Details
| Original language | English |
|---|---|
| Pages (from-to) | 599-606 |
| Number of pages | 8 |
| Journal | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Volume | 10 |
| Issue number | G-2025 |
| Publication status | Published - 11 Jul 2025 |
| Event | 2025 International Society for Photogrammetry and Remote Sensing (ISPRS) Geospatial Week, GSW 2025 - Dubai, United Arab Emirates Duration: 6 Apr 2025 → 11 Apr 2025 |
Abstract
One of the main fields of engineering geodesy is deformation monitoring of natural and man-made structures. Infrastructure objects such as bridges, dams, and tunnels are of special interest because their operational safety must be ensured at all times. Area-based deformation analysis can be effectively conducted using terrestrial laser scanners (TLS). Unlike the limited, pre-selected, and point-based measurements used in traditional approaches, TLS samples the environment with millions of points without the need to signal the points. Point clouds data from TLS are influenced by remaining systematic errors as well as random noise. These sources of uncertainty are frequently handled using probabilistic approaches, which may provide an inadequate or overoptimistic representation of the overall uncertainty in point cloud data. In this contribution, an alternative approach based on interval mathematics is proposed to bound the uncertainty due to remaining systematic errors. To this end, a sensitivity analysis of TLS observation correction models is performed, and typical variability of the input parameters, such as temperature, pressure, humidity, and temperature gradients, as well as instrument misalignment, is assessed. Subsequently, error bands for the polar measurement elements in the form of intervals are obtained. While variance propagation follows a quadratic form, interval-based techniques enable linear uncertainty propagation, which is more effective for describing residual systematic uncertainty and worst-case scenarios. The methodology will be explained in detail, and typical values for the obtained intervals will be discussed and highlighted in a simulation study.
Keywords
- Interval arithmetic, Observation Uncertainty, Terrestrial Laser Scanners
ASJC Scopus subject areas
- Physics and Astronomy(all)
- Instrumentation
- Environmental Science(all)
- Environmental Science (miscellaneous)
- Earth and Planetary Sciences(all)
- Earth and Planetary Sciences (miscellaneous)
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In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 10, No. G-2025, 11.07.2025, p. 599-606.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Interval-based Uncertainty Bounding for Terrestrial Laser Scanning Observations
AU - Naeimaei, Reza
AU - Schön, Steffen
N1 - Publisher Copyright: Copyright © 2025 Reza Naeimaei.
PY - 2025/7/11
Y1 - 2025/7/11
N2 - One of the main fields of engineering geodesy is deformation monitoring of natural and man-made structures. Infrastructure objects such as bridges, dams, and tunnels are of special interest because their operational safety must be ensured at all times. Area-based deformation analysis can be effectively conducted using terrestrial laser scanners (TLS). Unlike the limited, pre-selected, and point-based measurements used in traditional approaches, TLS samples the environment with millions of points without the need to signal the points. Point clouds data from TLS are influenced by remaining systematic errors as well as random noise. These sources of uncertainty are frequently handled using probabilistic approaches, which may provide an inadequate or overoptimistic representation of the overall uncertainty in point cloud data. In this contribution, an alternative approach based on interval mathematics is proposed to bound the uncertainty due to remaining systematic errors. To this end, a sensitivity analysis of TLS observation correction models is performed, and typical variability of the input parameters, such as temperature, pressure, humidity, and temperature gradients, as well as instrument misalignment, is assessed. Subsequently, error bands for the polar measurement elements in the form of intervals are obtained. While variance propagation follows a quadratic form, interval-based techniques enable linear uncertainty propagation, which is more effective for describing residual systematic uncertainty and worst-case scenarios. The methodology will be explained in detail, and typical values for the obtained intervals will be discussed and highlighted in a simulation study.
AB - One of the main fields of engineering geodesy is deformation monitoring of natural and man-made structures. Infrastructure objects such as bridges, dams, and tunnels are of special interest because their operational safety must be ensured at all times. Area-based deformation analysis can be effectively conducted using terrestrial laser scanners (TLS). Unlike the limited, pre-selected, and point-based measurements used in traditional approaches, TLS samples the environment with millions of points without the need to signal the points. Point clouds data from TLS are influenced by remaining systematic errors as well as random noise. These sources of uncertainty are frequently handled using probabilistic approaches, which may provide an inadequate or overoptimistic representation of the overall uncertainty in point cloud data. In this contribution, an alternative approach based on interval mathematics is proposed to bound the uncertainty due to remaining systematic errors. To this end, a sensitivity analysis of TLS observation correction models is performed, and typical variability of the input parameters, such as temperature, pressure, humidity, and temperature gradients, as well as instrument misalignment, is assessed. Subsequently, error bands for the polar measurement elements in the form of intervals are obtained. While variance propagation follows a quadratic form, interval-based techniques enable linear uncertainty propagation, which is more effective for describing residual systematic uncertainty and worst-case scenarios. The methodology will be explained in detail, and typical values for the obtained intervals will be discussed and highlighted in a simulation study.
KW - Interval arithmetic
KW - Observation Uncertainty
KW - Terrestrial Laser Scanners
UR - http://www.scopus.com/inward/record.url?scp=105013208509&partnerID=8YFLogxK
U2 - 10.5194/isprs-annals-X-G-2025-599-2025
DO - 10.5194/isprs-annals-X-G-2025-599-2025
M3 - Conference article
AN - SCOPUS:105013208509
VL - 10
SP - 599
EP - 606
JO - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
JF - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
SN - 2194-9042
IS - G-2025
T2 - 2025 International Society for Photogrammetry and Remote Sensing (ISPRS) Geospatial Week, GSW 2025
Y2 - 6 April 2025 through 11 April 2025
ER -