Accuracy improvement of airborne lidar strip adjustment by using height data and surface feature strength information derived from the tensor voting algorithm

Rey Jer You, Chao Liang Lee

Research output: Contribution to journalArticle

Abstract

Light detection and ranging (Lidar) spatial coordinates, especially height data, and the intensity data of point clouds are often used for strip adjustment in airborne Lidar. However, inconsistency in the intensity data and then intensity gradient data because of the variations in the incidence and reflection angles in the scanning direction and sunlight incident in the same areas of different strips may cause problems in the Lidar strip adjustment process. Instead of the Lidar intensity, a new type of data, termed surface feature strength data derived by using the tensor voting method, were introduced into the strip adjustment process using the partial least squares method in this study. These data are consistent in the same regions of different strips, especially on the roofs of buildings. Our experimental results indicated a significant improvement in the accuracy of strip adjustment results when both height data and surface feature strength data were used.

Original languageEnglish
Article number50
JournalISPRS International Journal of Geo-Information
Volume9
Issue number1
DOIs
Publication statusPublished - 2020 Jan 1

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Computers in Earth Sciences
  • Earth and Planetary Sciences (miscellaneous)

Cite this