scholarly journals Photogrammetric mapping using unmanned aerial vehicle

Author(s):  
N. Graça ◽  
E. Mitishita ◽  
J. Gonçalves

Nowadays Unmanned Aerial Vehicle (UAV) technology has attracted attention for aerial photogrammetric mapping. The low cost and the feasibility to automatic flight along commanded waypoints can be considered as the main advantages of this technology in photogrammetric applications. Using GNSS/INS technologies the images are taken at the planned position of the exposure station and the exterior orientation parameters (position Xo, Yo, Zo and attitude ω, φ, χ) of images can be direct determined. However, common UAVs (off-the-shelf) do not replace the traditional aircraft platform. Overall, the main shortcomings are related to: difficulties to obtain the authorization to perform the flight in urban and rural areas, platform stability, safety flight, stability of the image block configuration, high number of the images and inaccuracies of the direct determination of the exterior orientation parameters of the images. In this paper are shown the obtained results from the project photogrammetric mapping using aerial images from the SIMEPAR UAV system. The PIPER J3 UAV Hydro aircraft was used. It has a micro pilot MP2128g. The system is fully integrated with 3-axis gyros/accelerometers, GPS, pressure altimeter, pressure airspeed sensors. A Sony Cyber-shot DSC-W300 was calibrated and used to get the image block. The flight height was close to 400 m, resulting GSD near to 0.10 m. The state of the art of the used technology, methodologies and the obtained results are shown and discussed. Finally advantages/shortcomings found in the study and main conclusions are presented

2021 ◽  
Vol 912 (1) ◽  
pp. 012075
Author(s):  
H Arinah ◽  
A S Thoha ◽  
Z Mardiyadi ◽  
O A Lubis

Abstract Agroforestry-based land use is widely used in society, particularly in rural areas. With a combination of tree crops (annual) and crops (seasonal), agroforestry patterns can maximize land utilization. Unmanned aircraft, often known as drones, can map and detect land cover to optimise land usage based on agroforestry. Drones have various advantages, including low cost, ease of acquisition, and the ability to utilize them in high-risk situations without endangering human life or in difficult or inaccessible places. They can also fly at low altitudes, resulting in cloud-free shots and sharper images. This research focuses on using an unmanned aerial vehicle (UAV) to map agroforestry patterns in Namolandur Village and detect and determine the area of each agroforestry pattern land cover using aerial camera photos. Using the Mavic 2 pro drone and Pix4D Mapper software for aerial photo processing, Namolandur village became the research subject. The data analysis revealed that agrisilviculture, agrosilvofishery, and agrosilvopastoral were the forms of land use with agroforestry patterns in the village of Namolandur. In addition, water guava, duku fruit (Lansium domestika), oil palm, coconut, and a combination of fish ponds, cattle, and goats are among the geographical analysis of the area and each form of land use.


2021 ◽  
Vol 13 (5) ◽  
pp. 965
Author(s):  
Marek Kraft ◽  
Mateusz Piechocki ◽  
Bartosz Ptak ◽  
Krzysztof Walas

Public littering and discarded trash are, despite the effort being put to limit it, still a serious ecological, aesthetic, and social problem. The problematic waste is usually localised and picked up by designated personnel, which is a tiresome, time-consuming task. This paper proposes a low-cost solution enabling the localisation of trash and litter objects in low altitude imagery collected by an unmanned aerial vehicle (UAV) during an autonomous patrol mission. The objects of interest are detected in the acquired images and put on the global map using a set of onboard sensors commonly found in typical UAV autopilots. The core object detection algorithm is based on deep, convolutional neural networks. Since the task is domain-specific, a dedicated dataset of images containing objects of interest was collected and annotated. The dataset is made publicly available, and its description is contained in the paper. The dataset was used to test a range of embedded devices enabling the deployment of deep neural networks for inference onboard the UAV. The results of measurements in terms of detection accuracy and processing speed are enclosed, and recommendations for the neural network model and hardware platform are given based on the obtained values. The complete system can be put together using inexpensive, off-the-shelf components, and perform autonomous localisation of discarded trash, relieving human personnel of this burdensome task, and enabling automated pickup planning.


2019 ◽  
Author(s):  
Catur A. Rokhmana ◽  
Imung A. Gumeidhidta ◽  
Martinus E. Tjahjadi

Recently, the Ministry of Agrarian Affairs announces a decree to accelerate a completion of the registration of land parcels of cadaster maps up to a scale of 1:1000. It is known that the use of Unmanned Aerial Vehicle based mapping system (UAV-Map) can produce orthophoto image with spatial resolution less than 10 cm, but it is not yet known whether UAV-Map implementation is able to identify boundary of land parcel in any condition. Therefore, this paper would analyze the planimetric accuracy that is conformed to the regulation of State Minister of Agrarian Affairs/Head of National Land Agency No.3, 1997 both for urban and rural areas. Two testing areas are established which located on urban area and rural area respectively. Flight missions are conducted using a fixed-wing aircraft equipped with a consumer grade camera and a navigational grade GPS-INS system. Orthophoto maps are produced by using Agisoft Photoscan software. Digitizing of parcel boundaries are followed both on an existing map and on the orthophoto maps. Deviations in areas are expressed in terms of the RMSE figures. Planimetric accuracies as indicated by the RMSE value are of 0,044 m for urban areas and 0,122 m for rural area. It is showed that all discrepancies of the parcels area are still below the recommended threshold values of the regulation. It is can be concluded that the orthophoto maps obtained by using a low cost UAV-Map system can be used to identify land parcels boundaries and to determine the parcel area.


2012 ◽  
Vol 116 (1183) ◽  
pp. 895-914 ◽  
Author(s):  
C-S Lee ◽  
F-B Hsiao

Abstract This paper presents the design and implementation of a vision-based automatic guidance system on a fixed-wing unmanned aerial vehicle (UAV). The system utilises a low-cost ordinary video camera and simple but efficient image processing techniques widely used in computer-vision technology. The paper focuses on the identification and extraction of geographical tracks such as rivers, coastlines, and roads from real-time aerial images. The image processing algorithm primarily uses colour properties to isolate the geographical track of interest from its background. Hough transform is eventually used to curve-fit the profile of the track which yields a reference line on the image plane. A guidance algorithm is then derived based on this information. In order to test the vision-based automatic guidance system in the laboratory without actually flying the UAV, a hardware-in-the-loop simulation system is developed. Description regarding the system and significant simulation result are presented in the paper. Finally, an actual test flight where the UAV successfully follows a stretch of a river under automatic vision-based guidance is also presented and discussed.


1991 ◽  
Vol 24 (5) ◽  
pp. 9-19 ◽  
Author(s):  
Baozhen Wang

Various ecological waste treatment and utilization systems (EWTUS) available in urban and rural areas in China are described, among which are land treatment and utilization systems (LTUS), eco-pond systems mainly consisting of macrohydrophytes-growing ponds, fish ponds and duck/geese ponds, and comprehensive circulation eco–systems for the treatment and utilization of wastes in rural areas, such as semi–closed eco–system in fish ponds, “rice–fish” and “rice–azolla–fish” symbiotic systems, recycling eco–systems with methane-generating digesters as central link, and comprehensive recycling eco–systems with digesters and eco–ponds as central link. In the various EWTUS, the sewage and wastewaters and other wastes are utilized and converted into various forms of recoverable resources and/or energy, while they are being purified to good quality effluents, meeting their respective discharge standards, and hence acceptable to receiving waters.


2019 ◽  
Vol 14 (1) ◽  
pp. 27-37
Author(s):  
Matúš Tkáč ◽  
Peter Mésároš

Abstract An unmanned aerial vehicle (UAVs), also known as drone technology, is used for different types of application in the civil engineering. Drones as a tools that increase communication between construction participants, improves site safety, uses topographic measurements of large areas, with using principles of aerial photogrammetry is possible to create buildings aerial surveying, bridges, roads, highways, saves project time and costs, etc. The use of UAVs in the civil engineering can brings many benefits; creating real-time aerial images from the building objects, overviews reveal assets and challenges, as well as the broad lay of the land, operators can share the imaging with personnel on site, in headquarters and with sub-contractors, planners can meet virtually to discuss project timing, equipment needs and challenges presented by the terrain. The aim of this contribution is to create a general overview of the use of UAVs in the civil engineering. The contribution also contains types of UAVs used for construction purposes, their advantages and also disadvantages.


Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4705 ◽  
Author(s):  
Adil Shah ◽  
Joseph Pitt ◽  
Khristopher Kabbabe ◽  
Grant Allen

Point-source methane emission flux quantification is required to help constrain the global methane budget. Facility-scale fluxes can be derived using in situ methane mole fraction sampling, near-to-source, which may be acquired from an unmanned aerial vehicle (UAV) platform. We test a new non-dispersive infrared methane sensor by mounting it onto a small UAV, which flew downwind of a controlled methane release. Nine UAV flight surveys were conducted on a downwind vertical sampling plane, perpendicular to mean wind direction. The sensor was first packaged in an enclosure prior to sampling which contained a pump and a recording computer, with a total mass of 1.0 kg. The packaged sensor was then characterised to derive a gain factor of 0.92 ± 0.07, independent of water mole fraction, and an Allan deviation precision (at 1 Hz) of ±1.16 ppm. This poor instrumental precision and possible short-term drifts made it non-trivial to define a background mole fraction during UAV surveys, which may be important where any measured signal is small compared to sources of instrumental uncertainty and drift. This rendered the sensor incapable of deriving a meaningful flux from UAV sampling for emissions of the order of 1 g s−1. Nevertheless, the sensor may indeed be useful when sampling mole fraction enhancements of the order of at least 10 ppm (an order of magnitude above the 1 Hz Allan deviation), either from stationary ground-based sampling (in baseline studies) or from mobile sampling downwind of sources with greater source flux than those observed in this study. While many methods utilising low-cost sensors to determine methane flux are being developed, this study highlights the importance of adequately characterising and testing all new sensors before they are used in scientific research.


10.14311/754 ◽  
2005 ◽  
Vol 45 (4) ◽  
Author(s):  
P. Kaňovský ◽  
L. Smrcek ◽  
C. Goodchild

The study described in this paper deals with the issue of a design tool for the autopilot of an Unmanned Aerial Vehicle (UAV) and the selection of the airdata and inertial system sensors. This project was processed in cooperation with VTUL a PVO o.z. [1]. The feature that distinguishes the autopilot requirements of a UAV (Figs. 1, 7, 8) from the flight systems of conventional manned aircraft is the paradox of controlling a high bandwidth dynamical system using sensors that are in harmony with the low cost low weight objectives that UAV designs are often expected to achieve. The principal function of the autopilot is flight stability, which establishes the UAV as a stable airborne platform that can operate at a precisely defined height. The main sensor for providing this height information is a barometric altimeter. The solution to the UAV autopilot design was realised with simulations using the facilities of Matlab® and in particular Simulink®[2]. 


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