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TreeCreate

TreeCreate is a tool for generating synthetic tree files with procedural parameters and random seeds. It can create individual trees or entire forests for testing, algorithm development, and research purposes.

Usage

Single Tree Generation

treecreate tree <seed> [options]

Forest Generation

treecreate forest <seed> [options]
  • <seed>: Random seed (0-100) for reproducible generation

Tree Generation Options

Basic Parameters

  • --random_factor <value> or -r <value>: Degree of randomness (0-100, default: 0.25)
  • --max_trunk_radius <value> or -m <value>: Maximum trunk radius in meters (default: 0.2)

Forest Generation Options

Forest Structure

  • --width <value> or -w <value>: Width of square forest section in meters (default: 20)
  • --dimension <value> or -d <value>: Scaling exponent for tree distribution (default: 2.0)
  • --tree_density <value> or -t <value>: Number of mature trees per m² (default: 0.01)

Tree Properties

  • --max_trunk_radius <value> or -m <value>: Maximum trunk radius in meters (default: 0.2)
  • --random_factor <value> or -r <value>: Degree of randomness in construction (default: 0.25)

Examples

Single Tree Creation

Generate a simple tree:

treecreate tree 42

Create a tree with specific trunk radius:

treecreate tree 15 --max_trunk_radius 0.3

Generate a highly random tree:

treecreate tree 7 --random_factor 0.8

Forest Creation

Generate a default forest:

treecreate forest 123

Create a dense forest plot:

treecreate forest 50 --width 30 --tree_density 0.02

Generate a sparse, large forest:

treecreate forest 99 --width 100 --tree_density 0.005

Create forest with large trees:

treecreate forest 33 --max_trunk_radius 0.4 --dimension 2.5

Generation Parameters

Random Factor

Controls the variability in tree generation:

  • Low values (0.1-0.3): More regular, geometric trees
  • Medium values (0.3-0.6): Balanced natural appearance
  • High values (0.6-1.0): Highly irregular, organic forms

Tree Density

Forest density in trees per square meter:

  • Sparse (0.001-0.005): Open woodland
  • Medium (0.005-0.015): Typical forest
  • Dense (0.015-0.050): Dense forest or plantation

Dimension Parameter

Controls tree size distribution (higher = more small trees):

  • Low (1.5-2.0): More uniform tree sizes
  • Medium (2.0-2.5): Natural size distribution
  • High (2.5-4.0): Many small trees, few large ones

Output Files

Single Tree

  • Filename: tree.txt
  • Content: Single tree with full branch structure

Forest

  • Filename: forest.txt
  • Content: Multiple trees with realistic spatial distribution

Generated Tree Attributes

Each generated tree includes:

  • Spatial coordinates (x, y, z)
  • Branch radii and segments
  • Parent-child relationships (topology)
  • Realistic branch angles and lengths
  • Natural tapering from trunk to branches

Procedural Generation Features

Biological Realism

  • Realistic branch angle distributions
  • Natural tapering ratios
  • Appropriate branch length relationships
  • Botanically plausible structures

Structural Diversity

  • Variable branching patterns
  • Different tree heights and shapes
  • Diverse crown architectures
  • Natural variation in trunk sizes

Applications

Algorithm Testing

  • Generate consistent test datasets
  • Create controlled experimental conditions
  • Test processing algorithms on known structures

Research and Development

  • Prototype tree analysis methods
  • Validate measurement techniques
  • Generate training data for machine learning

Educational Purposes

  • Demonstrate tree structure concepts
  • Provide example datasets for tutorials
  • Support forestry education

Benchmarking

  • Create standardized test cases
  • Compare different analysis methods
  • Validate reconstruction algorithms

Reproducibility

Using the same seed and parameters guarantees identical output:

treecreate forest 42 --width 25 --tree_density 0.01

This ensures reproducible results across different runs and systems.

Integration

Generated trees work seamlessly with other treetools:

  • Process with treeinfo for statistics
  • Visualize with treemesh or treerender
  • Modify with treeprune, treesmooth, etc.
  • Analyze growth with treegrow

Parameter Guidelines

For Testing

  • Use consistent seeds for reproducibility
  • Start with default parameters
  • Adjust one parameter at a time

For Realism

  • Use random_factor 0.2-0.4
  • Set appropriate tree_density for ecosystem type
  • Match max_trunk_radius to target species

For Performance Testing

  • Large forests: increase width and density
  • Simple structures: reduce random_factor
  • Complex trees: increase random_factor

Additional Information

  • Minimum branch radius is fixed at 0.01m
  • Branch angle distributions use biological lookup tables
  • Forest generation includes realistic spatial clustering
  • For more detailed information on generation algorithms, refer to the TreeCreate source code at treetools/treetools/treecreate/treecreate.cpp.