Datasets to consider

[dokterbob]

Here's some datasets which could be great to include:

• TreeSatAI-Time-Series, OmniSat, Guillaume et. al., 2024
• PureForest "This dataset includes 135,569 patches, each measuring 50 m x 50 m, covering a cumulative exploitable area of 339 km². Each patch represents a monospecific forest, annotated with a single tree species label."
• Hauser et. al., 2024, An Open Benchmark Dataset for Forest Characterization from Sentinel-1 and -2 Time Series "The dataset encompasses labels, including tree count, crown area, tree types (deciduous, coniferous, dead), mean crown volume, base height, tree height, and forested area proportion per pixel."
• BAMFORESTS "BAMFORESTS contains 27,160 labelled trees in 105 hectares of three different AOIs in Bavarian forests and city parks"

[bw4sz]

Thanks for your message. I saw the email, haven't had a moment to respond. BAMFOREST is already in there. I'll look into the others, but this benchmark is for individual tree detection/segmentation, which it doesn't really look like https://www.mdpi.com/2072-4292/16/3/488 has. It looks like they created individual tree labels by algorithm.