Processing of LiDAR laz files to create Canopy Height Model and generate trees and bushes shapefiles for biomass estimation

LiDAR-Based Biomass Analysis (LiDAR-biomass)

Project Overview

This project provides a solution to estimate biomass area based on vegetation analysis using LiDAR data. The script processes LiDAR .laz data to create a Canopy Height Model and generate trees and bushes shapefiles, allowing for an accurate assessment of biomass.

Features

• Processing LiDAR data using CloudCompare from terminal (silent mode)
• Differentiating between trees and bushes based on height data
• Calculating the area covered by trees and bushes

Prerequisites

Before running the script, ensure you have CloudCompare installed

Usage

The process involves several steps, starting with LiDAR data processing in CloudCompare and followed by further analysis and shapefile generation.

1. CloudCompare Steps:

   • Export coordinates to SFs
   • Apply SOR, Noise and Cloth Simulation Filter (CSF)
   • Rasterize ground and off-ground points

2. Python Workflow:

   • Generate a Canopy Height Model
   • Perform raster calculations
   • Extract and dissolve cells for bushes and trees coverage
   • Calculate the area and generate the final shapefiles

Output

• Bushes coverage shapefile
• Trees coverage shapefile