Download LP360 Quick Sheets to Support your LiDAR and Imagery Processing
During our recent LP360 User Conference, we introduced a new set of LP360 Quick Sheets: concise, easy-to-follow resources designed to help you get the most out of your favorite LP360 features. These handy one-pagers quickly became a conference favorite, giving users step-by-step workflows, helpful visuals, and time-saving tips to make daily LiDAR and imagery processing even more efficient.
Now, we’re making them available online so everyone can take advantage of them! Whether you’re refining your point cloud classification, working with imagery, or exploring new tools, the LP360 Quick Sheets are the perfect reference to keep at your desk or in the field.
Browse and download the LP360 Quick Sheets below to elevate your workflow.
1. Auto AI Ground Classification
This Quick Sheet explains how to use LP360’s AI Ground Classification Add-On, a cloud-based deep learning model that automatically classifies ground and non-ground points within a point cloud. It highlights setup requirements, advantages over traditional methods, and optional preprocessing parameters like outlier detection, smoothing, and tiling for improved results.
2. Building Extraction in LP360
This guide walks through the Building Extraction workflow using LP360’s Point Cloud Tasks (PCTs). It covers thinning the dataset, ground classification, running the Building Filter, and applying the Building Extractor to create building polygons. It also includes tips for processing dense datasets and reviewing results in Feature Analyst.
This Quick Sheet details how to use the Ground Cleanup Tool to refine and correct areas missed during initial ground classification. It explains both manual and assisted cleanup modes, execution methods (by layer, polygon, or feature), and cleanup intensity options. The tool integrates with LP360’s AI Ground Classification workflow to deliver more accurate terrain models.
This sheet introduces the Immersive Image Explorer, a feature within the LP360 Immersive Viewer that provides a street-level view of point cloud data synchronized with imagery. It explains how to navigate between geo images and street-view images, toggle visual layers, and inspect data interactively for immersive inspection and analysis.
5. Powerline Extraction in LP360
This guide outlines how to use the Powerline Extractor PCT to classify and vectorize power line catenaries. It includes recommended preparation steps like ground classification, data cleaning, and feature path creation. Users can execute the tool by line or by feature layer and perform vegetation encroachment analysis to identify clearance issues.
6. Processing DJI L1/L2 in LP360
This Quick Sheet demonstrates how to process DJI Zenmuse L1 or L2 LiDAR data directly in LP360, eliminating the need for DJI Terra. It explains how to import raw or processed missions, create flight lines, perform post-processing, and optionally align strips or generate orthomaps for enhanced accuracy and visualization.
7. Processing Wingtra in LP360
This resource explains the workflow for processing Wingtra LiDAR data within LP360. It covers importing LAS and trajectory files, creating flight lines, and performing post-processing. Optional steps include colorizing point clouds, generating orthomosaics, and aligning data with the Strip Align and Surface Precision tools.
This Quick Sheet explains the Rail Extractor PCT, which automatically detects and extracts rail centerlines and classifies rail tops from raw LAS data. It details parameter setup, including rail width, spacing, and void spaces, and provides guidance for executing the tool by line or feature layer to ensure precision in rail mapping projects.
This guide provides an overview of SLAM Processing for handheld sensors like the TrueView GO. It covers trajectory processing, geocoding modes (SLAM, GNSS, RTK, PPK), and optional post-processing and LAS registration methods. It’s ideal for users processing indoor, outdoor, or mixed-environment handheld LiDAR data.
10. Tree Segmentation in LP360
This Quick Sheet focuses on the Tree Segmentation tool, used to identify and measure individual trees within a LiDAR dataset. It explains parameter setup, segmentation thresholds, and output formats. The tool produces a new LAS layer and attribute file (CSV or shapefile) showing tree ID, location, height, and canopy area.
11. Volumetric Analysis in LP360
This Quick Sheet explains how to perform Volumetric Analysis in LP360 using the Volumetric Analysis Point Cloud Task (PCT). It provides a step-by-step workflow for importing LAS data, preparing boundaries, and configuring task settings to calculate cut, fill, or combined volumes. The guide also highlights how this tool can be applied for stockpile measurements, earthwork calculations, and change detection over time, with output options including shapefiles, LAS files, and colorized rasters.
Download these LP360 Quick Sheets to assist with your LiDAR and imagery processing workflows. Each sheet provides a concise, step-by-step reference to help you make the most of LP360’s powerful tools and features. If there’s a specific workflow or feature you’d like to see added to the collection, please contact [email protected] our team is happy to help.