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A practical course on spatial data processing, analysis, and workflow automation using ArcGIS geoprocessing tools and ModelBuilder. Participants learn how to structure analytical processes, automate recurring tasks, and create reusable models for processing larger geospatial datasets.
You will become familiar with the fundamental concepts and functions of geoprocessing and use suitable ArcGIS tools for spatial analysis and data modelling. With ModelBuilder, you will combine several processing steps into clear, repeatable, and reusable workflows.
You will also work with variables, parameters, and iterators, export models to Python, and receive a practical introduction to scripting with ArcPy.
By the end of the course, you will be able to plan geoprocessing tasks systematically, automate them with ModelBuilder, and understand and adapt simple Python scripts as a foundation for more advanced automation.
• Select and use suitable geoprocessing tools for spatial tasks
• Configure geoprocessing options and environment settings
• Automate linear analysis and processing workflows with ModelBuilder
• Connect tools, data, and intermediate results within a model
• Use variables, model parameters, and preconditions
• Process collections of datasets automatically using iterators
• Test, document, and share models with other users
• Export ModelBuilder models to Python
• Apply the fundamentals of Python and ArcPy to geoprocessing tasks
• Basic knowledge of ArcGIS Desktop or ArcGIS Pro
• Experience working with layers, feature classes, attribute tables, and geodatabases
• A basic understanding of spatial data and simple GIS analyses
• No programming experience is required
*We customize the course outline and content to your specific needs and relevant use cases.
Module 1: Overview of Geoprocessing in ArcGIS
• Purposes and typical applications of geoprocessing
• How tools, ModelBuilder, and Python scripts work together
• Geoprocessing in ArcGIS Pro and ArcGIS Desktop
• Understanding input, output, and intermediate data
• Distinguishing spatial and attribute-based processing tasks
• Finding suitable tools for different requirements
• Reviewing results and documenting processing steps clearly
Module 2: Fundamentals of Geoprocessing Tools
• Structure and operation of geoprocessing tools
• Input parameters, optional parameters, and output data
• Working with feature classes, tables, and raster data
• Selection, analysis, conversion, and data-management tools
• Running individual tools and checking their results
• Interpreting processing messages, warnings, and errors
• Using geoprocessing history for recurring tasks
Module 3: Options and Environment Settings
• Purpose of geoprocessing environments
• Defining current and temporary workspaces
• Setting coordinate systems and output projections
• Controlling the processing extent and spatial resolution
• Using cell size, snap raster, and masks for raster analysis
• Managing the overwriting of existing outputs
• Applying environment settings at tool, model, and project level
• Assessing how different settings affect analytical results
Module 4: Introduction to ModelBuilder
• Structure and interface of ModelBuilder
• Adding tools and data to a model
• Connecting processes and variables
• Distinguishing input, output, and intermediate variables
• Validating and running models
• Managing and automatically deleting intermediate results
• Testing individual model processes
• Saving, naming, and documenting simple models
Module 5: Automating Linear Workflows
• Connecting multiple tools into an end-to-end process
• Defining dependencies and processing sequences
• Using the output of one tool as the input for another
• Selecting, analysing, converting, and storing data
• Using preconditions to control execution
• Distinguishing temporary and permanent results
• Identifying errors in model workflows systematically
• Creating models for recurring spatial analyses
Module 6: Variables and Model Parameters
• Using data, value, and environment variables
• Creating, renaming, and editing variables
• Applying dynamic values to file names and paths
• Using inline variable substitution
• Defining inputs and settings as model parameters
• Publishing models as custom geoprocessing tools
• Organising parameter order and user inputs
• Using default values and optional parameters
Module 7: Iteration and Batch Processing
• Automating repeated processing steps with iterators
• Processing every feature class within a workspace
• Iterating through feature datasets, files, tables, or rasters
• Filtering datasets by name or properties
• Generating dynamic outputs for each iteration
• Understanding nested and multi-stage processing
• Using collection tools and multivalue inputs
• Testing batch processes and checking their results
Module 8: Optimising and Sharing Models
• Structuring models for clarity and maintainability
• Using meaningful names, labels, and groups
• Adding descriptions and help information
• Optimising intermediate data and storage requirements
• Identifying and resolving common model errors
• Copying, adapting, and reusing models
• Organising models within toolboxes
• Sharing automated workflows with other users
Module 9: Exporting Models to Python
• Understanding the differences between visual models and scripts
• Exporting ModelBuilder models as Python code
• Reviewing the structure of the generated code
• Identifying tool calls, parameters, and variables
• Adjusting paths and input data in the exported script
• Understanding the limitations of automatically generated code
• Using models as a starting point for more advanced scripts
Module 10: Introduction to Python and ArcPy
• Applications of Python within ArcGIS
• Basic syntax, variables, and data types
• Python scripts and notebook environments in ArcGIS Pro
• Calling geoprocessing tools with ArcPy
• Using parameters and outputs in scripts
• Understanding simple conditions and loops
• Listing and processing datasets within workspaces
• Producing messages and handling errors in scripts
• Starting points for developing further workflow automation
Module 11: Practical Project – An Automated Geoprocessing Workflow
• Dividing a typical spatial analysis into individual steps
• Selecting suitable tools and environment settings
• Creating a complete workflow in ModelBuilder
• Defining parameters and dynamic variables
• Processing multiple datasets with an iterator
• Checking results and correcting errors
• Sharing the model as a geoprocessing tool
• Exporting the model to Python and reviewing the resulting code
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