Digital Twin Germany – a digital replica for simulation and analysis build on geospatial data

Hopfstock, Anja; Knöfel, Patrick; Lindl, Florian

doi:10.5194/ica-abs-5-119-2022

Cited by 2 publications

(1 citation statement)

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“…Nowadays, a multitude of point cloud (PC) data sources applicable to micro-topography exists. Terrestrial and aerial laser scanning [1], satellite aperture array (SAR) tomography [2] and photogrammetry [3] each have different penetration, density and angular and depth accuracy. Also, large PC collections [4] are available for micro-topography feature capture, and there is material from different years and under different seasonal conditions.…”

Section: Introductionmentioning

confidence: 99%

Highest informative density of a TIN model

Nevalainen,

Virjonen,

Salmivaara

et al. 2024

Preprint

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A point cloud (PC) source is useful for micro-topography, if the shortest spatial wavelength it carries is enough for a particular registration task. This wavelengthvaries a lot due to different scanning methodologies and environmentalconditions. We propose an automated procedure for approximating the highest meaningful density of a PC in order to produce relatively noiseless ground models.This density limit can serve as a set target for existing thinningprocedures of large PC archives. Three methods to approximate the highest meaningful density are being compared:mean absolute error (MAE) of the triangulated irregular network (TIN) fit, minimum description length (MDL) and direct spatial wavelength registration (DWR). Each method is computationally expensive but can be subjected to a small set of local samples of a possibly large PC archive. Natural data samples were: a photogrammetric PC and a detail of it,and an aerial laser scan (ALS), all from the same forest site. The pipeline for finding a suggested minimum PC density has n log n complexity in terms of original PC size n. DWR found a wavelength range 5 ... 14 m from a synthetic case with the wavelength of 13 m. All methods give mean TIN edge length0.05 ... 0.1 m corresponding well with a published choice 0.2 m.

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Section: Introductionmentioning

confidence: 99%

Highest informative density of a TIN model

Nevalainen,

Virjonen,

Salmivaara

et al. 2024

Preprint

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Digital Twins and Green Paths

Khan,

Jhanjhi,

Ray

2024

Digital Transformation for Improved Industry and Supply Chain Performance

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The contribution of digital twins to sustainability is explored in this chapter within the setting of Industry 4.0. It begins by providing concepts and definitions of digital twins by highlighting the significance of sustainability in contemporary industries. It subsequently investigates various types of digital twins and their interactions with other Industry 4.0 technologies representing their broad-ranging applications. The chapter then proceeds to examine sustainability, exemplifying how digital twins optimize resource utilization, efficiently manage energy, and promote eco-friendly practices in industrial settings, corroborated by empirical case studies. Additionally, it scrutinizes emerging technologies, global initiatives, and ethical considerations pertaining to the implementation of digital twins. Finally, it emphasizes the transformative potential of digital twins in driving sustainable industrial practices and advocates for ongoing research and collaboration to progress towards a more environmentally conscious future.

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Digital Twin Germany – a digital replica for simulation and analysis build on geospatial data

Cited by 2 publications

References 0 publications

Highest informative density of a TIN model

Highest informative density of a TIN model

Digital Twins and Green Paths

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