Data Quality Analysis of the Leica SPL100 Airborne Single Photon Lidar Sensor
type: CreativeWork
description: Recently, Geiger-mode and single photon lidar sensors have emerged on the commercial market, advertising greater collection efficiency than traditional linear mode lidar systems. Non-linear photon detection is a new technology for the geospatial community, and its performance characteristics for surveying and mapping are not yet well understood. The goal of this thesis, therefore, is to examine the geospatial quality of the data produced by one of these new sensors, the Leica SPL100. The SPL100 was shown to have a lower ranging precision than linear lidar and that its precision is more negatively affected by surface properties such as low intensity, roughness, and slope. The accuracy of the SPL100, however, was found to be comparable to that produced by linear lidar for smooth horizontal surfaces. It was also observed that the post-processed SPL100 data has limited ability to resolve multiple returns through vegetation due to the current filtering algorithms employed.
abstract: Recently, Geiger-mode and single photon lidar sensors have emerged on the commercial market, advertising greater collection efficiency than traditional linear mode lidar systems. Non-linear photon detection is a new technology for the geospatial community, and its performance characteristics for surveying and mapping are not yet well understood. The goal of this thesis, therefore, is to examine the geospatial quality of the data produced by one of these new sensors, the Leica SPL100. The SPL100 was shown to have a lower ranging precision than linear lidar and that its precision is more negatively affected by surface properties such as low intensity, roughness, and slope. The accuracy of the SPL100, however, was found to be comparable to that produced by linear lidar for smooth horizontal surfaces. It was also observed that the post-processed SPL100 data has limited ability to resolve multiple returns through vegetation due to the current filtering algorithms employed.
author: Brown, Rebecca Allene
language: eng
keywords: LiDAR, Single photon LiDAR, Remote sensing
date published: 2019-08
date modified: 2026-07-24T02:32:32Z
provider: University of Houston
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Houston

PropertyValue
property ID: Handle
value: https://hdl.handle.net/10657/5332