Vertigo User Guide

Introduction

Vertigo (Vertical Error Regression Tool for Independent Ground Observations) is a Python-based tool designed for processing and analyzing LiDAR data. Particularly, it is used for evaluating the Absolute Vertical Accuracy of LiDAR data, against independently measured ground observation points.

Getting Started

Prerequisites

• Python environment with libraries: os, csv, tqdm, laspy, shapefile, numpy, pandas, geopandas.
• LiDAR data files in LAS/LAZ format.

Installation

1. Ensure all required libraries are installed.
2. Download Vertigo.py to your local system.

Usage

Loading Data

• Use laspy to load your LAS/LAZ files.
• Import the Vertigo class from Vertigo.py.

from vertigo.Vertigo import Vertigo
# Example of loading a LAS file
import laspy

las_data = laspy.read("path/to/your/file.las")

Data Analysis

• Instantiate the Vertigo class with your LiDAR data.
• Call methods provided by Vertigo for data analysis like calibration, image compositing, and change detection.

# Instantiate Vertigo
vertigo_instance = Vertigo(las_data)
# Call methods for processing
# vertigo_instance.some_method()

Reporting

• Use Vertigo's reporting features to generate insights and visualizations from your data.

# Generate report
report = vertigo_instance.generate_report()
print(report)

Advanced Usage

• For advanced users, delve into custom workflows for specific data processing needs.
• Explore integration with other data sources and machine learning algorithms for enhanced analysis.

Conclusion

Vertigo offers a comprehensive suite of tools for LiDAR data analysis, catering to both basic and advanced use cases.