RPV, UAV, UAS, RPAS … or just drone?

Granshaw, Stuart I.

doi:10.1111/phor.12244

Cited by 39 publications

(28 citation statements)

References 7 publications

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“…We consider in this section the planning of data acquisition from ground-based camera stations. Since drones (Granshaw, 2018a) are widely used in modern photogrammetric projects, when allowed by local regulations, the readers are suggested to refer to the specific literature (O'Connor et al, 2017;Pepe et al, 2018).…”

Section: Guidelines For Data Acquisition With Sfmmentioning

confidence: 99%

“…This includes the case of countries affected by war events or characterized by local unstable social/political condition, preventing experts to come from outside the region to carry out 3D surveying of the CH. The use of amateur digital cameras, the availability of cheap small drones (see Granshaw, 2018a), and the chance of using low-cost photogrammetric packages, can be all together exploited by local people to do the 3D surveying operations.…”

Section: Introductionmentioning

confidence: 99%

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Distance-Training for Image-Based 3d Modelling of Archeological Sites in Remote Regions

Yordanov¹,

Mostafavi²,

Scaioni³

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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The impressive success of Structure-from-Motion Photogrammetry (SfM) has spread out the application of image-based 3D reconstruction to a larger community. In the field of Archeological Heritage documentation, this has opened the possibility of training local people to accomplish photogrammetric data acquisition in those remote regions where the organization of 3D surveying missions from outside may be difficult, costly or even impossible. On one side, SfM along with low-cost cameras makes this solution viable. On the other, the achievement of high-quality photogrammetric outputs requires a correct image acquisition stage, being this the only stage that necessarily has to be accomplished locally. This paper starts from the analysis of the well-know "3x3 Rules" proposed in 1994 when photogrammetry with amateur camera was the state-of-the art approach and revises those guidelines to adapt to SfM. Three aspects of data acquisition are considered: geometry (control information, photogrammetric network), imaging (camera/lens selection and setup, illumination), and organization. These guidelines are compared to a real case study focused on Ziggurat Chogha Zanbil (Iran), where four blocks from ground stations and drone were collected with the purpose of 3D modelling.

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Section: Guidelines For Data Acquisition With Sfmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distance-Training for Image-Based 3d Modelling of Archeological Sites in Remote Regions

Yordanov¹,

Mostafavi²,

Scaioni³

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Thanks to development of terrestrial laser scanning (TLS -Vosselman and Maas, 2010) and the success of Structure-from-Motion (SfM - Granshaw, 2018b), in the latest 20 years this sector of photogrammetric 3D modelling (also called Terrestrial Photogrammetry) has significantly expanded. With the diffusion of drones (Giordan et al, 2018;Granshaw, 2018a), the possibility of reconstructing the terrain topography and the objects located on its surface by using high-resolution digital photos has impressively grown up. Mostly, the approach adopted to process the images acquired by drones is still based on SfM, which also allows to deal with less regular block geometry than in the case of standard aerial blocks (Barazzetti et al, 2010).…”

Section: Close-/near-range Sensingmentioning

confidence: 99%

Monitoring Alpine Glaciers From Close-Range to Satellite Sensors

Yordanov

Fugazza

Azzoni

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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In this paper the use of different types of remote-sensing techniques for monitoring topographic changes of Alpine glaciers is presented and discussed. Close range photogrammetry based on Structure-from-Motion approach is adopted to process images recorded from ground-based and drone-based stations in order to output dense point clouds. These are then directly compared to detect local changes by mean of M3C2 algorithm, while digital elevation models are interpolated to find global ice thinning and retreat. Medium-resolution satellite imagery can be exploited to monitor the glacier evolution at lower resolution but including the development and collapse of large crevasses. A case study concerning the Forni Glacier in the Raethian Alps (Italy) is presented to demonstrate the feasibility of the proposed approach by adopting data sets collected from 2016 to 2018.

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“…An unmanned aerial system (UAS) or unmanned aerial vehicle (UAV) is defined as a powered aerial vehicle that does not carry a human operator, uses aerodynamic forces to provide vehicle lift, and can fly autonomously or be remotely piloted aircrafts. In this last case, they are also called a remotely piloted aerial system (RPAS) (i.e., aerial platform (RPA) plus control station for pilot and operator (if applicable) actions [1][2][3]). UASs and RPASs (usually the same denomination is employed, even in the everyday jargon they are called drones) are mostly associated with military, industry, and other specialized operations, but with recent developments in the area of sensors and information technology in the last two decades, the scope of drones has been widened to other areas like agriculture [4].…”

Section: Introductionmentioning

confidence: 99%

Converting a Fixed-Wing Internal Combustion Engine RPAS into an Electric Lithium-Ion Battery-Driven RPAS

et al. 2020

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It is well proved that remotely piloted aircraft systems (RPASs) are very useful systems for remote sensing in precision agricultural labors. INTA (National Institute for Aerospace Applications) and the University of Huelva are involved in Tecnolivo Project that proposes the development of a marketable and easy-to-use technological solution that allows integrated, ecological, and optimized management of the olive grove through non-invasive monitoring of key agronomic parameters using RPASs. The information collected by the RPAS in regards to the state of the vegetation, such as hydric stress levels, plague detection, or maturation of the fruit, are very interesting for farmers when it comes to make decisions about their crops. Current RPAS applications for precision agriculture are mainly developed for small- to medium-sized crops using rotary-wing RPASs with small range and endurance operation, leaving aside large-sized crops. This work shows the conversion of a fully declassified and obsolete fixed-wing internal combustion engine (ICE) remotely piloted aircraft (RPA), used as aerial target for military applications and in reconnaissance and surveillance missions at low cost, into an electric lithium polymer (LiPo) battery-driven RPA that will be used for precision agriculture in large-sized crop applications, as well as other applications for tracking and monitoring of endangered animal species in national parks. This RPA, being over twenty years old, has undergone a deep change. The applied methodology consisted of the design of a new propulsion system, based on an electric motor and batteries, maintaining the main airworthiness characteristics of the aircraft. Some other novelties achieved in this study were: (1) Change to a more efficient engine, less heavy and bulky, with a greater ratio of torque vs. size. Modernization of the fly control system and geolocation system. (2) Modification of the type and material of the propeller, reaching a higher performance. (3) Replacement of a polluting fuel, such as gasoline, with electricity from renewable sources. (4) Development of a new control software, etc. Preliminary results indicate that the endurance achieved with the new energy and propulsion systems and the payload weight available in the RPA meet the expectations of the use of this type of RPAS in the study of large areas of crops and surveillance.

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RPV, UAV, UAS, RPAS … or just drone?

Cited by 39 publications

References 7 publications

Distance-Training for Image-Based 3d Modelling of Archeological Sites in Remote Regions

Distance-Training for Image-Based 3d Modelling of Archeological Sites in Remote Regions

Monitoring Alpine Glaciers From Close-Range to Satellite Sensors

Converting a Fixed-Wing Internal Combustion Engine RPAS into an Electric Lithium-Ion Battery-Driven RPAS

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