The Combination of Terrestrial Lidar and Uav Photogrammetry for Interactive Architectural Heritage Visualization Using Unity 3d Game Engine

Andaru, Ruli; Cahyono, Bambang Kun; Riyadi, Gondang; Istarno,; Djurdjani,; Ramadhan, Gilang; Tuntas, S.

doi:10.5194/isprs-archives-xlii-2-w17-39-2019

Cited by 10 publications

(6 citation statements)

References 8 publications

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“…The point cloud analysis comprises a defined XYZ value for every point, followed by an intensity value (due to the active source of the t-LiDAR method) or an RGB value (due to the passive source of the UAV method). This type of multi-vector analysis (sphere-by-sphere and point-by-point analysis) is currently a cuttingedge technology with significant potential in several geoscientific applications [119][120][121][122], while a combination of multi-source point clouds is feasible [123].…”

Section: Discussionmentioning

confidence: 99%

Monitoring and Quantifying Soil Erosion and Sedimentation Rates in Centimeter Accuracy Using UAV-Photogrammetry, GNSS, and t-LiDAR in a Post-Fire Setting

Alexiou,

Papanikolaou,

Schneiderwind

et al. 2024

Remote Sensing

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Remote sensing techniques, namely Unmanned Aerial Vehicle (UAV) photogrammetry and t-LiDAR (terrestrial Light Detection and Ranging), two well-established techniques, were applied for seven years in a mountainous Mediterranean catchment in Greece (Ilioupoli test site, Athens), following a wildfire event in 2015. The goal was to monitor and quantify soil erosion and sedimentation rates with cm accuracy. As the frequency of wildfires in the Mediterranean has increased, this study aims to present a methodological approach for monitoring and quantifying soil erosion and sedimentation rates in post-fire conditions, through high spatial resolution field measurements acquired using a UAV survey and a t-LiDAR (or TLS—Terrestrial Laser Scanning), in combination with georadar profiles (Ground Penetration Radar—GPR) and GNSS. This test site revealed that 40 m3 of sediment was deposited following the first intense autumn rainfall events, a value that was decreased by 50% over the next six months (20 m3). The UAV–SfM technique revealed only 2 m3 of sediment deposition during the 2018–2019 analysis, highlighting the decrease in soil erosion rates three years after the wildfire event. In the following years (2017–2021), erosion and sedimentation decreased further, confirming the theoretical pattern, whereas sedimentation over the first year after the fire was very high and then sharply lessened as vegetation regenerated. The methodology proposed in this research can serve as a valuable guide for achieving high-precision sediment yield deposition measurements based on a detailed analysis of 3D modeling and a point cloud comparison, specifically leveraging the dense data collection facilitated by UAV–SfM and TLS technology. The resulting point clouds effectively replicate the fine details of the topsoil microtopography within the upland dam basin, as highlighted by the profile analysis. Overall, this research clearly demonstrates that after monitoring the upland area in post-fire conditions, the UAV–SfM method and LiDAR cm-scale data offer a realistic assessment of the retention dam’s life expectancy and management planning. These observations are especially crucial for assessing the impacts in the wildfire-affected areas, the implementation of mitigation strategies, and the construction and maintenance of retention dams.

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Section: Discussionmentioning

confidence: 99%

Monitoring and Quantifying Soil Erosion and Sedimentation Rates in Centimeter Accuracy Using UAV-Photogrammetry, GNSS, and t-LiDAR in a Post-Fire Setting

Alexiou,

Papanikolaou,

Schneiderwind

et al. 2024

Remote Sensing

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“…Additionally, point clouds and UAV-SfM methods are the baseline for the production of 3D models for surface reconstruction, surface change detection, and soil erosion monitoring [44,82,83,115]. The 3D point-to-point analysis leads to high-accuracy results in several scientific applications regarding surface change detection [45,50,116,117]. This multi-vector analysis denotes the complexity of the microsurface, which cannot be accurately represented by 2.5D DEM data and the interpolation method [83].…”

Section: Discussionmentioning

confidence: 99%

Measuring Annual Sedimentation through High Accuracy UAV-Photogrammetry Data and Comparison with RUSLE and PESERA Erosion Models

et al. 2023

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Model-based soil erosion studies have increased in number, given the availability of geodata and the recent technological advances. However, their accuracy remains rather questionable since the scarcity of field records hinders the validation of simulated values. In this context, this study aims to present a method for measuring sediment deposition at a typical Mediterranean catchment (870 ha) in Greece through high spatial resolution field measurements acquired by an Unmanned Aerial Vehicle (UAV) survey. Three-dimensional modeling is considered to be an emerging technique for surface change detection. The UAV-derived point cloud comparison, applying the Structure-from-Motion (SfM) technique at the Platana sediment retention dam test site, quantified annual topsoil change in cm-scale accuracy (0.02–0.03 m), delivering mean sediment yield of 1620 m3 ± 180 m3 or 6.05 t ha−1yr−1 and 3500 m3 ± 194 m3 or 13 t ha−1yr−1 for the 2020–2021 and 2021–2022 estimation. Moreover, the widely applied PESERA and RUSLE models estimated the 2020–2021 mean sediment yield at 1.12 t ha-1yr−1 and 3.51 t ha-1yr−1, respectively, while an increase was evident during the 2021–2022 simulation (2.49 t ha−1yr−1 and 3.56 t ha−1yr−1, respectively). Both applications appear to underestimate the net soil loss rate, with RUSLE being closer to the measured results. The difference is mostly attributed to the model’s limitation to simulate gully erosion or to a C-factor misinterpretation. To the authors’ better knowledge, this study is among the few UAV applications employed to acquire high-accuracy soil loss measurements. The results proved extremely useful in our attempt to measure sediment yield at the cm scale through UAV-SfM and decipher the regional soil erosion and sediment transport pattern, also offering a direct assessment of the retention dams’ life expectancy.

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“…(Buyuksalih et al, 2017) visualized 3D city models based on Unity3D and also estimated potential solar energy on buildings for Istanbul City. Other use cases are still limited and evolving, (Sihombing and Coors, 2018, Matthys et al, 2021, Edwards et al, 2015, Andaru et al, 2019 have already shown how 3D city models captured using geospatial technologies can be used with game engines for visualization of city objects, use of AR for city development, storytelling/public participation, AEC industry, preservation and visualization of heritage buildings. Such research shows the potential of 3D Unity visualization and game engine for 3D GIS visualization.…”

Section: State Of the Artmentioning

confidence: 99%

Viability Testing of Game Engine Usage for Visualization of 3d Geospatial Data With Ogc Standards

Würstle

Padsala

Santhanavanich

et al. 2022

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

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Abstract. Urban digital twins have become an essential factor for cities and communities to visualize, simulate and analyze data. The conventional geospatial standards work great with online platforms such as CesiumJS or ArcGIS API for JavaScript. However, their usage in different platforms such as game engines has not been well established yet. Game engines provide an interesting application case because they offer a different approach to visualizing large city models and provide a high graphical fidelity.This paper aims to answer how the existing standards, such as the API standards GeoVolumes and SensorThings, as well as the 3D model standards 3D Tiles and Esri Indexed 3D Scene Layer (I3S), can interact with game engines. For this purpose, three use-cases were selected and have been used to build applications. These focus on using sensor data in AR and different city development scenarios in a digital environment.This study shows that different geospatial standard formats such as 3D Tiles, I3S, and GL Transmission Format (glTF) can be used in game engines, either directly or over a GeoVolumes Server. Their implementation makes it possible to use the advantages of game engines with real-world datasets.

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The Combination of Terrestrial Lidar and Uav Photogrammetry for Interactive Architectural Heritage Visualization Using Unity 3d Game Engine

Cited by 10 publications

References 8 publications

Monitoring and Quantifying Soil Erosion and Sedimentation Rates in Centimeter Accuracy Using UAV-Photogrammetry, GNSS, and t-LiDAR in a Post-Fire Setting

Monitoring and Quantifying Soil Erosion and Sedimentation Rates in Centimeter Accuracy Using UAV-Photogrammetry, GNSS, and t-LiDAR in a Post-Fire Setting

Measuring Annual Sedimentation through High Accuracy UAV-Photogrammetry Data and Comparison with RUSLE and PESERA Erosion Models

Viability Testing of Game Engine Usage for Visualization of 3d Geospatial Data With Ogc Standards

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