GIS ModelBuilder Applications Training Course

Participants can prepare dependable datasets and workspace structures for model execution.

• File geodatabases, feature classes and raster datasets organised for processing
• Coordinate systems checked before distance, area and overlay operations
• Attribute fields profiled for nulls, types, domains and coding consistency
• Data paths replaced with project-relative and parameterised references
• Scratch workspaces separated from approved outputs and source datasets
• Naming conventions applied to intermediate data and final deliverables

Participants can construct and run a basic multi-tool ModelBuilder process.

• Geoprocessing tools added from toolboxes into a blank model canvas
• Connectors define data flow between variables and processing tools
• Buffer, Clip and Dissolve combined into a basic analysis chain
• Tool dialogs configured through model elements and exposed parameters
• Intermediate outputs marked to control storage and model readability
• Model validation identifies missing inputs and incompatible parameter values

Participants can create user-ready models with controlled input and output parameters.

• Model variables created for datasets, values, expressions and outputs
• Parameters exposed to users through the geoprocessing pane interface
• Default values set for distances, fields, workspaces and output names
• Data types selected to prevent invalid user inputs
• Parameter filters restrict feature classes, field types and value lists
• Descriptions and labels written for operational model users

Participants can automate common vector analysis procedures in reusable models.

• Intersect and Union chosen for different overlay analysis questions
• Spatial Join configured for proximity, containment and attribute transfer
• Buffer distances parameterised for service, hazard and exclusion zones
• Select Layer By Location automates rule-based feature screening
• Near and Generate Near Table measure nearest-feature relationships
• Dissolve statistics summarise selected features by operational categories

Participants can automate attribute-based data preparation and record selection.

• Select Layer By Attribute applies SQL expressions within models
• Make Feature Layer preserves selection logic for downstream tools
• Add Join and Join Field transfer tabular information reliably
• Calculate Field applies Python expressions to derived attributes
• Summary Statistics produces grouped counts, totals and descriptive measures
• Field mappings control retained, renamed and aggregated output fields

Participants can construct automated raster processing chains for spatial analysis.

• Raster properties inspected for cell size, extent, bands and value range
• Extract By Mask limits analysis to approved study boundaries
• Resample and Project Raster standardise analytical raster inputs
• Reclassify converts continuous values into defined decision classes
• Raster Calculator combines map algebra expressions with model variables
• Processing extent and snap raster settings control alignment

Participants can build a transparent weighted suitability model from multiple criteria.

• Decision criteria defined from policy rules, constraints and stakeholder needs
• Common measurement scales established through raster reclassification rules
• Weighted Overlay combines ranked criteria using documented percentage weights
• Constraint masks exclude protected, unsafe or unsuitable locations
• Sensitivity tests compare alternative weights and threshold assumptions
• Suitability classes translated into candidate areas for further review

Participants can configure models that process multiple datasets without manual repetition.

• Iterate Feature Classes processes datasets within selected workspaces
• Iterate Rows applies repeated actions to records in tables
• Iterate Field Values supports category-specific processing and outputs
• Inline variable substitution creates unique names from iterator values
• Batch inputs controlled through workspace filters and naming patterns
• Output collision rules prevent accidental overwriting during repeated runs

Participants can control execution order and conditional paths within a model.

• Preconditions prevent tools running before required inputs become available
• If Then Else branches workflows using defined Boolean conditions
• Calculate Value creates dynamic values from expressions and scripts
• Parse Path extracts workspace, filename and extension components
• Collect Values assembles multiple datasets for multivalue tool inputs
• Dependency chains reviewed to identify unnecessary serial processing

Participants can configure execution environments that produce reproducible spatial outputs.

• Processing extent fixed to study boundaries and approved analysis areas
• Output coordinate system specified for consistent downstream measurements
• Cell size, mask and snap raster aligned for raster comparability
• XY tolerance and resolution considered for precision-sensitive vector operations
• Overwrite output settings governed by controlled production procedures
• Parallel processing factors assessed against available computing resources

Participants can diagnose ModelBuilder failures and verify that outputs meet specifications.

• Validate Model identifies broken paths, missing tools and invalid parameters
• Geoprocessing history examined for messages, warnings and execution duration
• Intermediate datasets inspected to isolate failing workflow stages
• Test cases cover empty selections, null values and missing fields
• Error messages classified as data, environment, permission or tool issues
• Expected outputs compared against control maps and attribute checks

Participants can document models for review, reuse and controlled maintenance.

• Model metadata records purpose, owner, version and approved use
• Input specifications define source, format, currency and quality requirements
• Assumptions documented for thresholds, weights, exclusions and classifications
• Output specifications state fields, coordinate system and acceptance criteria
• Change logs record amendments, reasons, tester and release date
• Peer review checklists examine logic, parameters, labels and documentation

Participants can improve model execution time and manage processing outputs efficiently.

• Processing bottlenecks identified using tool messages and execution timings
• Spatial indexes assessed before repeated spatial selection and overlay tasks
• In-memory workspaces considered for small temporary vector datasets
• Early filtering reduces unnecessary records before expensive analysis steps
• Intermediate output deletion managed without losing diagnostic evidence
• Chunked processing planned for large rasters and enterprise datasets

Participants can extend ModelBuilder processes with targeted Python and ArcPy components.

• Export Python Script converts model logic into readable ArcPy code
• Calculate Value executes short Python expressions within workflows
• Script tools expose custom ArcPy functions through ModelBuilder parameters
• arcpy.env settings mirror geoprocessing environment controls in scripts
• Python paths, packages and project environments managed for portability
• Visual models retained when custom scripting adds unnecessary maintenance

Participants can prepare completed models for controlled sharing and operational use.

• Toolboxes organised with categories, aliases and user-facing tool names
• Model packages bundle tools, data references and supporting documentation
• Project packages prepared for colleagues using shared ArcGIS Pro resources
• Scheduled execution requirements assessed for recurring operational workflows
• Permissions and data access checked before team-wide model distribution
• Deployment plans define ownership, support routes and update responsibilities

Participants can assemble a documented land suitability workflow from policy and spatial criteria.

• Site selection requirements translated into constraints and scored criteria
• Protected areas, flood zones and slopes processed as exclusion layers
• Road access and utility proximity converted into suitability scores
• Weighted criteria combined through an auditable raster model
• Candidate parcels extracted, ranked and summarised for decision review
• Model outputs checked against planning rules and source data dates

Participants can design operational models for risk screening and service accessibility analysis.

• Catchment areas derived from distance, travel-time and network assumptions
• Asset proximity models identify facilities exposed to mapped hazards
• Population and customer data aggregated within defined service zones
• Risk scores calculated from exposure, vulnerability and hazard indicators
• Exception reports identify locations failing service or risk thresholds
• Output tables structured for operational dashboards and management reports

Participants can review a model against technical, operational and governance criteria.

• Workflow logic reviewed against stated analytical questions and business rules
• Parameters tested with plausible high, low and boundary values
• Data lineage traced from source layers to final output datasets
• Independent reviewers reproduce results using documented inputs and settings
• User feedback converted into prioritised model improvement actions
• Release criteria defined before models enter routine operational use

Participants can build, review and present a complete documented ModelBuilder workflow for an operational GIS requirement.

• Problem statement defines users, decisions, inputs and required outputs
• Workflow diagram maps preparation, analysis, quality checks and delivery
• ModelBuilder process incorporates parameters, environments and controlled outputs
• Test data demonstrates normal, boundary and failure-case model behaviour
• Documentation records assumptions, source data, ownership and maintenance actions
• Peer review assesses reproducibility, usability, performance and analytical validity
• Presentation explains model decisions, results and workplace implementation plan