Five LiDAR Software Tools: From Flight Planning to Classification
- Flai
- 3 days ago
- 2 min read
LiDAR (Light Detection and Ranging) has become a cornerstone in geospatial data collection—used for everything from forestry and agriculture to urban planning and archaeology. But raw point cloud data isn’t useful on its own. To unlock its value, you need the right software tools across every stage of the workflow: planning, processing, visualization, and classification.
UgCS – Flight Planning and Mission Control
Use case: Pre-flight mission planning and drone route optimization.
UgCS (Universal ground Control Software) is a popular tool for planning drone-based LiDAR missions. It supports terrain-following routes, customizable scan patterns (like serpentine or double-grid), and precise control of UAV flight paths. UgCS is especially handy when working in hilly or forested environments, where maintaining consistent altitude above ground is crucial.
Why it matters: Accurate flight planning directly affects data quality. UgCS helps ensure optimal point density and overlap before a drone even takes off.
LAStools – Preprocessing
Best for: Filtering, tiling, thinning, and cleaning raw point clouds
Platform: Windows (command line + GUI)
LAStools is a fast and lightweight toolbox for wrangling raw LiDAR data, especially LAS/LAZ formats. It’s ideal for the initial steps: stripping out noise, classifying ground points, and compressing gigantic datasets without losing precision.
Highlights:
lasground, lasnoise, and lasclassify handle early-stage processing.
Extremely fast due to native C++ implementation.
Can be chained into batch scripts for large-scale processing.
Potree – Web-based Point Cloud Visualization
Use case: Sharing and viewing large point clouds online.
Potree is an open-source viewer that lets you render massive point clouds directly in the browser using WebGL. It’s ideal for sharing results with clients or stakeholders without requiring them to install heavy desktop software.
Highlights:
Handles billions of points smoothly
Custom measurement tools and annotations
Easily embeddable in websites
It's not a processing tool, but when you need to showcase LiDAR data interactively, Potree shines.
CloudCompare – Desktop Visualization and Analysis
Use case: Manual inspection, comparison, and lightweight editing.
CloudCompare is a free and open-source 3D point cloud processing software that supports a wide range of file formats. It’s often used for visualizing and analyzing point clouds, computing distances, or performing basic classification and segmentation.
Standout features:
2.5D profile tools
Distance computation between clouds (e.g., before/after scans)
Plugins for additional processing steps
FLAI – AI-powered Classification
Use case: Automated point cloud classification using machine learning.
FLAi focuses on one thing: smart classification. It uses AI models trained on specific use cases (e.g., vegetation detection, power line mapping, urban segmentation) to rapidly classify LiDAR data.
Benefits:
Custom model training for specific environments
API integration for automation
High accuracy with minimal manual input
FLAi is particularly useful when traditional rule-based classification hits its limits, such as in complex or noisy datasets.
No single software tool covers the entire LiDAR workflow, but the right combination can make your job a lot easier:
Plan your mission with UgCS
Preprocessing with LAStools
Visualize results using Potree or CloudCompare
Classify intelligently with Flai
Whether you're a seasoned geospatial analyst or just dipping your toes into LiDAR, these tools form a solid foundation for building a reliable, efficient workflow.
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