ArcGIS Fundamentals Training Course

Participants can identify, assign and transform coordinate systems for reliable spatial alignment.

• Geographic coordinate systems, datums and ellipsoids distinguished from projected systems
• Coordinate reference system properties inspected through layer and map metadata
• Projection selection based on area, distance, direction and jurisdiction requirements
• Define Projection used only for datasets with known missing references
• Project tool transforms vector datasets between documented coordinate reference systems
• Datum transformation choices checked against source and target geographic coordinate systems

Participants can bring common operational and geographic datasets into an ArcGIS project.

• CSV, Excel and delimited tables imported with controlled field types
• XY Table To Point creates point features from coordinate columns
• Shapefiles, GeoJSON and KML converted for managed geodatabase storage
• Feature services and web layers added through portal connections
• Source metadata recorded for ownership, currency, scale and positional accuracy
• Field names, null values and character encoding checked before analysis

Participants can design a file geodatabase that supports controlled editing and analysis.

• File geodatabase structure organised through feature datasets and feature classes
• Attribute schemas designed with appropriate field types, lengths and aliases
• Coded value domains standardise repeated categories and data-entry values
• Subtypes separate feature classes with different business rules
• Relationship classes link assets, inspections and reference tables through keys
• GlobalIDs and editor tracking support identification and audit requirements

Participants can create and correct spatial features while applying basic quality controls.

• Create Features constructs points, lines and polygons using templates
• Snapping settings maintain shared boundaries and connected network features
• Modify Features tools reshape, split, merge and move existing geometry
• Attribute Rules apply calculation, constraint and validation logic
• Topology rules identify overlaps, gaps, dangles and duplicate geometry
• Error Inspector reviews topology exceptions and documented correction decisions

Participants can manage attributes and connect operational tables to mapped features.

• Attribute tables filtered, sorted and inspected for completeness and anomalies
• Calculate Field applies Arcade and Python expressions to attribute values
• Joins connect features to tabular records through common identifiers
• Relates preserve one-to-many links between features and inspection records
• Summary Statistics produces grouped counts, totals, averages and minimum values
• Field mapping controls output schemas during append, merge and export

Participants can design clear map displays that match the purpose and audience.

• Single symbol, unique values and graduated symbols communicate feature categories
• Natural Breaks, quantile and equal interval classifications compared critically
• Colour ramps selected for sequential, diverging and qualitative data
• Symbol hierarchy distinguishes primary evidence from contextual reference layers
• Label classes apply scale ranges, expressions and placement priorities
• Transparency, masking and feature weights reduce clutter in dense maps

Participants can produce print and digital map layouts with essential map elements.

• Layout templates establish page size, orientation and organisational presentation requirements
• Map frames, legends, scale bars and north arrows configured appropriately
• Dynamic text inserts titles, dates, sources, scale and coordinate references
• Inset maps provide location context for detailed operational study areas
• Visual hierarchy directs attention toward findings, constraints and decision areas
• PDF and image exports configured for print, reports and presentations

Participants can isolate records using structured attribute queries and selection methods.

• SQL expressions select records using operators, wildcards, dates and null values
• Definition queries limit displayed records without changing source datasets
• Select By Attributes identifies records meeting stated business conditions
• Selection sets saved as layers for repeatable review and mapping
• Summarised selections reveal counts and totals by administrative category
• Query logic checked through record inspection and expected-result comparisons

Participants can select and measure features based on their spatial relationships.

• Select By Location identifies features intersecting, containing or touching target layers
• Buffer analysis defines influence zones around facilities, routes and hazards
• Multiple-ring buffers compare access bands and graduated service thresholds
• Near and Generate Near Table calculate nearest-feature distances
• Spatial Join transfers counts and attributes between related geographic features
• Geodesic distance methods chosen for regional and global datasets

Participants can combine spatial criteria to identify priorities, constraints and suitable locations.

• Clip, Erase and Intersect derive features within defined administrative boundaries
• Union and Identity preserve attributes when polygon datasets overlap
• Dissolve aggregates features using shared categories and summary statistics
• Weighted Overlay combines standardised raster criteria for suitability modelling
• Boolean constraint layers exclude protected, hazardous or inaccessible locations
• Suitability criteria documented with rationale, weights, thresholds and limitations

Participants can inspect raster datasets and select suitable imagery for mapping questions.

• Raster cells, bands, resolution and extent interpreted from dataset properties
• Spatial, spectral, temporal and radiometric resolution compared for imagery selection
• Multispectral imagery distinguished from aerial photographs and derived elevation surfaces
• Raster functions applied without permanently changing source imagery datasets
• Stretch methods improve visual interpretation of continuous pixel values
• NoData values, resampling and cell alignment checked before raster analysis

Participants can derive basic land-cover information from multispectral imagery using documented methods.

• Band combinations reveal vegetation, water, built surfaces and bare ground
• Spectral signatures compared across representative land-cover training samples
• Normalized Difference Vegetation Index calculated from near-infrared and red bands
• Supervised classification assigns pixels using labelled training data
• Confusion matrices assess classification accuracy against reference observations
• Post-classification filtering removes isolated pixels and generalises mapped classes

Participants can derive terrain measures and assess elevation-related spatial conditions.

• Digital elevation models inspected for resolution, units, voids and coverage
• Hillshade renders terrain form using azimuth and altitude settings
• Slope and aspect derive gradient and directional exposure from elevation
• Contour generation selects intervals appropriate to terrain and map scale
• Viewshed analysis identifies visible areas from observer locations
• Hydrologic flow direction and accumulation indicate probable drainage paths

Participants can describe and test basic geographic patterns in point and area data.

• Spatial autocorrelation tests whether similar values cluster geographically
• Hot Spot Analysis identifies statistically significant high-value and low-value clusters
• Kernel Density estimates concentration surfaces from event point data
• Standard deviational ellipse summarises directional distribution and geographic dispersion
• Rate normalisation distinguishes population exposure from raw incident counts
• Pattern findings interpreted with scale, aggregation and data-quality limitations

Participants can model travel-based access to facilities using network analysis concepts.

• Network datasets represent streets, turn restrictions, costs and travel directions
• Route analysis identifies shortest or fastest paths between locations
• Service Area analysis maps travel-time catchments around facilities
• Closest Facility identifies reachable services from incident or demand locations
• Location-Allocation compares facility sites against demand and travel impedance
• Travel assumptions documented for time periods, modes and road restrictions

Participants can create repeatable geoprocessing models with controlled inputs and outputs.

• Geoprocessing history records tools, parameters, environments and output locations
• Analysis environments control extent, cell size, mask and coordinate system
• ModelBuilder links tools, variables and derived outputs into workflows
• Iterators process multiple datasets, fields or feature classes systematically
• Preconditions and inline variable substitution control model execution order
• Model documentation explains purpose, inputs, assumptions and expected outputs

Participants can adapt simple ArcPy scripts to automate routine ArcGIS tasks.

• Python window executes ArcPy commands within the active ArcGIS Pro session
• ArcPy geoprocessing syntax identifies tools, parameters and result objects
• Variables, lists and loops automate repeated dataset processing steps
• Describe objects inspect dataset properties before conditional processing
• Try-except blocks capture errors and produce readable processing messages
• Script tool parameters expose controlled inputs to non-programming users

Participants can publish and manage web maps with appropriate access and content settings.

• Feature layers published from ArcGIS Pro with configured fields and symbology
• Web map configuration sets basemaps, pop-ups, bookmarks and visibility ranges
• ArcGIS Online groups organise shared content for defined user communities
• Sharing permissions distinguish private, group, organisational and public access
• Hosted feature layer views restrict fields, records and editing capabilities
• Item details document ownership, tags, descriptions, credits and use limitations

Participants can prepare decision-focused web applications and apply basic GIS governance controls.

• Instant Apps templates selected for viewing, comparison, reporting and public information
• Dashboard indicators combine maps, charts, selectors and operational metrics
• Pop-up design presents relevant attributes, media and related records clearly
• Data governance assigns owners, update cycles, retention rules and access controls
• Metadata practices record lineage, collection methods, accuracy and processing history
• Publication review checks privacy, sensitivity, accessibility and map interpretation risks

Participants can build, review and present a complete ArcGIS project addressing a defined operational decision.

• Decision question translated into spatial criteria, outputs and success measures
• Project geodatabase structured with documented fields, sources and quality controls
• Spatial analysis workflow combines queries, proximity, overlay or raster methods
• ModelBuilder process records parameters and produces reproducible analytical outputs
• Map layout and web map communicate findings, uncertainty and recommended actions
• Peer review tests assumptions, cartography, data lineage and interpretation claims