Advanced ArcGIS Pro Applications Training Course

Participants can diagnose coordinate system issues and apply appropriate geographic transformations.

• Coordinate reference systems selected from data extent, purpose and accuracy requirements
• Geographic transformations evaluated using source datum, target datum and area coverage
• Define Projection used only when coordinate system metadata is absent
• Project tool parameters controlled for vector, raster and enterprise datasets
• Vertical coordinate systems examined for elevation, bathymetry and 3D analysis
• Distortion assessed through scale, area and distance measurement comparisons

Participants can design geodatabase schemas that enforce valid data entry and useful relationships.

• Feature datasets organised around shared coordinate systems and editing requirements
• Domains constrain coded values, ranges and controlled attribute entry
• Subtypes assign default values, domains and behaviour by feature category
• Relationship classes model one-to-many and many-to-many operational records
• Global IDs support attachments, replication and web feature service workflows
• Contingent values enforce valid attribute combinations during editing operations

Participants can establish editing controls and correct topological errors systematically.

• Topology rules identify gaps, overlaps, dangles and containment violations
• Error inspector prioritises topology exceptions and documented correction decisions
• Attribute rules calculate, constrain and validate values during edits
• Editor tracking records creator, editor and timestamp fields automatically
• Branch versioning supports managed edits within enterprise feature services
• Data Reviewer checks target completeness, integrity and positional consistency

Participants can integrate heterogeneous spatial and tabular sources into analysis-ready datasets.

• Field mapping standardises schema during merge, append and export operations
• Spatial joins transfer attributes using documented matching relationships
• Near and Generate Near Table quantify feature proximity relationships
• Geocoding workflows match addresses, review candidates and record match quality
• ETL sequences combine Excel, CSV, CAD, GPS and web service data
• Data interoperability tools translate formats while preserving geometry and attributes

Participants can control geoprocessing settings to produce reproducible and explainable outputs.

• Extent, mask and snap raster settings control analytical processing boundaries
• Cell size and resampling methods selected for raster analytical purpose
• Output coordinate system set explicitly for repeatable multi-source workflows
• Scratch workspace and overwrite settings managed for traceable processing
• Parallel processing factor assessed against tool behaviour and hardware capacity
• Geoprocessing history documented with parameters, inputs and output locations

Participants can build parameterised ModelBuilder workflows for repeatable GIS production.

• Model variables expose inputs, outputs and processing parameters clearly
• Iterators process feature classes, rasters and workspace contents systematically
• Preconditions sequence dependent tools and prevent invalid model execution
• Inline variable substitution creates dynamic names and output paths
• Model validation identifies broken paths, invalid parameters and missing data
• Custom model tools package documentation, symbology and user-facing parameters

Participants can write and run arcpy scripts for repeatable ArcGIS Pro processing tasks.

• ArcPy environments set workspace, extent, overwrite and coordinate settings
• SearchCursor and UpdateCursor process attributes using efficient data access
• ListFeatureClasses and ListRasters automate workspace inventory and processing
• Try-except blocks capture geoprocessing errors and produce useful logs
• Script tool parameters expose controlled inputs for non-programming GIS users
• Python toolboxes organise reusable scripts, aliases and parameter validation

Participants can prepare raster datasets and derive terrain-based analytical surfaces.

• Mosaic datasets manage large imagery collections with rules and overviews
• Raster functions apply on-the-fly processing without creating permanent outputs
• Slope, aspect and hillshade derived from digital elevation models
• Fill, Flow Direction and Flow Accumulation model drainage pathways
• Raster Calculator combines conditional statements and map algebra expressions
• Zonal Statistics summarises continuous surfaces by management or reporting zones

Participants can classify imagery and assess land-cover change using documented methods.

• Spectral profiles compare band responses across land-cover training classes
• Supervised classification uses representative training samples and class signatures
• Random Trees classification assesses predictor variables and class assignment
• Confusion matrices report producer accuracy, user accuracy and overall accuracy
• Normalized Difference Vegetation Index identifies relative vegetation condition patterns
• Change detection compares classified outputs, indices and temporal imagery composites

Participants can select and interpret spatial statistical methods for point and area data.

• Spatial weights matrices define neighbourhood relationships for statistical analysis
• Global Moran's I tests overall spatial autocorrelation across observations
• Hot Spot Analysis identifies statistically significant high and low clusters
• Local Moran's I distinguishes clusters from spatial outliers
• Kernel Density estimates intensity surfaces from incidents or observations
• Incremental Spatial Autocorrelation identifies appropriate clustering distance bands

Participants can construct transparent suitability models using weighted spatial criteria.

• Weighted Overlay combines reclassified criteria using documented relative importance
• Weighted Sum preserves continuous values during multi-criteria suitability modelling
• Reclassify converts raw measurements into transparent preference scores
• Euclidean Distance models proximity constraints around features and facilities
• Boolean exclusion masks remove prohibited areas before suitability scoring
• Sensitivity analysis tests rank changes under alternative criterion weights

Participants can model routes, service areas and allocation scenarios using network datasets.

• Network datasets represent connectivity, turns, restrictions and travel costs
• Route analysis identifies efficient multi-stop sequences under defined constraints
• Service areas model reachable populations within travel-time thresholds
• Closest Facility analysis assigns incidents to available response locations
• Location-Allocation models test facilities, demand points and capacity assumptions
• Traffic data and time-dependent costs refine operational routing scenarios

Participants can create 3D scenes and assess vertical spatial relationships.

• Local scenes support detailed site analysis with projected coordinate systems
• Global scenes display large-area data using geographic coordinate systems
• Extrusion symbolises heights, capacities and quantitative attribute values
• Multipatch features represent buildings, structures and complex three-dimensional assets
• Line of Sight assesses visibility between observer and target locations
• Viewshed analysis identifies terrain-visible areas from proposed observation points

Participants can produce decision-ready maps that communicate analytical findings accurately.

• Classification methods selected using distribution, audience and analytical intent
• ColourBrewer principles guide sequential, diverging and qualitative colour schemes
• Symbol hierarchy establishes visual priority among operational map elements
• Label classes resolve conflicts using weights, placement and scale ranges
• Map series automates indexed output for districts, assets or survey areas
• Layout elements document sources, methods, dates, scale and limitations

Participants can prepare and publish governed ArcGIS content for web-based use.

• Web feature layers configured with editing, sync and ownership settings
• Map image layers publish cartography and server-side rendering capabilities
• Hosted versus referenced layers selected from data governance requirements
• Sharing groups control access for internal teams and external partners
• Metadata standards document lineage, quality, use constraints and stewardship
• Item details record credits, tags, summaries and authoritative status

Participants can assemble web GIS products that support operational monitoring and decisions.

• Web maps combine operational layers, reference layers and pop-up configuration
• Arcade expressions calculate display values and conditional symbology dynamically
• ArcGIS Dashboards connect indicators, charts, lists and map selections
• Selectors filter dashboard elements through categories, dates and geographic extent
• Instant Apps configure focused public or internal mapping applications
• Operational views separate editing layers from decision-support presentation layers

Participants can diagnose performance problems and apply quality assurance controls before release.

• Spatial indexes improve query performance for large vector feature classes
• Attribute indexes support frequent filters, joins and definition queries
• Generalisation methods reduce geometry complexity while preserving intended shape
• Scale ranges limit drawing load for dense operational layers
• Quality assurance plans define acceptance criteria, sampling and error thresholds
• Peer review checks methods, assumptions, outputs and publication settings

Participants can document GIS work to meet governance, reproducibility and risk requirements.

• ISO 19115 metadata elements record identification, lineage and quality information
• Data dictionaries define fields, codes, units and permissible values
• Method statements record analytical purpose, parameters and decision rules
• Privacy controls assess location disclosure, aggregation and access restrictions
• Version control conventions preserve approved scripts, models and project artefacts
• Uncertainty statements distinguish measured results, estimates and analytical assumptions

Participants can build, review and present a complete ArcGIS Pro decision product from source data to published findings.

• Problem statement defines users, decisions, criteria and measurable analytical questions
• Data inventory assesses source authority, currency, quality and usage constraints
• Geodatabase schema applies domains, relationships, topology and metadata controls
• ModelBuilder or arcpy workflow documents repeatable transformation and analysis steps
• Analytical outputs combine spatial evidence, validation results and stated limitations
• Web map, dashboard or layout communicates findings for defined decision users
• Peer review tests reproducibility, cartographic clarity and governance compliance
• Presentation explains methods, results, recommendations and residual analytical risks