Presentation Information
[PPS03-P09]Functionally Expansion of PyAiGIS
*Wataru Izawa1, Naru Hirata1 (1.The University of Aizu)
Keywords:
Small bodies,Python,Jupyter Notebook
Small bodies are difficult to analyze due to their irregular shape. The conventional Geographic Information System (GIS) is a powerful tool for integrating and analyzing surface data for major planets with spherical bodies. However, conventional GIS software is unsuitable for irregular-shaped bodies since it only supports geographic coordinates (latitude and longitude) for spherical bodies that are unavailable as unique identifiers on the irregular shaped bodies. To address this, 3D-GIS tools like AiGIS and Small Body Mapping Tool (SBMT) were developed to represent the shapes of small bodies using polygon models. These tools enable researchers to analyze map data (e.g., gravitational elevation and slope) assigned to each polygon ID. While these tools are highly capable, research efficiency and flexibility are limited because these are standalone applications.
PyAiGIS [1] (repository: https://github.com/AiGIS-PyAiGIS/PyAiGIS) was developed as a Python module to address the limitation of these standalone applications designed for analysis and visualization of irregular-shaped bodies. It provides flexible research environment through Jupyter Notebook. PyAiGIS provides seamless integration with Python scientific modules. The current version of PyAiGIS following functions; visualize 3D shape models, visualize map data on the shape model and project an image map with the equirectangular map projection onto the surfaces. PyAiGIS also allows users to click on the shape model to place markers and extract 3D coordinates, which can then be used to define lines or circles on the shape model surface. In addition, a function has been implemented to extract map data along the path of these defined lines or circles.
In this study, the functionality of PyAiGIS was significantly expanded to enhance analytical versatility. The main contributions of this study include raw image projection using camera frustum, pixel value extraction, interactive object editing capabilities, and two additional methods for map data extraction.
The function for raw image projection using camera frustum allows researchers to analyze not only an image map with the equirectangular map projection that are mosaics by combining multiple images, but also single frame images obtained directly by a camera and preserving original metadata (e.g., incidence, emission, and phase angles) in PyAiGIS. Moreover, the function for pixel value extraction was implemented to analyze these projected images. These functions create an environment for image-based analysis in PyAiGIS.
To improve workflow efficiency, interactive object editing capabilities—including drawing, deleting, and re-drawing markers, lines, and circles—were implemented.
The addition of two map data extraction methods provides higher flexibility for various research needs. This allows users to choose between raw data fidelity and smoothed spatial profiles depending on their specific scientific objectives.
These enhancements transition PyAiGIS from a visualization-oriented module to a robust, programmable 3D-GIS platform, enabling highly reproducible and automated workflows for small-body exploration.
[1] Hirata et al. (2025) Latest Updates on AiGIS2/PyAiGIS: Enhancing Geographic Visualization and Analysis for Irregular-Shaped Small Bodies, LPSC 56, #1873.
PyAiGIS [1] (repository: https://github.com/AiGIS-PyAiGIS/PyAiGIS) was developed as a Python module to address the limitation of these standalone applications designed for analysis and visualization of irregular-shaped bodies. It provides flexible research environment through Jupyter Notebook. PyAiGIS provides seamless integration with Python scientific modules. The current version of PyAiGIS following functions; visualize 3D shape models, visualize map data on the shape model and project an image map with the equirectangular map projection onto the surfaces. PyAiGIS also allows users to click on the shape model to place markers and extract 3D coordinates, which can then be used to define lines or circles on the shape model surface. In addition, a function has been implemented to extract map data along the path of these defined lines or circles.
In this study, the functionality of PyAiGIS was significantly expanded to enhance analytical versatility. The main contributions of this study include raw image projection using camera frustum, pixel value extraction, interactive object editing capabilities, and two additional methods for map data extraction.
The function for raw image projection using camera frustum allows researchers to analyze not only an image map with the equirectangular map projection that are mosaics by combining multiple images, but also single frame images obtained directly by a camera and preserving original metadata (e.g., incidence, emission, and phase angles) in PyAiGIS. Moreover, the function for pixel value extraction was implemented to analyze these projected images. These functions create an environment for image-based analysis in PyAiGIS.
To improve workflow efficiency, interactive object editing capabilities—including drawing, deleting, and re-drawing markers, lines, and circles—were implemented.
The addition of two map data extraction methods provides higher flexibility for various research needs. This allows users to choose between raw data fidelity and smoothed spatial profiles depending on their specific scientific objectives.
These enhancements transition PyAiGIS from a visualization-oriented module to a robust, programmable 3D-GIS platform, enabling highly reproducible and automated workflows for small-body exploration.
[1] Hirata et al. (2025) Latest Updates on AiGIS2/PyAiGIS: Enhancing Geographic Visualization and Analysis for Irregular-Shaped Small Bodies, LPSC 56, #1873.