Research Methodology

Methods & Protocols

Transparent procedures and research methods for analysing urban trees, environmental conditions and planning scenarios

6 Methods 5 Guidelines Peer-Reviewed

Method categories

All Methods Data Acquisition Tree Representation Calibration & Validation Quality Assessment Guidelines Modeling & Simulation

Showing 6 methods

Protocol Available

PAD Calculation from Different LiDAR Sources

Method for deriving plant area density (PAD) or similar structural tree parameters from various LiDAR-based sources.

Input data
  • Terrestrial or airborne LiDAR point clouds
  • Tree location coordinates
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Output produced

Plant area density profiles, crown structure parameters

Key input factors
Scanner type Metadata LiDAR beauty scenarios
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Protocol Available

Turbulence Modelling Parameters Calibration

Procedure for calibrating turbulence-related modelling parameters for simulations involving trees and urban airflow.

Input data
  • Field measurement data
  • Wind profile observations
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Output produced

Calibrated turbulence parameters for CFD models

Key input factors
Microclimate models CFD simulation
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Protocol Available

Tree Library for Generic Trees

Reusable library of generic tree representations for modelling and scenario demonstrations.

Input data
  • Species characteristics
  • Growth shape templates
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Output produced

Parameterized generic tree models

Key input factors
Urban greenery Research validation
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Protocol Available

Tree Reconstruction Algorithm

Algorithmic method for reconstructing tree geometry and structure from available input data.

Input data
  • LiDAR scans or imagery
  • Tree basic geometry data
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Output produced

3D tree geometry, structural parameters

Key input factors
Scenarios Digital-twin techniques
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Protocol Available

Tree Representation from Different Sources

Guidance on converting different source data types into usable tree representations for modelling.

Input data
  • Various inventory, imagery, LiDAR, proxy data
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Output produced

Standardized tree model inputs

Key input factors
Data sources Models Data categories
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Protocol Available

Input-Output Quality Correlation

Method for understanding how input data quality influences output reliability in tree-related simulations.

Input data
  • Multiple data quality levels
  • Model outputs
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Output produced

Plant area density profiles, crown structure parameters

Key input factors
Scenarios Data relations Quality ranges
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Work Package 6

Methods and guidelines

developed as part of the research programme

Set of Improved Methods

LiDAR-based PAD calculation, turbulence calibration, tree libraries and reconstruction algorithms.

6 Research Methods View Methods

Implementation Guidelines

Best practices for tree representation, quality assessment and responsible output interpretation.

6 Research Methods View Methods