scholarly journals Monitoring Bituminous Layers Using Thermal Images

2020 ◽  
Vol 9 (1) ◽  
pp. 22-37
Author(s):  
Viorica David ◽  
Anda Ligia Belc ◽  
Maria-Roberta Jianu ◽  
Cosmin Constantin Muşat

Abstract The importance of mastering the temperatures of laying and compacting the bituminous layers is addressed by a multitude of researches in the field, but the treatment of their control possibilities throughout the work surface is less addressed. Checking the temperatures through classical methods (usually point measurements with a manual thermometer or on the direction of the thermometer attached to the beam of the spreading-finishing machine) can outline an image of the working temperatures, but cannot certify that the entire surface of the layer is at the same temperature. This article presents a new method for monitoring bituminous layers during execution, on an experimental road sector, with the help of a UAV (UAV - Unmanned Aerial Vehicle), equipped with two image capture cameras (for the visible area and for the infrared field). Following the qualitative analysis of the thermal images, information is obtained regarding the place where there are anomalies of the temperature uniformity, on the surface of the freshly laid bituminous layer.

Author(s):  
А.С. Алексеев ◽  
А.А. Никифоров ◽  
А.А. Михайлова ◽  
М.Р. Вагизов

В связи со старением информационных материалов о состоянии лесов существует потребность в разработке новых методов таксации древостоев, основанных на применении последних научно-технических достижений в области теории структуры и продуктивности древостоев, дистанционных методов изучения лесов, информационных и ГИС технологий. В статье приведены результаты разработки и проверки нового метода определения таксационных характеристик сомкнутых насаждений на основе правила 3/2 и подобных ему правил Хильми и Рейнеке, с одной стороны, и определения числа деревьев на единице площади по снимку сверх высокого разрешения, полученного с помощью БПЛА, с другой. С теоретической точки зрения эта зависимости величин запаса, средней высоты и среднего диаметра от числа стволов на единице площади относятся к классу аллометрических связей, очень часто встречающихся при количественном описании соотношений частей биологических систем разных уровней иерархии, от организмов до экосистем. Параметры аллометрических зависимостей запаса, средних высоты и диаметра от числа стволов на единице площади были определены для основных лесообразующих пород по данным таблиц хода роста нормальных (полных) древостоев с теоретическим показателем степени и затем использованы для расчетов. Число деревьев на единице площади определялось по снимку с разрешением 7,13 см/пиксель, полученному с помощью 4-роторной платформы. Обработка материалов аэрофотосъемки была выполнена в специализированной фотограмметрической системе Agisoft Photoscan. В результате были получены ортофотоплан и цифровая модель поверхности крон деревьев на изучаемую территорию с определением их высот. Для автоматизированной обработки полученных изображений с целью получения значений числа деревьев на единицу площади был создан специализированный скрипт на языке Java. Погрешности определения таксационных характеристик древостоев предлагаемым методом не выше установленных действующими нормативными материалами. Every time there is a demand for new innovative methods of forest resources estimation based on last achievements in theoretical science, remote sensing methods, information and GIS-technologies. In the paper are presented a new method and the results of its application to forest stands growing stock, mean height and diameter determination. The method is based on rule 3/2 and similar Reineke and Hilmy rules, on one hand and high resolution image made by unmanned aerial vehicle, which used for determination of number of trees per area unit, on other. The above rules are well known in quantitative biology as an allometric and widely used for description of different kind of relations in biological systems of various scale: from organisms to ecosystems. Parameters of above allometric relationships between growing stock, mean height and diameter and stems density per area unit was determine on the base of full stock growth and yield tables for main tree species and after used for experimental calculations. The number of trees per area unit was determined after special treatment of high resolution image made by unmanned flying machine. The growing stock, mean height and diameter determined by suggested method was compared with the data of regular forest inventory. Comparison gives positive result and method may be recommended for further development.


2017 ◽  
Vol 15 (41) ◽  
pp. 9-26
Author(s):  
Andrés Espinal Rojas ◽  
Andrés Arango Espinal ◽  
Luis Ramos ◽  
Jorge Humberto Erazo Aux

This paper describes the development and implementation of a six-pointed Unmanned Aerial Vehicle [UAV] prototype, designed for finding lost people in hard to access areas, using Arduino MultiWii platform. A platform capable of performing a stable flight to identify people through an on-board camera and an image processing algorithm was developed. Although the use of UAV represents a low cost and quick response –in terms of displacement– solution, capable to prevent or reduce the number of deaths of lost people in away places, also represents a technological challenge, since the recognition of objects from an aerial view is difficult, due to the distance of the UAV to the objective, the UAV’s position and its constant movement. The solution proposed implements an aerial device that performs the image capture, wireless transmission and image processing while it is in a controlled and stable flight.


2021 ◽  
Vol 13 (23) ◽  
pp. 4811
Author(s):  
Rudolf Urban ◽  
Martin Štroner ◽  
Lenka Línková

Lately, affordable unmanned aerial vehicle (UAV)-lidar systems have started to appear on the market, highlighting the need for methods facilitating proper verification of their accuracy. However, the dense point cloud produced by such systems makes the identification of individual points that could be used as reference points difficult. In this paper, we propose such a method utilizing accurately georeferenced targets covered with high-reflectivity foil, which can be easily extracted from the cloud; their centers can be determined and used for the calculation of the systematic shift of the lidar point cloud. Subsequently, the lidar point cloud is cleaned of such systematic shift and compared with a dense SfM point cloud, thus yielding the residual accuracy. We successfully applied this method to the evaluation of an affordable DJI ZENMUSE L1 scanner mounted on the UAV DJI Matrice 300 and found that the accuracies of this system (3.5 cm in all directions after removal of the global georeferencing error) are better than manufacturer-declared values (10/5 cm horizontal/vertical). However, evaluation of the color information revealed a relatively high (approx. 0.2 m) systematic shift.


Agriculture ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 176
Author(s):  
Koji Kakutani ◽  
Yoshinori Matsuda ◽  
Teruo Nonomura ◽  
Yoshihiro Takikawa ◽  
Kazumi Osamura ◽  
...  

The purpose of the study was to construct an electrostatic insect-capturing apparatus that could be applied to a drone (quadcopter). For this purpose, a double-charged dipolar electric field screen (DD-screen) was constructed using oppositely charged insulator tubes that was then attached to a drone. For charging, the inner surface of the tubes was coated with a conductive paste and then linked to a negative or positive voltage generator. The opposite charges of the tubes formed an electric field between them and created an attractive force to capture insects that entered the field. The DD-screen constructed here was sufficiently light to enable its attachment to a drone. The screen was hung from the drone perpendicular to the direction of drone movement, so as to receive the longitudinal airflow produced by the movement of the drone. It was positioned 1.8 m below the drone body to avoid the influence of the downward slipstream generated by the rotating propellers. Eventually, the drone was able to conduct a stable flight, with sufficient endurance, and captured airborne insects carried by an airflow of 8 m/s during the flight. This study, therefore, provides an experimental basis for establishing a new method for conducting trap-based monitoring of airborne insects during remote-controlled flight through operation of a DD-screen attached to a drone.


Author(s):  
T. J. Lei ◽  
R. R. Xu ◽  
J. H. Cheng ◽  
W. L. Song ◽  
W. Jiang ◽  
...  

Abstract. Remote sensing system fitted on UAV (Unmanned Aerial Vehicle) can obtain clear images and high-resolution aerial photographs. It has advantages of flexibility, convenience and ability to work full-time. However, there are some problems of UAV image such as small coverage area, large number, irregular overlap, etc. How to obtain a large regional map quickly becomes a major obstacle to UAV remote sensing application. In this paper, a new method of fast registration of UAV remote sensing images was proposed to meet the needs of practical application. This paper used Progressive Sample Consensus (PROSAC) algorithm to improve the matching accuracy by removed a large number of mismatching point pairs of remote sensing image registration based-on SURF (Speed Up Robust Feature) algorithm, and GPU (Graphic Processing Unit) was also used to accelerate the speed of improved SURF algorithm. Finally, geometric verification was used to achieve mosaic accuracy in survey area. The number of feature points obtained by using improved SURF based-on PROSAC algorithm was only 9.5% than that of SURF algorithm. Moreover, the accuracy rate of improved method was about 99.7%, while the accuracy rate of improved SURF algorithm was increased by 8% than SURF algorithm. Moreover, the improved running time of SURFGPU algorithm for UAV remote sensing image registration was a speed of around 16 times than SURF algorithm, and the image matching time had reached millisecond level. Thus, improved SURF algorithm had better matching accuracy and executing speed to meet the requirements of real-time and robustness in UAV remote sensing image registration.


2020 ◽  
Vol 77 (1) ◽  
pp. 527-537 ◽  
Author(s):  
Xuan Li ◽  
Durham Ken Giles ◽  
Franz J Niederholzer ◽  
John T Andaloro ◽  
Edward B Lang ◽  
...  

Author(s):  
A. Pathania ◽  
D. P. Gangwar ◽  
Shivanshu ◽  
Poonam ◽  
Arpita

A drone, technological term Unmanned aerial vehicle (UAV), means any aircraft operating or designed to operate autonomously or to be piloted remotely without a pilot on board. Essentially, a drone is a flying robot that can be remotely controlled or fly autonomously through software-controlled flight plans in their embedded systems, working in conjunction with onboard sensors and GPS. The easy accessibility to everyone led to an increase in drone crime. Criminals are using drones in many malicious activities worldwide due to the drones’ ability to offer live-stream, real-time video, and image capture, along with the ability to fly and transport goods. Terrorist groups are using aerial drones to conduct and coordinate attacks. Forensic laboratories have been receiving Drone cases throughout India. The drone has been built that can be operated by a radio frequency controller and send live audio-visual feedback. This paper aims to provide a case study of Drone, DJI Phantom 4 and presents the acquisition, examination, analysis of important artifacts recorded flight data and discuss some possible data extractions from its flash memory, GPS (navigator) & SD card.


2021 ◽  
Vol 304-305 ◽  
pp. 108433
Author(s):  
Samuel Ortega-Farias ◽  
Wladimir Esteban-Condori ◽  
Camilo Riveros-Burgos ◽  
Fernando Fuentes-Peñailillo ◽  
Matthew Bardeen

2021 ◽  
Vol 13 (17) ◽  
pp. 3526
Author(s):  
Pengfei Chen ◽  
Xiao Ma ◽  
Fangyong Wang ◽  
Jing Li

Crop row detection using unmanned aerial vehicle (UAV) images is very helpful for precision agriculture, enabling one to delineate site-specific management zones and to perform precision weeding. For crop row detection in UAV images, the commonly used Hough transform-based method is not sufficiently accurate. Thus, the purpose of this study is to design a new method for crop row detection in orthomosaic UAV images. For this purpose, nitrogen field experiments involving cotton and nitrogen and water field experiments involving wheat were conducted to create different scenarios for crop rows. During the peak square growth stage of cotton and the jointing growth stage of wheat, multispectral UAV images were acquired. Based on these data, a new crop detection method based on least squares fitting was proposed and compared with a Hough transform-based method that uses the same strategy to preprocess images. The crop row detection accuracy (CRDA) was used to evaluate the performance of the different methods. The results showed that the newly proposed method had CRDA values between 0.99 and 1.00 for different nitrogen levels of cotton and CRDA values between 0.66 and 0.82 for different nitrogen and water levels of wheat. In contrast, the Hough transform method had CRDA values between 0.93 and 0.98 for different nitrogen levels of cotton and CRDA values between 0.31 and 0.53 for different nitrogen and water levels of wheat. Thus, the newly proposed method outperforms the Hough transform method. An effective tool for crop row detection using orthomosaic UAV images is proposed herein.


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