Fully automatic spatiotemporal segmentation of 3D LiDAR time series for the extraction of natural surface changes

Anders, Katharina; Winiwarter, Lukas; Mara, Hubert; Lindenbergh, Roderik; Vos, Sander; Höfle, Bernhard

doi:10.1016/j.isprsjprs.2021.01.015

Cited by 28 publications

(25 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on this information, the appropriate resolution per change form could be selected, subsequently. A similar approach was shown to perform well for determining the locally adaptive DTW distance threshold used for region growing in the method (Anders et al, 2021). When making use of parallel computing, this does not necessarily increase runtimes.…”

Section: Discussionmentioning

confidence: 94%

“…We use spatiotemporal segmentation as time series-based method of change analysis following Anders et al (2021). In the first step, the method detects periods of temporary surface changes in the time series of a 2D location.…”

Section: Spatiotemporal Segmentation and Selected 4d-obcsmentioning

confidence: 99%

“…This is achieved by performing the region growing for a set of strict to loose thresholds in parallel. The final 4D-OBC is selected at the threshold with lowest increase in segment size, which maximizes segment sizes while avoiding leakage (Anders et al, 2021). A full spatiotemporal segmentation of the 3D time series used in our analysis yields over 2,000 4D-OBCs (cf.…”

Section: Spatiotemporal Segmentation and Selected 4d-obcsmentioning

confidence: 99%

“…A full spatiotemporal segmentation of the 3D time series used in our analysis yields over 2,000 4D-OBCs (cf. Anders et al, 2021). Extracted changes are temporary accumulation and erosion forms on the beach, which typically exist over periods of days to weeks.…”

Section: Spatiotemporal Segmentation and Selected 4d-obcsmentioning

confidence: 99%

“…The result of spatiotemporal segmentation are so-called 4D objects-by-change (4D-OBCs) which represent the spatial extent of surface changes over the period of their existence. This method is not dependent on a selection of analysis periods or on the definition of spatial and temporal properties of changes, such as their magnitude, spatial extent, duration, or change rate (Anders et al, 2021). The domain of surface change properties that can be observed within time series is generally determined by the resolution settings of data acquisition, according to the Nyquist-Shannon sampling theorem (Shannon, 1949).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Influence of Spatial and Temporal Resolution on Time Series-Based Coastal Surface Change Analysis Using Hourly Terrestrial Laser Scans

Anders

Winiwarter

Mara

et al. 2021

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

Abstract. Near-continuously acquired terrestrial laser scanning (TLS) data contains valuable information on natural surface dynamics. An important step in geographic analyses is to detect different types of changes that can be observed in a scene. For this, spatiotemporal segmentation is a time series-based method of surface change analysis that removes the need to select analysis periods, providing so-called 4D objects-by-change (4D-OBCs). This involves higher computational effort than pairwise change detection, and efforts scale with (i) the temporal density of input data and (ii) the (variable) spatial extent of delineated changes. These two factors determine the cost and number of Dynamic Time Warping distance calculations to be performed for deriving the metric of time series similarity. We investigate how a reduction of the spatial and temporal resolution of input data influences the delineation of twelve erosion and accumulation forms, using an hourly five-month TLS time series of a sandy beach. We compare the spatial extent of 4D-OBCs obtained at reduced spatial (1.0 m to 15.0 m with 0.5 m steps) and temporal (2 h to 96 h with 2 h steps) resolution to the result from highest-resolution data. Many change delineations achieve acceptable performance with ranges of ±10 % to ±100 % in delineated object area, depending on the spatial extent of the respective change form. We suggest a locally adaptive approach to identify poor performance at certain resolution levels for the integration in a hierarchical approach. Consequently, the spatial delineation could be performed at high accuracy for specific target changes in a second iteration. This will allow more efficient 3D change analysis towards near-realtime, online TLS-based observation of natural surface changes.

show abstract

Section: Discussionmentioning

confidence: 94%

Section: Spatiotemporal Segmentation and Selected 4d-obcsmentioning

confidence: 99%

Section: Spatiotemporal Segmentation and Selected 4d-obcsmentioning

confidence: 99%

Section: Spatiotemporal Segmentation and Selected 4d-obcsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Influence of Spatial and Temporal Resolution on Time Series-Based Coastal Surface Change Analysis Using Hourly Terrestrial Laser Scans

Anders

Winiwarter

Mara

et al. 2021

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

show abstract

LR B-Spline Surfaces and Volumes for Deformation Analysis of Terrain Data

Kermarrec

Skytt

Dokken

2022

Optimal Surface Fitting of Point Clouds Using Local Refinement

View full text Add to dashboard Cite

Geospatial data acquisition of terrains with contact-free sensors such as Terrestrial or Airbone Laser Scanners generates scattered and noisy point clouds. Performing a surface approximation is an efficient way to reduce and structure the recorded point clouds. To that end, LR B-splines are attractive as they allow a local refinement, on the contrary to the tensor product B-spline and raster surfaces. By comparing the approximation error with a given tolerance, a local refinement is performed. We apply this adaptive refinement strategy to landslides data sets from Alpine terrain in Austria. We show how different epochs of the point clouds can be analyzed with LR B-spline volumes for spatio-temporal visualisation of deformation. We highlight the potential of a time-differenced LR B-splines volume for analysing geomorphological changes. A further application of this method is the drawing of contour lines.

show abstract

Comparison of Cloud-to-Cloud Distance Calculation Methods - Is the Most Complex Always the Most Suitable?

Diaz,

van Oosterom,

Meijers

et al. 2024

Lecture Notes in Geoinformation and Cartography

View full text Add to dashboard Cite

Fully automatic spatiotemporal segmentation of 3D LiDAR time series for the extraction of natural surface changes

Cited by 28 publications

References 33 publications

Influence of Spatial and Temporal Resolution on Time Series-Based Coastal Surface Change Analysis Using Hourly Terrestrial Laser Scans

Influence of Spatial and Temporal Resolution on Time Series-Based Coastal Surface Change Analysis Using Hourly Terrestrial Laser Scans

LR B-Spline Surfaces and Volumes for Deformation Analysis of Terrain Data

Comparison of Cloud-to-Cloud Distance Calculation Methods - Is the Most Complex Always the Most Suitable?

Contact Info

Product

Resources

About