GIS Mapping for Energy Projects Training Course

Participants can select and manage coordinate systems suitable for energy project datasets.

• Geographic and projected coordinate systems distinguished for project mapping
• WGS 84, UTM zones and national grids selected appropriately
• Datums, ellipsoids and coordinate transformations checked before spatial overlay
• Linear, areal and positional accuracy requirements defined for project decisions
• Projection distortions assessed for long corridors and regional site studies
• Coordinate reference system documentation recorded within project metadata

Participants can design a structured geodatabase for an energy project study.

• Vector, raster and tabular data models matched to project needs
• Feature classes designed for assets, constraints, corridors and candidate sites
• Attribute domains and coded values standardised for reliable analysis
• Unique identifiers linked across engineering, environmental and land datasets
• Relational tables used for inspections, permits and stakeholder records
• File geodatabases and GeoPackages compared for project data exchange

Participants can evaluate source data and document its suitability for project use.

• Authoritative datasets identified from regulators, operators and national mapping agencies
• Satellite imagery, elevation models and open datasets assessed critically
• ISO 19115 metadata elements captured for spatial dataset traceability
• Source scale, date, resolution and licensing reviewed before use
• Fitness-for-purpose tests applied to screening, design and compliance decisions
• Data inventory created with owners, update cycles and access restrictions

Participants can detect and correct common spatial data errors before analysis.

• Topology rules defined for parcels, corridors, assets and exclusion zones
• Gaps, overlaps, duplicates and invalid geometries identified systematically
• Attribute completeness and value consistency tested using validation rules
• Positional discrepancies investigated against imagery and authoritative basemaps
• Quality-control logs record corrections, unresolved issues and responsible owners
• ISO 19157 quality measures applied to positional and attribute data

Participants can produce clear maps tailored to technical and executive audiences.

• Visual hierarchy directs attention toward decisions, risks and recommended options
• Symbology distinguishes proposed assets, existing infrastructure and restricted areas
• Classification methods selected for resource, cost and impact variables
• Labels, annotation and callouts clarify engineering features without clutter
• Map layouts include scale, projection, source notes and revision controls
• Map series generated for corridors, parcels and distributed project assets

Participants can create usable spatial features from drawings, imagery and scanned maps.

• Control points selected for georeferencing scanned plans and legacy maps
• Root mean square error interpreted during image rectification
• Heads-up digitising captures roads, facilities, waterways and disturbance areas
• Snapping, tracing and editing tools maintain accurate feature boundaries
• Engineering drawings aligned with aerial imagery and coordinate reference systems
• Digitised features attributed using controlled project data dictionaries

Participants can answer project location questions using core vector analysis methods.

• Attribute queries isolate assets, land parcels and regulated receptors
• Buffer distances model setbacks around communities, waterways and infrastructure
• Intersect operations identify overlap between candidate sites and constraints
• Union and erase tools produce usable exclusion and opportunity areas
• Spatial joins summarise receptors, land cover and population indicators
• Selection by location tests proximity, containment and crossing relationships

Participants can build and explain a weighted suitability model for energy siting.

• Decision criteria separated into factors, constraints and non-negotiable exclusions
• Analytic Hierarchy Process supports transparent weighting of suitability factors
• Raster reclassification converts mixed source variables into common suitability scores
• Weighted overlay combines resource, terrain, access and grid criteria
• Sensitivity analysis tests the effect of alternative weights and thresholds
• Suitability outputs documented with assumptions, limitations and decision implications

Participants can assess landform and water-related constraints for project planning.

• Digital elevation models prepared for terrain and drainage analysis
• Slope, aspect and hillshade derived for engineering site assessment
• Flow direction and accumulation identify drainage pathways and crossings
• Watershed boundaries delineated for catchment and erosion considerations
• Viewshed analysis assesses visual exposure of energy infrastructure
• Terrain profiles compare grades along access roads and corridors

Participants can compare infrastructure access and connectivity using network-based methods.

• Euclidean distance measures proximity to roads, substations and demand centres
• Cost distance models incorporate slope, land cover and crossing penalties
• Least-cost paths identify preliminary corridor alternatives between fixed endpoints
• Network datasets calculate travel times for construction and maintenance access
• Service areas identify asset coverage from depots and response facilities
• Route alternatives compared using distance, constraints and crossing counts

Participants can select suitable satellite data for defined energy project questions.

• Electromagnetic spectrum bands related to vegetation, water and built surfaces
• Spatial, spectral, temporal and radiometric resolution compared for project tasks
• Sentinel-2 and Landsat imagery selected for land monitoring purposes
• Synthetic aperture radar interpreted for cloud-prone areas and ground change
• Image acquisition dates matched to seasonal conditions and project baselines
• Cloud cover, shadows and atmospheric effects assessed before interpretation

Participants can prepare imagery and derive spectral indicators for project analysis.

• Radiometric correction improves comparability between imagery acquisition dates
• Atmospheric correction converts raw values into surface reflectance estimates
• Image mosaics assembled with matching projections, extents and pixel sizes
• Normalized Difference Vegetation Index identifies vegetation condition and disturbance
• Normalized Difference Water Index highlights surface water and wet areas
• Raster masking restricts analysis to project boundaries and study zones

Participants can create and assess a land-cover classification for energy studies.

• Training samples selected across representative land-cover classes and conditions
• Supervised classification separates vegetation, water, bare ground and built areas
• Random Forest classification applied to multispectral imagery predictor bands
• Post-classification filtering removes isolated pixels and obvious classification noise
• Confusion matrices calculate producer, user and overall accuracy measures
• Reference samples documented for classification review and future updates

Participants can identify and communicate spatial change relevant to project controls.

• Multi-date imagery aligned before detecting land-cover and construction changes
• Image differencing highlights vegetation loss, earthworks and surface-water changes
• Post-classification comparison quantifies transitions between land-cover categories
• Time-series indices track vegetation recovery near project infrastructure
• Change polygons prioritised by magnitude, location and environmental sensitivity
• Monitoring maps distinguish confirmed change from imagery artefacts and uncertainty

Participants can integrate spatial factors into preliminary renewable energy site screening.

• Solar irradiation surfaces combined with slope, aspect and shading constraints
• Wind resource layers screened against terrain, setbacks and aviation restrictions
• Grid connection distance assessed alongside substation capacity information
• Land tenure, protected areas and settlements incorporated into exclusion models
• Candidate polygons ranked using suitability scores and minimum-area thresholds
• Screening results separated from detailed engineering resource assessments clearly

Participants can develop preliminary corridor options and compare their spatial implications.

• Fixed endpoints, route constraints and engineering avoidance zones established
• Least-cost corridor analysis identifies broad route zones before alignment design
• Crossings inventoried for rivers, roads, railways and existing utilities
• Right-of-way widths modelled against parcels, settlements and sensitive habitats
• Route segments scored for constructability, access and permitting complexity
• Alternative corridors compared through transparent criteria and map evidence

Participants can map environmental and social constraints for early project risk assessment.

• Protected areas, critical habitat and wetlands mapped as environmental constraints
• Community receptors, cultural sites and livelihood areas incorporated responsibly
• Constraint buffers aligned with permit conditions and project-specific commitments
• Cumulative impacts screened using nearby infrastructure and disturbance footprints
• Sensitive receptors ranked by significance, proximity and potential exposure
• Constraint registers linked to maps, sources and mitigation actions

Participants can design field-data workflows that update project GIS records reliably.

• Field forms designed for assets, observations, photos and inspection findings
• Required attributes, coded lists and validation rules reduce collection errors
• Global positioning system accuracy settings matched to field-data requirements
• Offline basemaps support surveys in remote project locations
• Photo attachments linked to features using identifiers and coordinates
• Field updates synchronised with master datasets through review controls

Participants can package spatial findings for controlled sharing and decision review.

• Web map layers configured with appropriate symbology, filters and access controls
• Interactive dashboards communicate project status, constraints and monitoring indicators
• Static map exports prepared for reports, permits and investment committees
• Version control records dataset changes, map revisions and analytical decisions
• Data governance assigns stewardship, approval rights and retention periods
• Technical notes state methods, sources, uncertainty and recommended follow-up

Participants can build, review and present a complete GIS analysis package for an energy project decision.

• Project brief translated into datasets, criteria, analytical steps and deliverables
• Geodatabase assembled with documented projections, attributes and source metadata
• Suitability, constraint and corridor analyses produced from stated assumptions
• Map series prepared for technical review and executive decision discussion
• Peer review tests analytical logic, data quality and communication clarity
• Final presentation defends findings, limitations, risks and recommended actions