Generating UAV high-resolution topographic data within a FOSS photogrammetric workflow using high-performance computing clusters

Salandra, Marco La; Miniello, G.; Nicotri, S.; Italiano, Alessandro; Donvito, Giacinto; Mäggi, G.; Dellino, Pierfrancesco; Capolongo, Domenico

doi:10.1016/j.jag.2021.102600

Cited by 10 publications

(9 citation statements)

References 38 publications

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“…Majority of available research on the photogrammetric use of UAV for establishing DEMs and DSMs does not provide the precise input parameters of performed imaging (Martínez-Carricondo et al, 2018;Ajibola et al, 2019;Donager et al, 2021;Sankey et al, 2021;Villoslada Peciña et al, 2021). The information tends to be either incomplete (Uysal et al, 2015;La Salandra et al, 2021) or relate to UAV technology employed in fixed-wing units (Zmarz et al, 2018;Donager et al, 2021;Sankey et al, 2021;Vavulin et al, 2021). Studies utilizing UAV photogrammetry to generate DSM and DEM typically use fixed parameters, i.e., altitude of approx.…”

Section: Discussionmentioning

confidence: 99%

“…Studies utilizing UAV photogrammetry to generate DSM and DEM typically use fixed parameters, i.e., altitude of approx. 50 m a.g.l in the case of multirotor UAVs, overlap at 50-70%, camera angle in the range of 60-80 ° (Kędzierski et al, 2014;Uysal et al, 2015;Akturk and Altunel, 2019;La Salandra et al, 2021). Bearing that in mind, the presented study set out to determine differences in photogrammetric measurement results that arise from the choice of parameters set prior to the flight.…”

Section: Discussionmentioning

confidence: 99%

“…Traditional methods of generating DEMs are time consuming and cost-inefficient as they require on-site surveying and expensive measuring equipment (e.g., on-ground and aerial LiDAR scanners). Owing to the development of technology and its increasing availability, Unmanned Aerial Vehicles (UAV) have become a viable option for establishing precise DEMs in relation to relatively vast areas and at very low cost (Moore et al, 1991;Walker and Willgoose, 1999;Thar and Ahmad, 2013;Audronis, 2015;Uysal et al, 2015;Akbari et al, 2016;Martínez-Carricondo et al, 2018;Zmarz et al, 2018;Ajibola et al, 2019;Akturk and Altunel, 2019;Donager et al, 2021;La Salandra et al, 2021;Sankey et al, 2021;Vavulin et al, 2021;Villoslada Peciña et al, 2021). And thus, over the past several years low-altitude photogrammetry (Kędzierski et al, 2014) has become one of the main methods of generating DEMs.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of the Applicability of UAV for the Creation of Digital Surface Model of a Small Peatland

Czapiewski

2022

Front. Earth Sci.

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Rapid development and growing availability of Unmanned Aerial Vehicles (UAV) translates into their more wide-spread application in monitoring of the natural environment. Moreover, advances in computer analysis techniques allow the imaging performed with UAVs to be used in creating Digital Elevation Models (DEM) and Digital Surface Models (DSM). DEMs are often employed in studies on geology, environment, engineering, and architecture. The presented paper discusses the procedures enabling the making of a precise DEM, discusses the aerial imaging data processing technique as well as determines the accuracy of obtained products in comparison with an existing Digital Elevation Model. Based on available literature the author indicates four sets of input parameters applicable in UAV imaging. Data collection missions were performed on two separate days in the area of a small peatland located in the Tuchola Pinewood, Poland. The study aims to address two research issues. Firstly, the author investigates the possibility of creating a DSM based on UAV imaging performed under unfavorable conditions and indicates whether results obtained via this method display sufficient quality to be seen as an alternative to the traditional surveying techniques (LiDAR). Secondly, the article determines the input parameters for a photogrammetric flight that ensure the highest accuracy of a resulting DSM. The analyses show a strong positive correlation between the DSMs prepared based on UAV imaging with data obtained by means of traditional methods (LiDAR). Mean correlation coefficient ranged from 0.45 to 0.75 depending on the type of land use and input parameters selected for a given flight. Furthermore, the analysis revealed that DSMs prepared based on UAV imaging—provided the most suitable input parameters are selected—can be a viable alternative to standard measurements, with the added benefit of low cost and the capacity for repeatable data collection in time. Admittedly, the method in question cannot be utilized in relation to peatlands overgrown with high vegetation (trees, shrubs) as it effectively diminishes the accuracy of obtained DSMs.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessment of the Applicability of UAV for the Creation of Digital Surface Model of a Small Peatland

Czapiewski

2022

Front. Earth Sci.

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“…ARDAS was developed following the experimentation of integrated methodologies of RS and data processing [45]. The multi-technologies system applies a sequential step-bystep procedure (Figure 3):…”

Section: Ardas Descriptionmentioning

confidence: 99%

New Perspectives of Earth Surface Remote Detection for Hydro-Geomorphological Monitoring of Rivers

2022

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In the current scenery of climate change and its relatively increasing visible effects seen over the world, the monitoring of geomorphological processes and flood dynamics becomes more and more necessary for disaster risk reduction. During recent decades, the advantages offered by remote sensing for Earth surface observations have been widely exploited, producing images, digital elevation models (DEM), maps, and other tools useful for hydro-geomorphological parameters detection, flood extent monitoring, and forecasting. However, today, advanced technologies and integrated methodologies do not yet enable one to completely provide near-real-time (NRT) and very-high-resolution (VHR) observations of a river, which is needed for risk evaluation and correct operational strategy identification. This work presents an advanced remote detection analysis system (ARDAS) based on the combination of multiple technologies, such as Unmanned Aerial Vehicle (UAV) systems, Structure from Motion (SfM) techniques, and cloud computing environment. The system allows to obtain VHR products, such as ortho-photomosaics and DEM, for deep observation of the river conditions, morphological modifications, and evolution trend. The test of ARDAS in the Basento river catchment area (Basilicata, South Italy) showed that the innovative system (i) proves to be advantageous in river monitoring due to its high accuracy, quickness, and data flexibility; (ii) could represent a NRT solution for timely support of flood hazard assessments; and (iii) can be further developed by integrating other technologies for direct application in land planning and safeguard activities by contributing to the value chain of the new space economy and sustainable development.

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“…Still, it requires time and effort and also higher costs. The last method that can be used and is currently significantly developed in mapping the area is unmanned aircraft or Unmanned Aerial Vehicles (UAV) [2]. The use of UAV can provide information on the condition or situation of a site in great detail with a very high spatial resolution and can cover a large area in a shorter time [3].…”

Section: Introductionmentioning

confidence: 99%

Spatial Modelling for the Calculation of River Capacity: Case Study Downstream Area of Wanggu River Kendari

Fadlin

Thaha²,

Maricar³

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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Spatial modelling of flood-prone areas will provide maximum results if it is supported by the accuracy of the data acquired, mainly related to elevation data or the area’s topography. Spatial modelling generated from accurate topographic data can estimate the river’s carrying capacity. This study built a spatial model using data from aerial, terrestrial, and hydrographic surveys. Aerial surveys were conducted using UAV corrected by terrestrial surveys, GCP, and ICP. Testing the accuracy of the spatial model is carried out by comparing the results of current field velocity with the results of 2D Hec-Ras numerical simulations using a variation of the manning coefficient. The combination of aerial, terrestrial, and hydrographic surveys produces a cross-sectional spatial model of the river, which is used in calculating the river’s carrying capacity. The river’s capacity is calculated using a 2D numerical simulation method using Hec-Ras software and verified by a mathematical approach based on the flood hydrograph curve. The results showed that the horizontal accuracy of the GCP was 2.8 cm and the vertical accuracy was 6.5 cm. The results of testing the vertical elevation accuracy of aerial photographs on terrestrial topographic data measured in the field (ICP) have a Mean Absolute Percentage Error (MAPE) value of 5.81%. According to the spatial model, the manning roughness value is 0.06-0.09. The river’s capacity based on numerical simulations is 1.700.766 m3, and the results of the verification using a mathematical approach are 1.683.433 m3 with a difference of 1.02%.

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Generating UAV high-resolution topographic data within a FOSS photogrammetric workflow using high-performance computing clusters

Cited by 10 publications

References 38 publications

Assessment of the Applicability of UAV for the Creation of Digital Surface Model of a Small Peatland

Assessment of the Applicability of UAV for the Creation of Digital Surface Model of a Small Peatland

New Perspectives of Earth Surface Remote Detection for Hydro-Geomorphological Monitoring of Rivers

Spatial Modelling for the Calculation of River Capacity: Case Study Downstream Area of Wanggu River Kendari

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