New Approach for Photogrammetric Rock Slope Premonitory Movements Monitoring

Andrés, A.; Prades, Albert; Matas, Gerard; Pozuelo, Felipe Buill; Lantada, Nieves

doi:10.3390/rs15020293

Cited by 10 publications

(3 citation statements)

References 40 publications

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“…Additionally, this study provides researchers with a novel perspective for solving the coverage planning problem in the case of rotational motion. This method could be applied to many practical applications besides WAPS, including robot sensing [52], mass and slope movement monitoring [53,54], and ecological observation [55].…”

Section: Discussionmentioning

confidence: 99%

Coverage Path Planning with Adaptive Hyperbolic Grid for Step-Stare Imaging System

Zhao

2024

Drones

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Step-stare imaging systems are widely used in aerospace optical remote sensing. In order to achieve fast scanning of the target region, efficient coverage path planning (CPP) is a key challenge. However, traditional CPP methods are mostly designed for fixed cameras and disregard the irregular shape of the sensor’s projection caused by the step-stare rotational motion. To address this problem, this paper proposes an efficient, seamless CPP method with an adaptive hyperbolic grid. First, we convert the coverage problem in Euclidean space to a tiling problem in spherical space. A spherical approximate tiling method based on a zonal isosceles trapezoid is developed to construct a seamless hyperbolic grid. Then, we present a dual-caliper optimization algorithm to further compress the grid and improve the coverage efficiency. Finally, both boustrophedon and branch-and-bound approaches are utilized to generate rotation paths for different scanning scenarios. Experiments were conducted on a custom dataset consisting of 800 diverse geometric regions (including 2 geometry types and 40 samples for 10 groups). The proposed method demonstrates comparable performance of closed-form path length relative to that of a heuristic optimization method while significantly improving real-time capabilities by a minimum factor of 2464. Furthermore, in comparison to traditional rule-based methods, our approach has been shown to reduce the rotational path length by at least 27.29% and 16.71% in circle and convex polygon groups, respectively, indicating a significant improvement in planning efficiency.

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Section: Discussionmentioning

confidence: 99%

Coverage Path Planning with Adaptive Hyperbolic Grid for Step-Stare Imaging System

Zhao

2024

Drones

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“…Camera-based monitoring techniques have recently been used to monitor and track fallen rocks in real time. More recently, the development of photogrammetric monitoring systems for rock-fall monitoring purposes has received increased attention in the scientific literature [8][9][10][11][12]. A test version of an artificial intelligence camera was used to track and monitor falling rocks in real-time [13].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning- and IoT-Based Framework for Rock-Fall Early Warning

Abaker,

Dafaalla,

Eisa

et al. 2023

Applied Sciences

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In recent years, several strategies have been introduced to enhance early warning systems and lower the risk of rock-falls. In this regard, this paper introduces a deep learning- and IoT-based framework for rock-fall early warning, devoted to reducing rock-fall risk with high accuracy. In this framework, the prediction accuracy was augmented by eliminating the uncertainties and confusion plaguing the prediction model. In order to achieve augmented prediction accuracy, this framework fused prediction model-based deep learning with a detection model-based Internet of Things. This study utilized parameters, namely, overall prediction performance measures based on a confusion matrix, to assess the performance of the framework in addition to its ability to reduce the risk. The result indicates an increase in prediction model accuracy from 86% to 98.8%. In addition, the framework reduced the risk probability from 1.51 × 10−3 to 8.57 × 10−9. Our findings demonstrate the high prediction accuracy of the framework, which also offers a reliable decision-making mechanism for providing early warning and reducing the potential hazards of rock falls.

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“…Progressive creep, deformation and micro-tremors are clear indicators of the ongoing disruption of the slope stability, therefore they are the primary goals for a comprehensive assessment of rockfall hazard. Most of the previous literature so far lies with the application of terrestrial-based technologies, such as terrestrial laser scanners (TLS) [32][33][34][35][36] or terrestrial InSAR platforms (TInSAR) [37,38] to identify pre-failure information. Despite the numerous advantages and exceptional precision of these techniques, however, several challenges arise due to the high costs and logistical constraints (linked to the positioning of the instrumentation and the lack of data in shaded areas).…”

Section: Introductionmentioning

confidence: 99%

Multi-Sensor and Multi-Scale Remote Sensing Approach for Assessing Slope Instability along Transportation Corridors Using Satellites and Uncrewed Aircraft Systems

et al. 2023

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Rapid slope instabilities (i.e., rockfalls) involving highway networks in mountainous areas pose a threat to facilities, settlements and life, thus representing a challenge for asset management plans. To identify different morphological expressions of degradation processes that lead to rock mass destabilization, we combined satellite and uncrewed aircraft system (UAS)-based products over two study sites along the State Highway 133 sector near Paonia Reservoir, Colorado (USA). Along with a PS-InSAR analysis covering the 2017–2021 interval, a high-resolution dataset composed of optical, thermal and multi-spectral imagery was systematically acquired during two UAS surveys in September 2021 and June 2022. After a pre-processing step including georeferencing and orthorectification, the final products were processed through object-based multispectral classification and change detection analysis for highlighting moisture or lithological variations and for identifying areas more susceptible to deterioration and detachments at the small and micro-scale. The PS-InSAR analysis, on the other hand, provided multi-temporal information at the catchment scale and assisted in understanding the large-scale morpho-evolution of the displacements. This synergic combination offered a multiscale perspective of the superimposed imprints of denudation and mass-wasting processes occurring on the study site, leading to the detection of evidence and/or early precursors of rock collapses, and effectively supporting asset management maintenance practices.

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New Approach for Photogrammetric Rock Slope Premonitory Movements Monitoring

Cited by 10 publications

References 40 publications

Coverage Path Planning with Adaptive Hyperbolic Grid for Step-Stare Imaging System

Coverage Path Planning with Adaptive Hyperbolic Grid for Step-Stare Imaging System

Deep Learning- and IoT-Based Framework for Rock-Fall Early Warning

Multi-Sensor and Multi-Scale Remote Sensing Approach for Assessing Slope Instability along Transportation Corridors Using Satellites and Uncrewed Aircraft Systems

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