The LiDAR mapping brings highly accurate models with a richness of details
CompassData UAS LiDAR Mapping is deployed through world-class technologies integrating the DJI Matrice 600 and the LiDAR sensor RIEGL VUX-1UAV.
The LiDAR mapping brings, to the CompassData’s customer, highly accurate models with a richness of details of the mapped area, allowing post-processing and interpretation of edges and limits of features with 10mm survey-grade accuracy.
Precise distances, areas, and volumes can be obtained from rural, and urban features. Buildings, constructions, cables, towers or any facility can have detailed modeling processed, as rural landscapes, vegetations, trees and crops can have their dimensions and volumes extracted
Accuracy and Details
The drone-based platform, handled by the long term drone specialists from CompassDrone team, deliveries a high qualified mapping process, safer and more efficient.
10mm grade accuracy
With 25 years in the Geospatial market, CompassData also deliveries all post-processing services promoting to the end user high-quality extractions and GIS integration. Consistent dataset are provided, to CompassData’s customers, oriented to their decision-making process, ensuring the strongest ROI.
ELECTRIC POLES AND CABLING AND TREES EXTRACTED BY THE CompassData TEAM
Digital surface Model Of A Light Aggregate Qravel Quarry Created Using LiDAR Data
Read this Case Study to find out more about recent Colorado Flood Mapping LiDAR projects that CompassData participated in.
Knowledge Base and LiDAR FAQ
What is LiDAR?
Airborne Light Detection and Ranging (LiDAR) – LiDAR is an active sensory system that uses laser light, an inertial measurement unit (IMU), and GNSS to rapidly measure distances between the sensor and points on the ground. This creates dense, highly accurate elevation data. Along with GNSS calibration sites within LiDAR collection grids that verify the GNSS, Ground Control is necessary to provide “Ground Truth” for LiDAR data analysis.
CompassData establishes and manages multi-use GNSS calibration sites for digital sensors and LiDAR, working with clients such as the National Oceanic and Atmospheric Administration (NOAA) and the United States Geological Survey (USGS).
Besides providing the GNSS and Control necessary to ensure “Ground Truth” for LiDAR projects, CompassData’s team includes post-processing professionals who have the expertise to ensure Quality Control/Quality Assurance for LiDAR deliverables.
Postprocessing from CompassData includes GNSS and IMU data, in a LiDAR LAS file. This includes all relevant LiDAR attributes: classification, intensity, return information, GNSS timestamp, flight line information, etc.
QA/QC for LiDAR
Quantitative for vertical accuracy, horizontal accuracy, clustering of points and nominal posting
Qualitative for the elevation surface (look and feel) and removal of anomalies or temporary features such as vehicles; intersecting building corners; assessing completeness; etc.
- FEMA PM61 Compliant (FEMA Procedure Memorandum No. 61: “Standards for LiDAR and Other High-Quality Digital Topography” published Sept. 27, 2010)
- USGS V13 Compliant (United States Geological Survey (USGS) LiDAR Guidelines and Base Specifications Version 13)
Digital Surface Model (DSM)
Elevation model including ground, vegetation, buildings and other objects
Digital Elevation Model (DEM)
Elevation model including ground but not vegetation, buildings or other objects
Digital Terrain Model (DTM)
Elevation model including ground and break line but not vegetation, buildings or other objects
Nominal Post Spacing (NPS)
Average distance between adjacent LiDAR points (ft or m)
Number of LiDAR points per unit area (points per square meter)
Root Mean Square Error (RMSE)
The Statistical value equal to the square root of the average of the squares of the differences between known points and modeled points in the LiDAR surface
Vertical Accuracy of LiDAR
Is not an “absolute” accuracy. It is commonly specified as the Root Mean Square Error (RMSEz)
- RMSEz is 68% confidence interval
- RMSEz x 1.96 is the 95% confidence interval
- RMSEz is the 99.7% confidence interval