Other, UAV

DigiForests

Forestry robotics and LiDAR semantic interpretation

Longitudinal forest LiDAR collection with backpack and aerial point clouds, tree instance and stem/canopy labels, and March tree-trait measurements.

Metadata: Partial Metadata needs review

Quick facts

Vehicle type
Other, UAV
Environment
Outdoor
Data origin
Real-world
Sensor count
5
Ground truth
Available
Calibration
Not reported
Annotations
Available

Sensor overview

High-level sensor availability before the detailed sensor records below.

Ground truth

Reference scope, method, rate, coverage, and provenance.

Ground-truth references for DigiForests
Scope Method Reference system Count Rate Coverage Reference provenance
External
Measured using equipment independent of the platform’s normal onboard sensor pipeline.
Derived
Computed primarily from the dataset’s own recorded sensors.
Hybrid
Combines independent reference equipment with onboard measurements.
Not reported Other Not reported Not reported Not reported Unknown Reference provenance
External
Measured using equipment independent of the platform’s normal onboard sensor pipeline.
Derived
Computed primarily from the dataset’s own recorded sensors.
Hybrid
Combines independent reference equipment with onboard measurements.
Derived
Reference notes
Released per-plot VILENS trajectory estimates fuse LiDAR, IMU and visual odometry. Cross-season pose graph optimization aligns plots; these are derived poses with no independent trajectory accuracy established.
Other Other Not reported Not reported Not reported Partial · March 2023 Reference Trees Reference provenance
External
Measured using equipment independent of the platform’s normal onboard sensor pipeline.
Derived
Computed primarily from the dataset’s own recorded sensors.
Hybrid
Combines independent reference equipment with onboard measurements.
External
Reference notes
Manual tree species, DBH, clear-wood length, first-green-branch height and qualitative traits. AprilTags associate trees with camera detections; tags are not a trajectory reference.

Calibration and synchronization

Reported calibration level, reproducibility signals, and supporting notes.

Level
Not reported
Processed parameters
Not reported
Raw calibration data
Not reported
Calibration targets
Not reported

Calibration data

Calibration reproducibility details are not reported.

Notes

Not reported

Known or intentional limitations

Reported constraints and characteristics to check before using the dataset.

Annotation focuses on larger trees with thick stems.

Backpack motion and forest occlusions challenge LiDAR-only odometry.

Annotated coverage is uneven across seasons; tree totals count plot-session annotations rather than unique longitudinal identities.

Benchmark test labels are hidden.

Cameras

Not reported

IMUs

Not reported

GNSS

Not reported

LiDAR

Hesai XT32

Model or name
Hesai XT32
Count
1
Dimensions
3
Rate
Not reported
Channels
Not reported
Range
Not reported

Hesai QT64

Model or name
Hesai QT64
Count
1
Dimensions
3
Rate
Not reported
Channels
Not reported
Range
Not reported

Hesai QT32

Model or name
Hesai QT32
Count
1
Dimensions
3
Rate
Not reported
Channels
Not reported
Range
Not reported

Velodyne HDL-32E

Model or name
Velodyne HDL-32E
Count
1
Dimensions
3
Rate
Not reported
Channels
Not reported
Range
Not reported

Hesai XT-32M2X

Model or name
Hesai XT-32M2X
Count
1
Dimensions
3
Rate
Not reported
Channels
Not reported
Range
Not reported

Radar

Not reported

Pitot tube

Not reported

Additional sensors

Not reported

Annotations

Reported annotation availability and task support.

Availability
Available
Format
Not reported
Class count
Not reported
Semantic segmentation Available
Instance segmentation Available
Object detection Not reported
Optical flow Not reported
Depth ground truth Not reported

Citation

Citation key and BibTeX kept at the end of the page for reference.

Citation key
Not reported

BibTeX

Not reported

Dataset corrections

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