Geoprocessing is a framework and set of tools for processing geographic and related data, with a comprehensive suite of tools that can be used to perform spatial analysis or manage GIS data in an automated way.
Building workflows in ArcGIS Pro allows energy professionals to automate complex spatial analyses—from pipeline route optimization to renewable energy site selection—by connecting multiple geoprocessing tools into repeatable, documented processes.
Key Points
-
ModelBuilder is a visual programming language for building geoprocessing workflows that automate and document spatial analysis and data management processes
-
Python is the scripting language of ArcGIS, with ArcPy providing access to all geoprocessing tools as well as additional functions and classes
-
A model is a visual representation of a workflow in which several geoprocessing tools are run in sequence, with the output from one tool often serving as input to another tool
-
ArcGIS Pro's Task Framework offers a powerful way to streamline geoprocessing workflows, automate repetitive tasks, and enhance team collaboration
- Workflows can be shared as packages or services, enabling teams to standardize analysis procedures across projects
Understanding Geoprocessing Workflows
A typical geoprocessing tool performs an operation on a dataset such as a feature class, raster, or table, and creates a resulting output dataset—for example, the Buffer tool takes features as input, creates buffer areas around the features to a specified distance, and writes those buffer areas to a new output dataset.
When energy companies need to perform complex spatial analyses—such as identifying optimal locations for solar installations or analyzing pipeline corridors—they rarely use just one tool. Instead, they chain multiple tools together into workflows.
Models are workflows that string together sequences of geoprocessing tools, feeding the output of one tool into another tool as input, and ModelBuilder can be thought of as a visual programming language for building workflows.
This approach is particularly valuable in the energy sector, where analysts frequently repeat similar analyses across different regions or time periods. Rather than manually running each tool with specific parameters every time, a workflow automates the entire sequence.
A model is a map of a workflow—just like you can navigate a map in ArcGIS, you can navigate a model using ModelBuilder.
The visual nature of ModelBuilder makes workflows easier to understand, document, and share with colleagues who may not have programming experience.
How It Works
Building geoprocessing workflows in ArcGIS Pro can be accomplished through three primary methods:
1. ModelBuilder (Visual Programming)
On the Analysis tab, in the Geoprocessing group, click ModelBuilder to open a new blank model that is created in your project's default toolbox.
The process involves several steps:
Add Data and Tools:
Drag layers from the map Contents and datasets from Project into the model, where they are added as input data variables.
To add a geoprocessing tool, make sure the model view is active, then start typing to search for a tool—a list of search results will display on the Add Tools To Model dialog box, and you can double-click a tool to add it to the model.
Connect Elements:
Connect the data variables you added to the model directly to a tool by drawing a connection between them, then choose the tool parameter to which to connect the variable, and you can connect the output of one tool as input to another tool.
Configure Parameters:
Double-click a geoprocessing tool in the model to open the tool and modify the tool parameters—after specifying all required parameters, click OK (the tool does not run when you click OK; it only saves the tool settings).
Set Model Parameters:
Variables that are set as model parameters show as tool parameters when the model is run as a geoprocessing tool, allowing you to specify different data or values for your model to process than what was specified when the model was created—right-click any variable in the model and select Parameter to make the variable a model parameter.
Run the Model:
Click the Run button on the ModelBuilder tab to run the entire model, and while the tools are running, a progress window appears to indicate which tool is running and any messages.
2. Python Scripting with ArcPy
ArcGIS includes a Python API, ArcPy, that provides access to all geoprocessing tools as well as additional functions and classes, and specialized modules that help you automate GIS tasks, and you can write scripts that use ArcPy in conjunction with a diverse set of functionality provided through Python standard and third-party libraries.
You can run Python commands and scripts with ArcGIS Notebooks, in the Python window, through script tools, or you can run Python outside of ArcGIS Pro—however you run Python, commands work fundamentally the same way and use the same geoprocessing tools.
Python scripts can be used to automate repetitive tasks in GIS workflows, and ArcPy includes several functions to create lists of datasets.
This approach offers greater flexibility than ModelBuilder for complex logic, conditional operations, and integration with external data sources.
3. Task Framework (Guided Workflows)
Many ArcGIS Pro workflows include a repeated set of steps, often run in a similar order by a similar user type or persona—a task is a set of pre-configured steps that guide you and others through a workflow or business process, and can be used to implement a best practice workflow, improve the efficiency of a workflow, or create a series of interactive tutorial steps.
The Task Framework supports automating geoprocessing models—tasks can run complex ModelBuilder workflows, adapt based on user input or intermediate results through conditional logic for dynamic workflows, and advanced users can embed Python scripts for additional automation.
Why It Matters
Geoprocessing workflows are essential for energy sector applications where spatial analysis must be repeated consistently across multiple projects or datasets. Energy companies use these workflows for pipeline route analysis, transmission line siting, renewable energy resource assessment, and environmental impact studies.
Energy utilities develop automated geoprocessing scripts and ETL pipelines using Python/ArcPy, ModelBuilder, and REST APIs to build and maintain integrations between GIS and systems such as SAP, Oracle, ADMS, SCADA, and other operational systems.
Built for reuse, models are a perfect way to explore and test what-if scenarios—like scripts, models are encapsulated workflows that once created, can be used over and over as a fast alternative to manually performing all the individual steps in a workflow.
This repeatability is crucial in the energy sector, where analysts often need to evaluate multiple site alternatives or update analyses as new data becomes available. By documenting workflows in ModelBuilder or Python scripts, organizations ensure that analytical methods remain consistent across teams and projects, supporting regulatory compliance and quality assurance requirements.
Related Terms
ArcPy:
A Python API that provides access to all geoprocessing tools as well as additional functions and classes, and specialized modules that help you automate GIS tasks
Model Parameter:
Variables that are set as model parameters show as tool parameters when the model is run as a geoprocessing tool, allowing you to specify different data or values for a model to process than what was specified when the model was created
Geoprocessing Tool:
A tool that performs an operation on a dataset such as a feature class, raster, or table, and creates a resulting output dataset
Frequently Asked Questions
What's the difference between ModelBuilder and Python for building workflows?
ModelBuilder provides a drag-and-drop visual programming environment, allowing users to automate geoprocessing tasks without any coding experience.
Python scripting offers unparalleled flexibility and power for automation in ArcGIS Pro, allowing users to script complex processes and integrate third-party libraries, automate workflows within or outside of ArcGIS Pro, and customize GIS operations for unique project needs—however, Python has a steeper learning curve, making it ideal for advanced users requiring custom solutions.
ModelBuilder is best for straightforward sequential workflows, while Python excels at complex logic, batch processing, and integration with external systems.
Can I share my geoprocessing workflows with colleagues?
You can share models in various ways—if you share it as a project package (.ppkx file), the package will include the model, the map view, and all the project data, and if you share it as a geoprocessing package (.gptx file), the package will include only the geoprocessing tool and sample input and output data layers.
Geoprocessing workflows (both Python-based and ModelBuilder-based) can also be published as geoprocessing services to enable request-based processing, which can provide other automation avenues.
How are geoprocessing workflows used in the energy sector?
Energy companies use geoprocessing workflows for site selection analysis, infrastructure planning, environmental monitoring, and regulatory compliance.
Geospatial technology, especially GIS, helps the energy industry capture and use spatial data with the right geographic context to plan, build, inspect, and optimize energy infrastructure, and by combining GIS mapping with reliable GIS datasets, teams can maintain accurate digital maps for everything from site selection and environmental monitoring to asset health and grid performance across transmission and distribution networks.
Workflows automate repetitive analyses such as calculating solar radiation potential, identifying pipeline corridors that avoid sensitive areas, or assessing transmission line viewsheds.
Last updated: May 22, 2026. For the latest energy news and analysis, visit stakeandpaper.com.
