LiDAR Aerial Matching Case Study

Introduction

The objective of the project is the flightline matching process of Aerial LiDAR point cloud.

Key Features

  • Automatic classification of LiDAR point cloud.
  • Solve hrpm for whole data set.
  • Solve z for individual flightline.

Methodology

Processing steps

  • Import trajectories into terrascan
  • Split any trajectories which overlap themselves
  • Import time stamped laser point into terrascan
  • Automatically classify low points, buildings and ground for each flightline.
  • Run find match tool and solve for heading, roll, pitch and mirror scale corrections for the whole data set
  • Apply the correction to the laser data
  • Run find match tool and solve for elevations corrections for the individual flightline
  • Apply the correction to the laser data
  • Check the flightlines visually in cross sections to determine if the correction was good.
  • Try solving parameters with different settings to get improved result .

Quality assurance

Expertise with stringent knowledge in matching will be allocated to assess the quality of the data. Quality checks will be carried according to checklist prepared with reference to acceptance criteria.

Deliverables

Flight line matched las

Technology Used

Microstation, Terrascan, Terramodel, Terramatch

Challenges

  • Selection of sample blocks to find hrpm & z mismatch is a skillful task
  • Las blocks with no built up area is difficult to match

Inputs

  • LiDAR point cloud in LAS format
  • Ptc file
  • Project file
  • Trajectory file
  • AOI
  • Specification document

Application

  • Urban planning
  • Topographical surveying and contouring
  • Forestry
  • Water and gas pipeline survey
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