FOSS4G-Asia 2023 Seoul

The interdisciplinary nature of forest ecology requires a seamless integration of traditional ecological methods with advanced computational tools. With this in mind, we introduce "skye-vision," an open-source collection of Python libraries specifically curated to bridge the gap in the Python ecosystem for forest ecologists. By leveraging remote sensing, photogrammetry, and machine learning, these libraries offer researchers an extensive toolkit for in-depth forest structure analysis.

Noteworthy functionalities of Skye-Vision are:
1. Advanced Visualization: Capability to generate and visualize detailed point clouds and meshes, offering insight into forest morphology.
2. Structural Analysis: Tools to quantify forest attributes, including leaf area index, leaf area density, plant volume density, foliage height diversity, and canopy cover.
3. Hemispherical Image Processing: Techniques for converting 360-degree images into hemispherical photos, enriching the study of forest canopies and their defining metrics.
4. Data Access & Processing: Simplified workflows for downloading and processing LiDAR data from GEDI and street-level imagery from Mapillary.

While the primary focus of Skye-Vision is forest ecology, the flexibility of these libraries ensures applicability in a wider context. For instance, their utility extends to ground truthing in various ecosystems or analyzing urban environments for optimizing shade-rich pathways, thereby aiding urban planning and conservation.

In this presentation, we'll provide a comprehensive exploration of Skye-Vision’s capabilities. Beyond its primary application in forest ecology, we will discuss potential extensions into other research domains. Attendees will gain insights into the library’s functionalities, its contributions to current research methodologies, and its potential for advancing both academic and practical projects. As we emphasize the spirit of FOSS4G, Skye-Vision exemplifies the collaborative and transformative power of open-source endeavors in the scientific community.