In Flight ALS Point Cloud Georeferencing using RTK GPS Receiver

Transcription

1 Integration of Geodetic Sensors In Flight ALS Point Cloud Georeferencing using RTK GPS Receiver Yannick Stebler, Philipp Schär, Jan Skaloud, Bertrand Merminod E mail: yannick.stebler@epfl.ch Web:

2 Content Scan2map ALS System Traditional concept of TLS/ALS In move data quality assessment Kinematic laser Scanning challenges System architecture Real time point cloud analyses Real time GPS quality control Helipos operator view Demo Real time mapping accuracy Applications

3 The Scan2map System Fast and accurate 3D mapping Georeferenced sensor data processed into DSM/DTM (0.5 m² density) and ortho image (5 cm/pixel) Ideal for natural hazards and corridor mapping CCD/LiDAR/GPS/INS

4 Traditional Concept of kinematic TLS/ALS GPS Absolute position CP-DGPS GPS IMU Li idar Laser orientation Ixyz/rpy Range and Intensity Encoder angle pointcloud IMU ALS Data Acquisition Post Processing Differential GPS Track GPS/INS Integration Point cloud generation reference station ti

5 «In Move» Data Quality Assessment Goal: In flight data quality and coverage monitoring RT Trajectory Quality RT Swath Boundaries RT ALS Gap detection Challenges Combination of different data streams in RT RT Attitude computation (RTGPS/INS Kalman Filtering) RT Georeferencing of ALS Point cloud IMU GPS 1-2 HZ Hz LiDAR KHz

6 Kinematic Laser Scanning Challenges GPS IMU LiDAR Bad GPS Constellation Cycle slips Long baseline Unfavorable dynamics Vibrations No returns (reflectivity) missing strip overlap CP-DGPS xyz/rpy pointcloud Achilles heel: Lack of reliable data quality assessment within or shortly after the survey Possible pitfalls Trajectory /attitude computation fails or inaccurate Poor precision of the point cloud The point cloud not homogenous or incomplete detected only in post processing! Increased cost of mapping product Time delay between flight and data delivery increases QC by independent ground survey Point density, accuracy are not met reflight

7 System Architecture Data Acquisition Communication Data Analysis

8 LIEAN (Real Time Point Cloud Analyses) RT Georeferencing Density Grid Vectorize Extend Vectorize Gaps Min. required density [pts/m 2 ] Send to HELIPOS Min. gap surface [m 2 ] On flightline On transfer

9 Real Time GPS Quality Control

10 Helipos Operator View

11 Demo: ALS Survey near St Moritz (Switzerland) Pilot View Controller View

12 Real Time Mapping Accuracy Differences between real time and post mission generated point cloud

13 Colored Point Cloud

14 Hazard Mapping

15 Conclusions RT quality and coverage assessment tool successfully tested RT Point Cloud Accuracy (using single positioning mode) largely sufficient to control lals point cloud consistency it and coverage GPS RTK positioning enables RT DSM/DTM generation with high accuracy opens new application domains Processing modules are portable and could be used for other ALS systems Towards RT high accuracy DSM/DTM generation