GRASS GIS Terrain Analysis and Geoprocessing Training Course

Course overview

Terrain-derived information is often used to support drainage design, catchment planning, landslide screening, route selection, habitat assessment and flood-risk work, yet inconsistent DEM preparation and undocumented geoprocessing can produce misleading slopes, flow paths and suitability outputs. This course equips GIS professionals to build defensible terrain-analysis workflows in GRASS GIS, moving from raw elevation and vector source data to validated raster products, hydrological models and decision-ready map layers. It is designed for teams that need repeatable analysis rather than one-off desktop outputs.

Participants work deeply with GRASS GIS raster, vector and imagery-processing capabilities, including location and mapset management, region and resolution control, DEM conditioning, terrain derivatives, watershed modelling, raster algebra, map algebra, vector overlays and automated processing. They learn to select suitable computational regions, identify and correct common elevation-data issues, derive slope, aspect, curvature and topographic indices, delineate catchments and stream networks, and combine environmental criteria into transparent suitability models. The course also covers integration with QGIS, GDAL/OGR and PostGIS for data exchange, visual checking and operational deployment.

Instructor-led demonstrations are followed by structured lab work using a realistic terrain and watershed case. Each participant develops a documented GRASS GIS analysis project containing an organised GIS database, processing commands, terrain derivative layers, a hydrological model, a weighted suitability analysis and export-ready maps. The final day focuses on turning that project into a reusable workflow, with parameters, quality checks and an implementation plan that can be adapted to the participant's own data and organisational standards.

The course is suited to practitioners who already work with spatial data and need stronger command of open-source geoprocessing for terrain-intensive projects. It is particularly valuable where analysis must be reproducible, auditable and practical to run across large datasets.

Course objectives

By the end of this course, participants will be able to:

• Configure GRASS GIS locations, mapsets, computational regions and raster resolutions for controlled analysis
• Import, inspect and standardise DEM, vector and tabular datasets using GRASS GIS and GDAL/OGR
• Condition elevation models by identifying sinks, null cells, projection issues and edge effects
• Generate slope, aspect, curvature, shaded-relief and topographic-position rasters with appropriate parameters
• Delineate flow direction, flow accumulation, drainage networks and watershed boundaries using r.watershed tools
• Build transparent multi-criteria suitability models with raster map algebra, reclassification and weighted overlays
• Automate a repeatable terrain-processing sequence with GRASS GIS command scripts and parameter documentation
• Produce a validated terrain-analysis project package with maps, metadata, processing steps and quality checks

Benefits of attending

Target competencies

Who should attend

• GIS Analysts — who need reproducible terrain and hydrology workflows beyond standard desktop GIS tools
• Geospatial Data Scientists — who prepare elevation-derived variables for environmental models and spatial decision systems
• Remote Sensing Analysts — who must convert DEM and imagery products into validated terrain information
• Environmental Consultants — who assess catchments, erosion, habitat terrain conditions or development constraints
• Civil and Infrastructure Planners — who need defensible slope, drainage and route-screening evidence
• Open-Source GIS Administrators — who support GRASS GIS, QGIS and spatial-data processing environments

Requirements and prerequisites

Participants should already be comfortable with core GIS concepts: coordinate reference systems, raster and vector data, attribute tables, map layers and basic spatial analysis. Previous experience in QGIS, ArcGIS Pro or another desktop GIS is expected, along with the ability to manage files and folders on a Windows, macOS or Linux workstation. Familiarity with DEMs, contour data or environmental datasets is helpful but not essential. No prior GRASS GIS experience, programming experience, advanced mathematics or remote-sensing classification knowledge is required. Participants should be prepared to work with command syntax as well as graphical GIS tools.

Training methodology

The instructor introduces each method through live GRASS GIS demonstrations, then participants reproduce and adapt it in guided labs using a shared watershed and terrain dataset. Exercises progress from database setup and DEM quality checks to hydrological modelling, raster-based suitability analysis and automation. Short technical reviews compare parameter choices, resolution effects and validation evidence. Participants receive individual feedback while building their own organised project workspace. The final workshop converts the completed analysis into a documented workflow and application plan for a current organisational use case.

Course outline

Day 1: GRASS GIS foundations and elevation data control

• GRASS GIS architecture: locations, mapsets, search paths and temporal workspace discipline
• Coordinate reference systems and projection checks for terrain-analysis projects
• Computational region settings, raster resolution and their analytical consequences
• Importing DEM, contour, vector and CSV data with r.in.gdal, v.in.ogr and db modules
• Raster and vector metadata inspection using r.info, r.univar, v.info and attribute queries
• Data exchange between QGIS, GDAL/OGR and GRASS GIS map layers
• DEM quality assessment for voids, null cells, units, artefacts and vertical interpretation

Workshop: Participants create a structured GRASS GIS project, import a supplied DEM and reference datasets, set an appropriate region, and produce a data-quality inventory.

Day 2: Terrain derivatives and surface characterisation

• DEM conditioning choices: filling depressions, preserving channels and managing boundary effects
• Slope and aspect generation with r.slope.aspect and interpretation of output units
• Profile, tangential and mean curvature for landform and flow analysis
• Hillshade, multidirectional relief and colour-relief visualisation with r.relief and r.colors
• Topographic position, local relief and neighbourhood analysis using r.neighbors and map algebra
• Reclassification of terrain variables into operational thresholds with r.reclass
• Resolution sensitivity testing and visual validation against contours and imagery

Workshop: Participants derive and validate a terrain-characterisation layer set, then create a slope and landform constraint map for a proposed development area.

Day 3: Hydrological terrain modelling

• Hydrological assumptions behind flow direction, flow accumulation and drainage extraction
• Depression handling and least-cost flow concepts using r.fill.dir and r.watershed
• Flow accumulation, stream initiation thresholds and drainage-network extraction
• Watershed and subcatchment delineation from pour points and outlet locations
• Stream-vector creation and network refinement with r.stream.extract and v.clean
• Topographic wetness and erosion-related terrain indicators using raster map algebra
• Hydrological model validation against mapped streams, culverts and field reference data

Workshop: Participants delineate a catchment and stream network for a supplied outlet, compare threshold scenarios, and document the selected hydrological parameters.

Day 4: Geoprocessing and multi-criteria spatial modelling

• Raster map algebra with r.mapcalc for transparent conditional and weighted models
• Preparing vector constraints and proximity surfaces with v.buffer and r.grow.distance
• Rasterising vector criteria and aligning categorical and continuous input layers
• Suitability scoring, standardisation and reclassification of environmental criteria
• Weighted-overlay design, exclusion masks and Boolean decision rules
• Zonal statistics and area summaries for candidate sites using r.stats.zonal and r.report
• Sensitivity testing and uncertainty communication for suitability outputs

Workshop: Participants build a documented site-suitability model that combines slope, drainage proximity, land-cover constraints and protected-area exclusions.

Day 5: Automation, QA and operational delivery

• GRASS GIS command-line execution and module parameter capture
• Bash and Python workflow patterns for repeatable GRASS GIS processing
• Batch processing multiple DEM tiles, regions or catchments
• Quality-assurance checks for projection, extent, cell size, null values and output ranges
• Exporting GeoTIFF, GeoPackage and styled outputs for QGIS and enterprise GIS users
• Metadata, processing logs and reproducibility documentation for technical review
• Performance considerations for large rasters, memory settings and computational regions

Workshop: Participants package their final terrain and suitability workflow with scripts, parameter notes, QA checklist, exported maps and a workplace application plan.

Tools & standards covered

GRASS GIS, QGIS, GDAL/OGR, PostGIS

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions