DOI: 10.5281/zenodo.15873635
title: DART-UGV-single-canopy-trees

description: This dataset was developed to investigate the optical consequences of foliage arrangement and spatial heterogeneity in tree canopies. It was generated using the DART (Discrete Anisotropic Radiative Transfer) model, a widely used radiative transfer simulator for vegetation and complex 3D environments.  

This dataset was developed to investigate the optical consequences of foliage arrangement and spatial heterogeneity in tree canopies. It contains ten synthetic tree models, each defined by a specific combination of leaf angle distribution (LAD) and clumping index (Ω), resulting in a controlled yet diverse set of canopy architectures. The configurations were carefully chosen to represent a broad spectrum of canopy structures commonly observed in agricultural orchards, ranging from well-pruned, symmetric forms to more irregular and naturally clustered crowns.  

Five standard LAD types were considered: elliptical, planophile, erectophile, plagiophile, and spherical. Each distribution was simulated both with and without spatial clumping, leading to ten structurally distinct tree models labelled A to J. This duplication enables the independent evaluation of the effects of leaf orientation and spatial aggregation on canopy optical properties.  

The resulting configurations provide realistic examples of tree crowns, from dense, horizontally oriented foliage to vertically aligned sparse canopies. This diversity allows researchers to assess the sensitivity of radiative transfer models to key structural parameters and to validate optical simulations under controlled, reproducible conditions. Potential applications include the evaluation of algorithms for retrieving biophysical parameters—such as leaf area index (LAI) and leaf area density (LAD)—from simulated LiDAR data and other optical measurements.  

The following table summarises the parameters used in each configuration, including the distribution type, weight factors (w_min, w_max), empirical parameters (α, β), canopy scaling factors (C2, C3), projected leaf area, and total leaf area:  

| Tree | Distribution | w_min | w_max | α      | β    | C2 [m] | C3 [m] | Tree LA [m²] | Leaf area [m²] ||------|-----------------------|------------|-------------|--------:|------:|----------:|----------:|----------------------:|-------------------------|| A    | Elliptical        | 0.50     | 0.50      | 0.25 | 55  |   1.50 |   0.65 |         3.26         | 3.0 × 10⁻³         || B    | Elliptical        | 0.10     | 0.70      | 0.40 | 55  |   0.65 |   1.50 |         2.35         | 3.0 × 10⁻³         || C    | Planophile    | 0.90     | 0.10      | 0.05 | 55  |   1.50 |   0.65 |         1.31         | 1.0 × 10⁻³         || D    | Planophile    | 0.10     | 0.70      | 0.40 | 55  |   0.65 |   1.50 |         2.87         | 1.0 × 10⁻³         || E    | Erectophile   | 0.50     | 0.40      | 0.25 | 55  |   1.50 |   0.65 |         0.65         | 4.0 × 10⁻³         || F    | Erectophile   | 0.10     | 0.60      | 0.40 | 55  |   0.65 |   1.50 |         1.96         | 4.0 × 10⁻³         || G    | Plagiophile   | 1.00     | 0.00      | 0.00 |  0   |   1.50 |   0.65 |         3.00         | 2.0 × 10⁻³         || H    | Plagiophile   | 0.90     | 0.10      | 0.05 | 55  |   0.65 |   1.50 |         4.57         | 2.0 × 10⁻³         || I     | Spherical       | 0.40     | 0.40      | 0.25 | 55  |   1.50 |   0.65 |         6.53         | 1.0 × 10⁻³         || J    | Spherical       | 0.10     | 0.40      | 0.40 | 55  |   0.65 |   1.50 |         9.14         | 1.0 × 10⁻³         |

Each of the ten tree folders (A–J) has the same internal organisation:

A (example)├── data/                          # Raw simulation outputs│   ├── abs2local/                 # Transformations between absolute and local frames│   │   ├── sequencer_0.txt│   │   ├── sequencer_1.txt│   │   └── ... sequencer_60.txt│   ├── voxels.txt                 # Voxelised representation of the canopy│   ├── whole_pointcloud_0p1.txt   # Full canopy point cloud (0.1 m radio)│   ├── whole_pointcloud_0p2.txt   # Full canopy point cloud (0.2 m radio)│   ├── whole_pointcloud_0p3.txt   # Full canopy point cloud (0.3 m radio)│   ├── whole_pointcloud_0p4.txt   # Full canopy point cloud (0.4 m radio)│   └── whole_pointcloud_0p5.txt   # Full canopy point cloud (0.5 m radio)│├── ground_truth/                  # Reference parameters for validation│   ├── canopy_LAD.txt             # Leaf angle distribution values│   ├── canopy_LAD.png             # Leaf angle distribution plot│   ├── canopy_LAI.txt             # Leaf area index values│   ├── canopy_LAI.png             # Leaf area index plot│   └── canopy.png                 # Structural rendering of the canopy│└── sequence/                      # Scan-wise simulation outputs    ├── sequencer_0/               # Virtual scan position 0    │   └── output/    │       ├── augmented_point_cloud.txt   # Point cloud enriched with attributes    │       ├── DetectedPoints.txt          # List of detected LiDAR returns    │       ├── treeReport.txt              # Per-scan canopy metrics    │       └── treesDescriptionFile.txt    # Structural descriptors of the scanned tree    ├── sequencer_1/    │   └── output/ (same structure as above)    └── ... up to sequencer_60/

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UAV Altitude: 1.6 [m]Sample Frequency: 5 [Hz]Horizontal resolution: 1024 @360°Vertical Resolution: 128 layers @90°Wavelength: 865 [nm]Echoes: 2