The Maximum On Ground (MOG) Calculation Toolbox is a custom ArcGIS Python toolbox designed to optimize the parking layout of Air Mobility Command (AMC) aircraft on military airfields. The toolbox leverages ArcGIS's geoprocessing capabilities, powered by ArcPy, to calculate the maximum number of aircraft that can be parked on a given airfield while considering real-world constraints such as airfield dimensions, taxiway widths, and aircraft specifications.
This tool is tailored for airfield operators, planners, and decision-makers, enabling them to make data-driven decisions about parking configurations that maximize efficiency and operational effectiveness.
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Standard and Rotated Parking Configurations
- Automatically evaluates both standard and rotated parking layouts to determine the most efficient configuration.
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Advanced Settings
- Allows users to manually specify airfield dimensions, taxiway widths, and other parameters for custom scenarios.
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Use Advanced AI
- Offers an optional Genetic Algorithm Optimization feature to provide AI-enhanced solutions for aircraft parking.
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Data Validation
- Built-in error handling to ensure input data integrity and guide users when errors are detected.
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Customizable Outputs
- Generates feature classes showing parking layouts and constraint areas.
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User-Friendly Integration
- Packaged as a Python toolbox (.pyt), making it easy to use within the ArcGIS Pro interface.
- ArcGIS Pro (Required)
- Must be installed with an active license.
- Python 3.14
- Included with ArcGIS Pro; ensure the ArcGIS Pro Python environment is active.
- ArcPy
- Part of the ArcGIS Pro Python environment; no separate installation is needed.
- Standard Python Libraries
- Includes
os,math,traceback, andrandom.
- Includes
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Clone the Repository
git clone https://github.com/MarvenCesar/arcGISToolBox.git
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Add the Correct Toolbox to ArcGIS Pro
- Open ArcGIS Pro.
- In the Catalog Pane, right-click Toolboxes > Add Toolbox.
- Navigate to the downloaded
MOGTools.pytfile and add it to your project.
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Configure Inputs
- Ensure your input data, such as airfield layers and aircraft tables, are ready and accessible.
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Locate the Toolbox
- In the Catalog Pane, navigate to the toolbox and open the tool named Calculate Maximum On Ground.
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Input Parameters
- Input Aircraft Table: Select the table containing aircraft specifications.
- Airfield Layer: Choose the airfield polygon layer.
- Select Aircraft (MDS): Select a specific aircraft model designation (MDS).
- Enable Advanced Settings: (Optional) Check this box to provide manual airfield dimensions and taxiway widths.
- Use Advanced AI Feature: (Optional) Check this box to enable AI-based optimization using a genetic algorithm.
- Output Locations: Specify paths for output feature classes.
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Execute the Tool
- Click Run. The tool will process the inputs and generate results based on your configuration.
- Aircraft Positions Feature Class:
- Displays the calculated positions of parked aircraft on the airfield.
- Constraint Polygons Feature Class:
- Highlights restricted areas based on aircraft dimensions and taxiway requirements.
- Input Aircraft Table: A table containing aircraft specifications such as length and wingspan.
- Airfield Layer: A feature class representing the airfield geometry.
- Select Aircraft (MDS): Dropdown to select a specific aircraft type.
- Enable Advanced Settings: Allows manual input of airfield dimensions and taxiway widths.
- Use Advanced AI Feature: Enables the genetic algorithm for AI-optimized parking configurations.
- Ensure the airfield layer uses a projected coordinate system with linear units (e.g., feet or meters).
The Use Advanced AI Feature checkbox activates a genetic algorithm to optimize parking configurations. This feature iteratively evaluates potential solutions to find the most efficient layout for aircraft parking, particularly useful for complex airfield layouts and constraints.
- Test individual methods such as
calculate_taxiway_widthsandcalculate_parking_available.
- Validate the interaction between ArcPy and Python toolbox logic.
- Perform end-to-end tests by running the tool with various input datasets to ensure outputs meet expectations.
- Fork this repository.
- Create a branch for your feature or bug fix.
- Test your changes in ArcGIS Pro.
- Submit a pull request with a detailed explanation of your changes.
We welcome contributions that improve functionality, usability, or documentation.
Copyright [2024] [Marven Cesar, Alain Padron, Izzat Omar, Bruno De Nadai Mundim, Kyle Moore]
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
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Marven Cesar (Interface developer) [email protected]
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Bruno De Nadai Mundim (AI-specialist) [email protected]
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Alain Padron (Interface developer) [email protected]
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Izzat Omar (Interface developer) [email protected]
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Kyle Moore (AI-specialist) [email protected]
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GitHub Issues: MOG Calculation Toolbox Issues
Special thanks to:
- The ArcGIS team for providing robust geoprocessing tools.
- Contributors and testers for refining this toolbox.
- Our sponsors, Department of Defense Air Force for their ongoing support and sponsorship.
This toolbox enhances airfield efficiency through advanced GIS and AI techniques, ensuring optimal space utilization and operational planning.