sUAS, SfM-MVS photogrammetry and a topographic algorithm method to quantify the volume of sediments retained in check-dams

Alfonso-Torreño, Alberto; Gutiérrez, Álvaro Gómez; Schnabel, Susanne; Contador, Joaquín Francisco Lavado; Blasco, José Juan de Sanjosé; Fernández, Manuel García

doi:10.1016/j.scitotenv.2019.04.332

Cited by 42 publications

(27 citation statements)

References 64 publications

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“…Solving the minimum value of the above formula means that the three-dimensional coordinates of the feature point are obtained [34].…”

Section: Sfm Algorithm For Sparse Point Cloudmentioning

confidence: 99%

Research on a Single-Tree Point Cloud Segmentation Method Based on UAV Tilt Photography and Deep Learning Algorithm

2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Developing a robust point cloud segmentation algorithm for individual trees from an amount of point cloud data has great significance for tracking tree changes. This method can measure the size, growth and mortality of individual trees to track and understand forest carbon storage and variation. Traditional measurement methods are not only slow but tardy. In order to obtain forest information better and faster, this article focuses on two aspects: The first is using UAVs to obtain multi-view remote sensing images of the forest, then using the SFM algorithm to construct the forest sparse point cloud and PMVS algorithm to construct the dense point cloud. The second is that a targeted point cloud deep learning method is proposed to extract the point cloud of a single tree. The research results show that the accuracy of single-tree point cloud segmentation of deep learning methods is more than 90%, and the accuracy is far better than traditional planar image segmentation and point cloud segmentation. The combination of point cloud data acquisition with UAV remote sensing and point cloud deep learning algorithms can meet the needs of forestry surveys. It is undeniable that this method, as a forestry survey tool, has a large space for promotion and possible future development.

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“…Solving the minimum value of the above formula means that the three-dimensional coordinates of the feature point are obtained [34].…”

Section: Sfm Algorithm For Sparse Point Cloudmentioning

confidence: 99%

Research on a Single-Tree Point Cloud Segmentation Method Based on UAV Tilt Photography and Deep Learning Algorithm

2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…However, all these techniques require labour intensive and time-consuming fieldwork for accurate surveys [36,37]. The recent development of remote sensing techniques (using satellites and unmanned aerial vehicles) has opened new tools to make the measurement activities quicker and easier [47]. For instance, the digital photogrammetry through aerial mapping using unmanned aerial vehicles (UAVs), adjusted to GNSS/RTK (Global Navigation Satellite Systems, based on Real-time Kinematic Positioning), is an efficient and low-requiring technique for such measurements, since it is able to map and quantify the sediment wedge from high-resolution and precise orthorectified images, and Digital Elevation Models (DEM) generated by UAVs, covering relatively large areas and providing quick estimations.…”

Section: Introductionmentioning

confidence: 99%

“…However, the examples of the use of this technique for estimating the check dam sediment wedge and map its geometric features are very scarce. Only Alfonso-Torreño et al [47] tested UAVs in combination with Structure-from-Motion photogrammetry to obtain Digital Elevation Models (DEMs) to estimate sediments behind 259 check dams in Western Spain, but this work was carried out at the watershed scale and on the long term, instead of working at the reach scale and with recent control works. Moreover, this technique has never been used for this purpose in fire-affected watershed regulated with check dams, and therefore, its effectiveness in these conditions is unknown.…”

Section: Introductionmentioning

confidence: 99%

The Use of Unmanned Aerial Vehicles (UAVs) for Estimating Soil Volumes Retained by Check Dams after Wildfires in Mediterranean Forests

et al. 2021

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Check dams act as soil collectors during floods, thus retaining a large amount of sediments. The estimation of the soil volumes stored behind a check dam is a key activity for a proper design of these control works and for evaluation of soil delivery after restoration measures at watershed level. Several topographic techniques have been proposed for this activity, but the sediment wedge mapping tools are complex and time consuming. Conversely, the use of unmanned aerial vehicles (UAVs) has been proposed to support aerophotogrammetric techniques for several survey activities with promising results. However, surveys by UAVs have never applied to calculate the size of the sediment wedge behind check dams that are built in fire-affected watersheds, where soil loss and sediment transport may be high after a wildfire. To fill this gap, this study evaluates the efficiency and efficacy of aerophotogrammetric surveys using UAVs to estimate the volume of the sediments stored behind ten check dams, built as post-fire channel treatment in a forest watershed of Castilla La Mancha (Central Eastern Spain). The results of the aerophotogrammetric technique were compared to traditional topographic surveys using a total station and GNSS/RTK, assumed as reference. The estimation of sediment wedge volume provided by UAVs was more accurate (mean RMSE of 0.432), extensive (density of mapped points of 328 m−2) and quick (two days of fieldwork) compared to surveys using the topographic method (RMSE < 0.04 m, six days of field work and density of mapped points of 0.194 m−2) by the topographic method. The differences in the sediment volume estimated by the two methods were not significant, but the UAV method was more accurate for the larger check dams. Moreover, a significant correlation was observed between the volume estimates provided by the two methods, shown by a coefficient of determination close to 0.98. Overall, these results propose a larger use of the aerial surveys for mapping activities in channels regulated by check dams, such as those built for restoration of fire-affected forest watersheds.

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“…Image-based health monitoring techniques to acquire 3D point clouds (PCs) on real scenes are low-cost and very precise, but the quality of the images is significantly affected by the surrounding environmental conditions and exhaustive images are needed to achieve the required resolution [17]. The recent development of robotic equipment such as unmanned aerial vehicles (UAVs) facilitates the acquisition of high-resolution aerial photos from which 3D PCs are obtained through Structure-from-Motion (SfM) [18] and MultiView-Stereo (MVS) photogrammetry algorithms [19,20]. Skarlatos and Kiparissi [21] showed that for small and medium size objects and distances, an SfM algorithm followed by an MVS algorithm is superior to terrestrial laser scanner (TLS) in terms of accuracy, density, modelling quality and cost.…”

Section: Introductionmentioning

confidence: 99%

Concrete Preliminary Damage Inspection by Classification of Terrestrial Laser Scanner Point Clouds through Systematic Threshold Definition

Hadavandsiri

Lichti

Jahraus

et al. 2019

IJGI

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This paper presents a novel approach for automatic, preliminary detection of damage in concrete structures using ground-based terrestrial laser scanners. The method is based on computation of defect-sensitive features such as the surface curvature, since the surface roughness changes strongly if an area is affected by damage. A robust version of principal component analysis (PCA) classification is proposed to distinguish between structural damage and outliers present in the laser scanning data. Numerical simulations were conducted to develop a systematic point-wise defect classifier that automatically diagnoses the location of superficial damage on the investigated region. The method provides a complete picture of the surface health of concrete structures. It has been tested on two real datasets: a concrete heritage aqueduct in Brooks, Alberta, Canada; and a civil pedestrian concrete structure. The experiment results demonstrate the validity and accuracy of the proposed systematic framework for detecting and localizing areas of damage as small as 1 cm or less.

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sUAS, SfM-MVS photogrammetry and a topographic algorithm method to quantify the volume of sediments retained in check-dams

Cited by 42 publications

References 64 publications

Research on a Single-Tree Point Cloud Segmentation Method Based on UAV Tilt Photography and Deep Learning Algorithm

Research on a Single-Tree Point Cloud Segmentation Method Based on UAV Tilt Photography and Deep Learning Algorithm

The Use of Unmanned Aerial Vehicles (UAVs) for Estimating Soil Volumes Retained by Check Dams after Wildfires in Mediterranean Forests

Concrete Preliminary Damage Inspection by Classification of Terrestrial Laser Scanner Point Clouds through Systematic Threshold Definition

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