IDTReeS 2020 Competition: Geospatial Data for Individual Tree Crowns

Data from the IDTReeS Competition includes vector data of Individual Tree Crown boundaries identified by researchers. The dataset was generated by Sarah Graves, Sergio Marconi, and Benjamin Weinstein, with support from Stephanie Bohlman, Ethan White, and the IDTReeS group. It incorporates multiple NEON data products from 2020, including high-resolution orthorectified camera imagery, LiDAR point clouds, woody plant vegetation structure, and ecosystem structure data.

Use Cases

• Mapping tree locations and sizes based on remote sensing data mentioned in the description
• Training models for tree species identification using the provided geospatial and field data
• Testing the generalization of tree detection methods to other forest ecosystems as described
• Analyzing ecosystem structure using the combined LiDAR and camera imagery data products

Strengths

• Data originates from the National Ecological Observatory Network (NEON), a major ecological monitoring program
• Includes multiple high-quality data products: orthorectified imagery, LiDAR point clouds, vegetation structure, and ecosystem structure
• Designed for a specific data science competition, suggesting a curated task focus

Limitations

• Row count, file formats, and column-level documentation are unknown, limiting suitability assessment
• Last update date is unknown; freshness unverified
• Data may reflect geographic or temporal bias inherent to the specific NEON sites and collection date

Provenance

Source

National Ecological Observatory Network (NEON) data products, packaged by the IDTReeS research group

Collection Method

Selected, downloaded, and packaged from NEON's provisional data portal on March 4, 2020

Time Range

Data products are from 2020, with a download date of March 4, 2020

Geography

Coverage is likely forests within the NEON observatory network, though specific locations are not detailed