scholarly journals Controller for a Low-Altitude Fixed-Wing UAV on an Embedded System to Assess Specific Environmental Conditions

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Johannes von Eichel-Streiber ◽  
Christoph Weber ◽  
Jesús Rodrigo-Comino ◽  
Jens Altenburg

The use of an appropriate sensor on an unmanned aerial vehicle (UAV) is vital to assess specific environmental conditions successfully. In addition, technicians and scientists also appreciate a platform to carry the sensors with some advantages such as the low costs or easy pilot management. However, extra requirements like a low-altitude flight are necessary for special applications such as plant density or rice yield. A rotary UAV matches this requirement, but the flight endurance is too short for large areas. Therefore, in this article, a fixed-wing UAV is used, which is more appropriate because of its longer flight endurance. It is necessary to develop an own controller system to use special sensors such as Lidar or Radar on the platform as a multifunctionality system. Thereby, these sensors are used to generate a digital elevation model and also as a collision avoidance sensor at the same time. To achieve this goal, a small UAV was equipped with a hardware platform including a microcontroller and sensors. After testing the system and simulation, the controller was converted into program code to implement it on the microcontroller. After that, several real flights were performed to validate the controller and sensors. We demonstrated that the system is able to work and match the high requirements for future research.

2021 ◽  
Vol 2 ◽  
Author(s):  
Sasha. Z. Leidman ◽  
Åsa K. Rennermalm ◽  
Richard G. Lathrop ◽  
Matthew. G. Cooper

The presence of shadows in remotely sensed images can reduce the accuracy of land surface classifications. Commonly used methods for removing shadows often use multi-spectral image analysis techniques that perform poorly for dark objects, complex geometric models, or shaded relief methods that do not account for shadows cast on adjacent terrain. Here we present a new method of removing topographic shadows using readily available GIS software. The method corrects for cast shadows, reduces the amount of over-correction, and can be performed on imagery of any spectral resolution. We demonstrate this method using imagery collected with an uncrewed aerial vehicle (UAV) over a supraglacial stream catchment in southwest Greenland. The structure-from-motion digital elevation model showed highly variable topography resulting in substantial shadowing and variable reflectance values for similar surface types. The distribution of bare ice, sediment, and water within the catchment was determined using a supervised classification scheme applied to the corrected and original UAV images. The correction resulted in an insignificant change in overall classification accuracy, however, visual inspection showed that the corrected classification more closely followed the expected distribution of classes indicating that shadow correction can aid in identification of glaciological features hidden within shadowed regions. Shadow correction also caused a substantial decrease in the areal coverage of dark sediment. Sediment cover was highly dependent on the degree of shadow correction (k coefficient), yet, for a correction coefficient optimized to maximize shadow brightness without over-exposing illuminated surfaces, terrain correction resulted in a 49% decrease in the area covered by sediment and a 29% increase in the area covered by water. Shadow correction therefore reduces the overestimation of the dark surface coverage due to shadowing and is a useful tool for investigating supraglacial processes and land cover change over a wide variety of complex terrain.


2020 ◽  
Vol 20 (4) ◽  
pp. 63-73
Author(s):  
Jaehee Choi ◽  
Namgyun Kim ◽  
Bongjin Choe ◽  
Byonghee Jun

In this study, the risk of rockfall on incision slopes adjacent to roads was evaluated using the RocFall program. The study area was a slope adjacent to the road leading to a university campus in Samcheok-si, Gangwon-do, with an area of 774 m<sup>2</sup> and an average slope of approximately 43°. A rock shed was installed at the lower zone of the slope. A 3D model of the terrain was generated based on point cloud data gathered using a UAV (unmanned aerial vehicle). Fast and accurate orthoimages were captured by UAV and high-resolution digital surface models (DSMs) were produced; these data were used to assess the risk of rockfall. Compared to terrain extraction using a digital elevation model (DEM) generated from an existing digital map, terrain extraction using a UAV was more effective in deriving results close to the actual situation in the field, especially for the analysis of rockfall jump height and kinetic energy. The necessity of constructing 3D topographic data using UAVs to predict rockfall disasters in mountainous regions was confirmed.


OENO One ◽  
2016 ◽  
Vol 50 (3) ◽  
Author(s):  
Léo Pichon ◽  
Arnaud Ducanchez ◽  
Hélène Fonta ◽  
Bruno Tisseyre

<p style="text-align: justify;"><strong>Aims:</strong> This work aims to study the quality of low cost Digital Surface Models (DSMs) obtained with Unmanned Aerial Vehicle (UAV) images and to test whether these DSMs meet common requirements of the wine industry.</p><p style="text-align: justify;"><strong>Methods and results: </strong>Experiments were carried out on a 4-ha vineyard located 10 km north of Beziers (France). The experimental site presents slope and aspect variations representative of mechanised commercial vineyards in Languedoc Roussillon. DSMs were provided by three UAV companies selected for the diversity of their solutions in terms of image capture altitude, type of UAV and image processing software. DSMs were obtained by photogrammetry and correspond to commercial products usually delivered by UAV companies. DSMs from UAV were compared to a reference Digital Elevation Model (DEM) acquired by a laser tachymeter. Four indicators were used to test the quality of DSMs: the mean error and its dispersion in the XY plane and in elevation Z. Results show a good georeferencing of the DSMs (MeanErrorXY&lt;10 cm) and a similar quality in elevation (MeanErrorZ&lt;10 cm) estimation. Results also show that the error in elevation is highly spatially structured. The spatial patterns observed did not depend on the elevation and could be related to algorithms used to compute the DSMs.</p><p style="text-align: justify;"><strong>Conclusion: </strong>Data acquisition and processing methods have an impact on the quality of the DSMs provided by the UAV companies. DSM qualities are good enough to meet commercial vineyard requirements. The tested DSMs fit the requirements to assess field characteristics (elevation, slope, aspects) which may be important for terroir characterisation purposes.</p><p style="text-align: justify;"><strong>Significance and impact of the study:</strong> This study proves that elevation data derived from UAV present an accuracy equivalent to the reference system used in this study. The rapidity, the low cost and the high spatial resolution of these data offer significant opportunities for the development of new services for the wine industry for field characterisation.</p>


Author(s):  
T. Nakano ◽  
I. Kamiya ◽  
M. Tobita ◽  
J. Iwahashi ◽  
H. Nakajima

Nishinoshima volcano in Ogasawara Islands has erupted since November, 2013. This volcanic eruption formed and enlarged a new island, and fused the new island with the old Nishinoshima Island. We performed automated aerial photographing using an Unmanned Aerial Vehicle (UAV) over the joined Nishinoshima Island on March 22 and July 4, 2014. We produced ortho-mosaic photos and digital elevation model (DEM) data by new photogrammetry software with computer vision technique, i.e. Structure from Motion (SfM) for estimating the photographic position of the camera and Multi-view Stereo (MVS) for generating the 3-D model. We also estimated the area and volume of the new island via analysis of ortho-mosaic photo and DEM data. Transition of volume estimated from the UAV photographing and other photographing shows the volcanic activity still keeps from initial level. The ortho-mosaic photos and DEM data were utilized to create an aerial photo interpretation map and a 3-D map. These operations revealed new knowledge and problems to be solved on the photographing and analysis using UAV and new techniques as this was first case in some respects.


2019 ◽  
Vol 1 ◽  
pp. 1-7
Author(s):  
Klemen Kozmus Trajkovski ◽  
Gašper Štebe ◽  
Dušan Petrovič

<p><strong>Abstract.</strong> Our research is based on a large case study of Unmanned Aerial Vehicle (UAV) surveys, modelling and visualizations of the Doblar accumulation basin. The various approaches for UAV surveying of large, demanding terrain configurations, and the benefits of surveying products used as a basis for other interdisciplinary hydrological and environmental services were researched. The demanding mountainous terrain, the steep slopes and deep and narrow streams required detailed pre-planning of the survey, including the pre-survey terrain overview. The accumulation basin was emptied merely for a short period; thus, the survey was performed in unfavourable weather conditions, which included coldness, snowfall and wind. Point clouds were generated and georeferenced from the 4377 recorded photos. The dense point cloud contained approximately 222 million points in the medium setting and more than a billion in the high setting. A 3D model was built from the data. This became the basis for numerous further analyses and for the presentation using cartographic principles: a digital elevation model with a resolution of 10&amp;thinsp;cm, an orthophoto with a resolution of 10&amp;thinsp;cm, a 3D model draped with orthophoto, contour lines with a 1&amp;thinsp;m interval, topographic profiles, calculations of volumes at different water levels, a flythrough, augmented reality and a video simulation of the water level changes. The model can also serve as a basis for hydraulic and environmental analysis and simulations or used for analyses of the accumulation and deposition of river material compared with previous and future surveys.</p>


2016 ◽  
Vol 7 (15) ◽  
pp. 87
Author(s):  
Antonia Spanò ◽  
Filiberto Chiabrando ◽  
Livio Dezzani ◽  
Antonio Prencipe

<p>The reconstructive study of the urban arrangement of Susa in the 4th century arose from the intention to exploit some resources derived from local studies, and survey activities, fulfilled by innovative methods from which the modelling of architectural heritage (AH) and virtual reconstructions are derived.  The digital Segusio presented in this paper is the result of intensive discussion and exchange of data and information during the urban landscape documentation activities, and due to the technology of virtual model generation, making it possible to recreate the charm of an ancient landscape. The land survey has been accomplished using aerial and terrestrial acquisition systems, mainly through digital photogrammetry from UAV (Unmanned Aerial Vehicle) and terrestrial laser scanning.  Results obtained from both the methods have been integrated into the medium scale geographical data from the regional map repository, and some processing and visualization supported by GIS (Geographical Information System) has been achieved. Subsequently, with the help of accurate and detailed DEM (Digital Elevation Model) and other architectural scale models related to the ancient heritage, this ancient landscape was modelled. The integration of the history of this city with digital and multimedia resources will be offered to the public in the city museum housed in the restored castle of Maria Adelaide (Savoy dynasty, 11th century), which stands in the place where the acropolis of the city of Susa lay in ancient times.</p>


2020 ◽  
Vol 8 (5) ◽  
pp. 5409-5414

This study tested the accuracy and precision of the UAV-SfM method, an automated photogrammetry technique called SfM (Structure from Motion) using multiple pictures taken by UAV (Unmanned Aerial Vehicle), in a section of Saba river, Yamaguchi, Japan. The method was applied in the submerged area as well as in the exposed area, taking into account the refraction at the water surface, for the first time in domestic rivers. When the resultant DEM (Digital Elevation Model) is considered as the map of riverbed elevation, the RMS (Root Mean Square) error and R2 (coefficient of determination) of UAV-SfM were 0.165 m and 0.93, respectively. In pixels with thick algae cover, large apparent overestimations reaching 0.351 m at maximum were observed because UAV-SfM actually measures the algae surface elevation, not the riverbed elevation. Error analyses also showed that the refraction correction method adopted in this study is working well in spite of its simplicity.


Author(s):  
C. Serifoglu ◽  
O. Gungor ◽  
V. Yilmaz

Digital Elevation Model (DEM) generation is one of the leading application areas in geomatics. Since a DEM represents the bare earth surface, the very first step of generating a DEM is to separate the ground and non-ground points, which is called ground filtering. Once the point cloud is filtered, the ground points are interpolated to generate the DEM. LiDAR (Light Detection and Ranging) point clouds have been used in many applications thanks to their success in representing the objects they belong to. Hence, in the literature, various ground filtering algorithms have been reported to filter the LiDAR data. Since the LiDAR data acquisition is still a costly process, using point clouds generated from the UAV images to produce DEMs is a reasonable alternative. In this study, point clouds with three different densities were generated from the aerial photos taken from a UAV (Unmanned Aerial Vehicle) to examine the effect of point density on filtering performance. The point clouds were then filtered by means of five different ground filtering algorithms as Progressive Morphological 1D (PM1D), Progressive Morphological 2D (PM2D), Maximum Local Slope (MLS), Elevation Threshold with Expand Window (ETEW) and Adaptive TIN (ATIN). The filtering performance of each algorithm was investigated qualitatively and quantitatively. The results indicated that the ATIN and PM2D algorithms showed the best overall ground filtering performances. The MLS and ETEW algorithms were found as the least successful ones. It was concluded that the point clouds generated from the UAVs can be a good alternative for LiDAR data.


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