High-resolution structure-from-motion models covering 160 km-long surface ruptures of the 2021 M_(W)7.4 Madoi earthquake in northern Qinghai-Tibetan Plateau

The May 222021 M_(W)7.4 Madoi,Qinghai,China earthquake presented a rare opportunity to apply the modern unmanned aerial vehicle(UAV)photography method in extreme altitude and weather conditions to image surface ruptures and near-field effects of earthquake-related surface deformations in the remote Tibet.High-resolution aerial photographs were acquired in the days immediately following the mainshock.The complex surface rupture patterns associated with this event were covered comprehensively at 3-6 cm resolution.This effort represents the first time that an earthquake rupture in the interior of the Qinghai-Tibetan Plateau has been fully and systematically captured by such high-resolution imagery,with an unprecedented level of detail,over its entire length.The dataset has proven valuable in documenting subtle and transient rupture features,such as the significant mole-tracks and opening fissures,which were ubiquitous coseismically but degraded during the subsequent summer storm season.Such high-quality imagery also helps to document with high fidelity the fractures of the surface rupture zone(supplements of this paper),the pattern related to how the faults ruptured to the ground surface,and the distribution of off-fault damage.In combination with other ground-based mapping efforts,the data will be analyzed in the following months to better understand the mechanics of earthquake rupture related to the fault zone rheology,rupture dynamics,and frictional properties along with the fault interface.

Structure-from-Motion Photogrammetry and Rare Earth Oxides can quantify diffuse and convergent soil loss and source apportionment

Accurately quantifying rates of soil erosion requires capturing both the volumetric nature of the visible,convergent fluvial pathways(also known as rills)and the subtle nature of the less-visible,diffuse pathways(interrill areas).The aim of this study was to use Rare Earth Oxide(REO)tracers and Structure-from-Motion(SfM)photogrammetry to elucidate retrospective information about soil erosion rates and sediment sources during different soil erosion conditions,within a controlled laboratory environment.The experimental conditions created erosion events consistent with diffuse and convergent erosion processes.REO tracers allowed the sediment transport distances of over 2 m to be described,and helped resolved the relative contribution of diffuse and convergent soil erosion;interrill areas were also iden-tified as a significant sediment sources soil loss under convergent erosion conditions.While the potential for SfM photogrammetry to resolve sub-millimetre elevations changes was demonstrated,under some conditions non-erosional changes in surface elevation,such as compaction,exceeded volumes of soil loss via diffuse erosion.The discrepancies between SfM Photogrammetry calculations and REO tagged sediment export were beneficial,identifying that during soil erosion events sediment in both aggregate and particle form is deposited within the convergent features,even when the rill extended the full length of the soil surface.The combination of SfM photogrammetry and REO tracers has provided a novel platform for building a spatial understanding of patterns of soil loss and source apportionment between rill and interrill erosion.

A Skeletal Camera Network for Close-range Images with a Data Driven Approach in Analyzing Stereo Configuration

Structure-from-Motion(SfM)techniques have been widely used for 3D geometry reconstruction from multi-view images.Nevertheless,the efficiency and quality of the reconstructed geometry depends on multiple factors,i.e.,the base-height ratio,intersection angle,overlap,and ground control points,etc.,which are rarely quantified in real-world applications.To answer this question,in this paper,we take a data-driven approach by analyzing hundreds of terrestrial stereo image configurations through a typical SfM algorithm.Two main meta-parameters with respect to base-height ratio and intersection angle are analyzed.Following the results,we propose a Skeletal Camera Network(SCN)and embed it into the SfM to lead to a novel SfM scheme called SCN-SfM,which limits tie-point matching to the remaining connected image pairs in SCN.The proposed method was applied in three terrestrial datasets.Experimental results have demonstrated the effectiveness of the proposed SCN-SfM to achieve 3D geometry with higher accuracy and fast time efficiency compared to the typical SfM method,whereas the completeness of the geometry is comparable.

A low-overhead asynchronous consensus framework for distributed bundle adjustment

Generally,the distributed bundle adjustment(DBA)method uses multiple worker nodes to solve the bundle adjustment problems and overcomes the computation and memory storage limitations of a single computer.However,the performance considerably degrades owing to the overhead introduced by the additional block partitioning step and synchronous waiting.Therefore,we propose a low-overhead consensus framework.A partial barrier based asynchronous method is proposed to early achieve consensus with respect to the faster worker nodes to avoid waiting for the slower ones.A scene summarization procedure is designed and integrated into the block partitioning step to ensure that clustering can be performed on the small summarized scene.Experiments conducted on public datasets show that our method can improve the worker node utilization rate and reduce the block partitioning time.Also,sample applications are demonstrated using our large-scale culture heritage datasets.