-neighbour analysis identifies closest facilities, assets or response points
• Service areas estimated from travel distances along road network links
• Shortest-path routing compares alternative routes between operational locations
• Network topology checked for disconnected links, directionality and impedance fields
• Accessibility results interpreted against stated service standards and constraints

Participants can derive terrain indicators and basic drainage patterns from elevation data.

• Hillshade rendering improves visual interpretation of elevation surface form
• Slope and aspect derived for construction, agriculture and hazard screening
• Contour intervals selected according to terrain variation and map scale
• Depression filling prepares digital elevation models for flow analysis
• Flow direction and accumulation identify likely drainage pathways and catchments
• Terrain outputs validated against imagery, contours and known ground conditions

Participants can create and evaluate estimated surfaces from point observations.

• Point sampling patterns assessed for clustering, gaps and representativeness
• Inverse distance weighting parameters selected from observed spatial variation
• Kriging concepts distinguished from deterministic interpolation approaches
• Interpolation extent and cell size aligned with decision requirements
• Cross-validation residuals reviewed to assess prediction error and bias
• Estimated surfaces classified without overstating precision beyond source observations

Participants can prepare satellite imagery and derive indicators for environmental analysis.

• Landsat and Sentinel-2 bands selected for visible and infrared analysis
• Cloud masks and scene metadata reviewed before image interpretation
• Band stacking assembles multispectral imagery into analysis-ready raster datasets
• Normalized Difference Vegetation Index calculated from near-infrared and red bands
• Normalized Difference Water Index identifies surface water and moisture patterns
• Raster calculator expressions document band combinations and output units

Participants can classify land cover and identify changes between dated imagery.

• Training samples defined for spectrally distinct land-cover classes
• Supervised classification separates target categories using labelled pixel samples
• Unsupervised clustering explored where reliable training data remains unavailable
• Confusion matrices report classification accuracy, omission and commission errors
• Post-classification comparison identifies transitions between two classified raster dates
• Change maps documented with acquisition dates, classes and accuracy limitations

Participants can create reusable processing models for repeated GIS tasks.

• Processing Toolbox algorithms selected by input type and expected output
• Modeler workflows connect inputs, geoprocessing steps and named outputs
• Model parameters exposed for study areas, distances and source layers
• Conditional branches manage alternative processing paths and optional inputs
• Batch processing applies identical operations across multiple datasets efficiently
• Processing history retained to document methods and reproduce results

Participants can assess GIS data quality and document an auditable analysis process.

• Positional, attribute, temporal and logical accuracy assessed systematically
• Completeness checks identify missing records, coverage gaps and duplicate features
• ISO 19115 metadata elements recorded for source, quality and lineage
• Data lineage documents transformations, assumptions, tools and processing dates
• Quality-control checklists applied before publishing maps or analytical outputs
• Reproducible folder structures preserve source data, scripts and final products

Participants can prepare appropriate GIS outputs for controlled sharing and publication.

• Web map layers prepared with simplified geometries and appropriate attribute fields
• QGIS web services concepts distinguished between WMS, WFS and WMTS
• Data classification rules applied before publishing sensitive location information
• Map exports optimised for print, PDF, image and presentation formats
• Licensing terms reviewed for basemaps, open data and derived outputs
• Versioned deliverables managed through naming conventions and approval records

Participants can combine weighted spatial criteria into a transparent suitability assessment.

• Decision questions translated into measurable spatial criteria and exclusion rules
• Boolean constraints separate unsuitable areas from candidate locations
• Criteria standardisation converts diverse variables to comparable suitability scales
• Weighted linear combination combines criteria using documented stakeholder priorities
• Sensitivity analysis tests how weight changes affect ranked locations
• Suitability outputs communicate uncertainty, trade-offs and decision limitations clearly

Participants can build, review and present a complete documented QGIS analysis addressing a defined operational decision.

• Problem statement defines users, decision criteria, geography and required evidence
• Source datasets assessed for coordinate systems, completeness and analytical fitness
• Analysis workflow combines preparation, spatial methods and quality-control checkpoints
• Map layouts communicate findings, uncertainty, sources and recommended actions
• Peer review tests reproducibility, cartographic clarity and method justification
• Project presentation explains results, limitations and implementation recommendations clearly