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This paper deals with the implementation of an automatic and novel approach for UAV flight planning and control based on photogrammetric principles. Software which performs multiple tasks related to aerial photogrammetry and particularized to UAV systems was developed. Specifically,
the flight planning and control framework incorporates a robust ge...
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Citations
... The sensor was mounted on a quadcopter Carabo S3 (Icom3D, Asturias, Spain) ( Figure 2). The flight planning was performed by using UAV-GeoFlip Geomatic Flight Planning software [27]. The flight was planned and executed to establish a minimum forward overlap of 60% and a minimum side overlap of 20%, with a GSD of 5.09 cm/pix for the DSM (digital surface model). ...
Close-range remote sensing techniques employing multispectral sensors on unoccupied aerial vehicles (UAVs) offer both advantages and drawbacks in comparison to traditional remote sensing using satellite-mounted sensors. Close-range remote sensing techniques have been increasingly used in the field of precision agriculture. Planning the flight, including optimal flight altitudes, can enhance both geometric and temporal resolution, facilitating on-demand flights and the selection
of the most suitable time of day for various applications. However, the main drawbacks stem from the lower quality of the sensors being used compared to satellites. Close-range sensors can capture spectral responses of plants from multiple viewpoints, mitigating satellite remote sensing challenges, such as atmospheric interference, while intensifying issues such as bidirectional reflectance distribution function (BRDF) effects due to diverse observation angles and morphological variances associated with flight altitude. This paper introduces a methodology for achieving high-quality vegetation indices under varied observation conditions, enhancing reflectance by selectively utilizing well-geometry vegetation pixels, while considering factors such as hotspot, occultation, and BRDF effects. A non-parametric ANOVA analysis demonstrates significant statistical differences between the proposed methodology and the commercial photogrammetric software AgiSoft Metashape, in a case study of a vineyard in Fuente-Alamo (Albacete, Spain). The BRDF model is expected to
substantially improve vegetation index calculations in comparison to the methodologies used in satellite remote sensing and those used in close-range remote sensing.
... To mitigate possible risks (although they were not considered particularly relevant in our study area, such as collisions of the drone with topographic elements or vegetation), a digital elevation model (DEM) of the area was previously elaborated. In this flight the most essential geometric criteria for photogrammetric applications [13] were applied, which guaranteed the obtaining of high-quality cartographic data and a Ground Sampling Resolution (GSD) of 4 centim per pixel. ...
In the contemporary era, the exploitation of aquifers in the agricultural sector has become increasingly important. In response, researchers have directed their efforts towards the formulation of effective methodologies, with geophysical prospecting emerging as a fundamental tool in locating the best underground deposits. The magnetic prospecting technique can discriminate between different categories of rocks, which facilitates the localisation of geological contacts—an essential factor in determining the strategic location of boreholes, while electromagnetic time-domain prospecting helps in the definition of sedimentary strata. In particular, this process reveals the important influence of tertiary and metamorphic formations on the regional hydrogeological framework of the studied area. The variable yields recorded in the wells in the area that have yielded good results are a clear indication of the presence of aquifers. However, it is important to note that numerous wells have been drilled in this region that have yielded negligible or even zero flow rates. Prudent selection of the location and depth of boreholes is essential to ensure proper management of this resource. The use of drones equipped with magnetometers is essential to speed up the spatial mapping process. Empirical results corroborate the accurate classification of lithological units, thus facilitating the selection of sites for groundwater abstraction. These studies serve to validate initial hypotheses and profoundly enrich our understanding of the hydrogeological dynamics of the site, thus providing avenues for optimal and sustainable exploitation and future academic research.
... Due to the operating temperatures of UAV, inlet temperatures below zero were also used (Hernandez-Lopez et al., 2013). In the open literature, uniform heat generation approach is used to determine heat generation rate in battery cells. ...
Abstract
Purpose
Lithium-polymer batteries have common usage in the aviation industry, especially unmanned aerial vehicles (UAV). Overheating is a serious problem in lithium-polymer batteries. Various cooling methods are performed to keep lithium-polymer batteries in the desired temperature range. The purpose of this paper is to examine pouch-type lithium-polymer batteries with plate fins by using particle image velocimetry (PIV) and computational fluid dynamics (CFD) for UAVs.
Design/methodology/approach
Battery models were produced with a 3D printer. The upper surfaces of fabricated battery models were covered with plate fins with different fin heights and fin thicknesses. Velocities were obtained with PIV and CFD. Temperature dissipations were acquired with numerical simulations.
Findings
At the end of the study, the second battery model gave the lowest temperature values among the battery models. Temperature values of the seventh battery model were the highest temperatures. Fin cooling reduced the maximum cell temperatures noticeably. Numerical simulations agreed with PIV measurements well.
Practical implications
This paper takes into account two essential tools such as PIV and CFD, for fluid mechanics, which are significant in the aviation industry and engineering life.
Originality/value
The originality of this paper depends on the investigation of both PIV and CFD for UAVs and developing a cooling method that can be feasible for landing and take-off phases for UAVs.
... The sensor was a 4.8 × 3.6 mm charge coupled device (CCD), with a pixel size of 3.75 × 3.75 µm, resulting in an image size of 1280 × 960 (columns and rows). Image acquisition was established according to a flight plan computed using Microdrones Photogrammetric FLight Planning software (Hernandez-Lopez et al., 2013). Multispectral images were radiometrically and geometrically corrected. ...
... The sensor was a 4.8 × 3.6 mm charge coupled device (CCD), with a pixel size of 3.75 × 3.75 µm, resulting in an image size of 1280 × 960 (columns and rows). Image acquisition was established according to a flight plan computed using Microdrones Photogrammetric FLight Planning software (Hernandez-Lopez et al., 2013). Multispectral images were radiometrically and geometrically corrected. ...
Because of climate change and the scarce availability of natural resources there is a need to develop sustainable intensification strategies intended for optimizing water use in vineyards. In this study, water regime, fertilization and soil management practices were assessed in terms of vineyard water use, by evaluating the inter-row and crop line evapotranspiration (ET) components using the Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) model in combination with unmanned aerial vehicle multispectral and thermal images taken on five dates throughout the growing season. The application of the METRIC-UAV using high-resolution imagery was proven as a useful tool for evaluating the effects of sustainable intensification strategies on water use of crops where vegetation does not completely cover the soil, identifying the most efficient site-specific strategies for water conservation purposes. Moreover, METRIC-UAV allowed evaluating separately their effects on the inter-row and the crop line. Among the assessed sustainable intensification strategies, the application of mulching provided the highest water savings (- 28%) when compared to traditional soil tillage management, reducing inter-row soil evaporation by 63%, while increasing crop-line ET by 14%. In spite of this, the mulching application did not affect yield, but significantly enhanced water use efficiency (WUE) in terms of grape yield compared to tillage. The adoption of deficit irrigation (DI) strategies did not result in vine water stress that was severe enough to significantly affect crop line ET when compared with fully irrigated (FI)
vines. Both DI and FI strategies increased vine water use by 18% and 27%, respectively, as compared to the rainfed regime, with no differences found in the inter-row water consumption. DI and FI, in turn, significantly increased yield as compared to rainfed crops, leading to significant improvements in WUE. In the short term, the application of supplemental inorganic fertilizers did not modify either the vineyard water use or vine performance.
... The following table (Table 1) outlines the technical details of the different drone platforms and sensors used. For the imagery acquisition, different photogrammetric flights were planned and executed using a tool, Mflip, developed by the authors [44]. Special attention was focused on the different characteristics of the RGB and IRT cameras (i.e., resolution, field of view, etc.) so that the PV plants could be recorded with a single flight using both sensors simultaneously. ...
... In those cases where a simultaneous acquisition flight is not possible, two different flights will be required. Our flight-planning software [44] allows dealing with all these specifications, providing successful integration of RGB and IRT cameras. ...
Global awareness of environmental issues has boosted interest in renewable energy resources, among which solar energy is one of the most attractive renewable sources. The massive growth of PV plants, both in number and size, has motivated the development of new approaches for their inspection and monitoring. In this paper, a rigorous drone photogrammetry approach using optical Red, Green and Blue (RGB) and Infrared Thermography (IRT) images is applied to detect one of the most common faults (hot spots) in photovoltaic (PV) plants. The latest advances in photogrammetry and computer vision (i.e., Structure from Motion (SfM) and multiview stereo (MVS)), together with advanced and robust analysis of IRT images, are the main elements of the proposed methodology. We developed an in-house software application, SunMap, that allows automatic, accurate, and reliable detection of hot spots on PV panels. Along with the identification and geolocation of malfunctioning PV panels, SunMap provides high-quality cartographic products by means of 3D models and true orthophotos that provide additional support for maintenance operations. Validation of SunMap was performed in two different PV plants located in Spain, generating positive results in the detection and geolocation of anomalies with an error incidence lower than 15% as validated by the manufacturer’s standard electrical tests.
... Using a pinhole camera model (or, sometimes called projective camera model), i.e., a model that relates the physical image space to the physical workspace using the projective transformation [55], it is possible to calculate the GSD [56,57]: ...
... Graphically, these parameters can be sketched in the following picture (Figure 4b), where the focal length is exaggerated in order to identify the key elements of the photogrammetric approach; details of the focal length relative to the sensor are sketched in Figure 4c. Using a pinhole camera model (or, sometimes called projective camera model), i.e., a model that relates the physical image space to the physical workspace using the projective transformation [55], it is possible to calculate the GSD [56,57]: ...
In recent years, structure from motion (SfM) and multi-view stereo (MVS) algorithms have been successfully applied to stereo images generated by cameras mounted on unmanned aerial vehicle (UAV) platforms to build 3D models. Indeed, the approach based on the combination of SfM-MVS and UAV-generated images allows for cost-effective acquisition, fast and automated processing, and detailed and accurate reconstruction of 3D models. As a consequence, this approach has become very popular for representation, management, and conservation in the field of cultural heritage (CH). Therefore, this review paper discusses the use of UAV photogrammetry in CH environments with a focus on state of the art trends and best practices in image acquisition technologies and 3D model-building software. In particular, this paper intends to emphasise the different techniques of image acquisition and processing in relation to the different platforms and navigation systems available, as well as to analyse and deepen the aspects of 3D reconstruction that efficiently describe the entire photogrammetric process, providing further insights for new applications in different fields, such as structural engineering and conservation and maintenance restoration of sites and structures belonging to the CH field.
... However, it is a technological product in which there is little knowledge about the UAV usage method's effect on photogrammetric purposes on the FT and the BS and much less identified. The importance of parameters and their effect on the resulting product is investigated with many different purpose studies (Hernandez-Lopez et al. 2013;Martin et al. 2016). ...
... The analyses show that UAVs are technical equipment that is widely used in photogrammetry but does not have a definite optimization standard (Hernandez-Lopez et al. 2013). Using photogrammetric UAVs, optimization subjects in the literature either do not contain all the parameters that completely affect the FT of the UAV, or they cannot create a very realistic optimization because they are based on the data produced in the simulation (Behnck et al. 2015;Martin et al. 2016;Dewangan, Shukla, and Godfrey 2019;Herrero-Huerta, Rahmani, and Rainey 2020). ...
Artificial intelligence (AI) is undergoing a ground-breaking period. Recently, AI affects almost every part of human life. Using AI in path planning for Unmanned Aerial Vehicle (UAV) attracts attention as a novel need. The inputs that form the base of UAV use in photogrammetry are UAV Type (UT), Ground Sampling Distance (GSD), Overlap Rates (OR), and Atmospheric Conditions (AC). Input parameters directly impact the UAV’s Flight Time (FT) and Battery Status (BS). Weighting and optimizing these parameters are the main ideas of this study.
The effects of input values (GSD, OR, UT, AC) on the outputs (BS and FT) were optimized using Artificial Neural Networks (ANN) in this study. For the analysis, results have been produced in which different training algorithms are preferred (Gradient Descent – GD – and Levenberg-Marquardt – LM). The GD algorithm has reached 77.65% accuracy in FT estimation and 80.91% estimation accuracy on normalized data on the BS. Then, the correlation between the produced model and the input parameters and the output parameters was determined, and the weights of the inputs were revealed. As a result, it was determined that the AC parameter has the most significant effect on BS and FT. Also, it has been identified that the normalization process has a considerable impact on optimization.
... Flight planning was performed by using the Microdrones Photogrammetric Flight Planning software (MFLIP) [36]. Eight targets with known coordinates were used to georeference the obtained images and calibrate the cameras geometrically. ...
... Figure 4 shows the flowchart of the processes implemented with LAIC software in a multispectral orthoimage. Flight planning was performed by using the Microdrones Photogrammetric Flight Planning software (MFLIP) [36]. Eight targets with known coordinates were used to georeference the obtained images and calibrate the cameras geometrically. ...
The development of unmanned aerial vehicles (UAVs) and light sensors has required new approaches for high-resolution remote sensing applications. High spatial and temporal resolution spectral data acquired by multispectral and conventional cameras (or red, green, blue (RGB) sensors) onboard UAVs can be useful for plant water status determination and, as a consequence, for irrigation management. A study in a vineyard located in south-eastern Spain was carried out during the 2018, 2019, and 2020 seasons to assess the potential uses of these techniques. Different water qualities and irrigation application start throughout the growth cycle were imposed. Flights with RGB and multispectral cameras mounted on a UAV were performed throughout the growth cycle, and orthoimages were generated. These orthoimages were segmented to include only vegetation and calculate the green canopy cover (GCC). The stem water potential was measured, and the water stress integral (Sψ) was obtained during each irrigation season. Multiple linear regression techniques and artificial neural networks (ANNs) models with multispectral and RGB bands, as well as GCC, as inputs, were trained and tested to simulate the Sψ. The results showed that the information in the visible domain was highly related to the Sψ in the 2018 season. For all the other years and combinations of years, multispectral ANNs performed slightly better. Differences in the spatial resolution and radiometric quality of the RGB and multispectral geomatic products explain the good model performances with each type of data. Additionally, RGB cameras cost less and are easier to use than multispectral cameras, and RGB images are simpler to process than multispectral images. Therefore, RGB sensors are a good option for use in predicting entire vineyard water status. In any case, field punctual measurements are still required to generate a general model to estimate the water status in any season and vineyard.
... As a result, all images covering the survey area are acquired for the generation of a DEM, which is used to perform the 3D flight route planning. The 3D flight planning can effectively direct UAV to photographing positions with specific planning parameters (Hernandez-Lopez et al., 2013). It is the most significant part of the field activities and has a great influence on the accuracy and quality of the following generation of georeferenced data, such as 3D point clouds, DEM, and orthophotos (Jimenez-Jimenez et al., 2021). ...
In the mountainous areas passed by the Sichuan–Tibet Railway, rockfall is one of the important geological hazards with characteristics of unpredictable and sudden occurrences. For high and steep slopes, this study employs nap-of-the-object photogrammetry with the characteristic of close flight distance to reconstruct a 3D geological model, which is clear and qualified for discontinuity identification. For the rockfall investigation of areas where unstable blocks are widely distributed, this study proposes a new methodology for 3D rockfall risk statistical analysis to conduct well-directed rockfall simulations and perform a rockfall analysis on a tunnel portal. This methodology first narrows down the rockfall source regions through a field investigation and by slope aspect. Then, the critical source areas that threaten the tunnel portal are determined by preliminary simulation results. Finally, unstable blocks within the critical source areas are interpreted, and well-directed simulations are performed. The rockfall risk analysis on the tunnel portal is conducted on the basis of trajectory distributions and kinematic parameters. This methodology greatly simplifies the rockfall simulation process and reduces the workload of unstable block identification and interpretation. As a consequence, in the Kangyuqu area, several unstable blocks are identified for simulations. Results indicate that rockfalls reaching the tunnel portal have a kinetic energy range of 300–20,000 kJ, a velocity range of 8–30 m/s, and a maximum jump height of 25 m.
