scholarly journals UAV – a useful tool for monitoring woodlands

2014 ◽  
Vol 18 (2) ◽  
pp. 46-52 ◽  
Author(s):  
Anna Zmarz
Keyword(s):  
Field Research ◽  
Image Data ◽  
Large Field ◽  
Unmanned Aerial Systems ◽  
Digital Cameras ◽  
Forest Division ◽  
Human Costs ◽  
The One ◽  
Aerial Systems ◽  
Spectral Channels

Abstract Unmanned aerial systems are in many countries one of the most dynamically developing branches of technology. They have also been recognized and are being utilized by scientists who find remote sensing indispensable in their work. Today, it is increasingly common to find research teams utilizing so-called drones in field research. Unmanned systems are becoming ever more important for environment monitoring by, on the one hand, providing data from inaccessible or remote areas, and, on the other hand, reducing the human costs required by traditional large field teams while also increasing the efficiency of the work. This paper presents the possibility of utilizing UAVs for image data collection in woodland areas. Flights over Głuchów and an Arboretum were performed using two different UAVs (Mentor, AVI). The flights were made in 2010 in the middle of the growing season. Images were taken with Sigma DP2 digital cameras in four spectral channels: R (red), G (green), B (blue) and IR (infrared). Images were saved in 8-bit. The Głuchów forest complex is located in the Głuchów forest district, which forms a part of the Rogów forest division. From the administrative viewpoint, the forest division is located in the Łódzkie province, Skierniewicki Poviat. The Arboretum is a park with a collection of trees and shrubs from different regions of the world. The area is characterized by a high variability of species and trees of varying heights. It is located in the Łódzkie province, Skierniewicki Poviat.

scholarly journals Error simulations of uncorrected NDVI and DCVI during remote sensing measurements from UAS

2014 ◽  
Vol 18 (2) ◽  
pp. 35-45 ◽  
Author(s):  
Michał T. Chiliński ◽  
Marek Ostrowski
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Vegetation Index ◽  
Vegetation Mapping ◽  
Radiative Transfer Model ◽  
Unmanned Aerial Systems ◽  
Transfer Model ◽  
Digital Cameras ◽  
Aerial Systems

Abstract Remote sensing from unmanned aerial systems (UAS) has been gaining popularity in the last few years. In the field of vegetation mapping, digital cameras converted to calculate vegetation index (DCVI) are one of the most popular sensors. This paper presents simulations using a radiative transfer model (libRadtran) of DCVI and NDVI results in an environment of possible UAS flight scenarios. The analysis of the results is focused on the comparison of atmosphere influence on both indices. The results revealed uncertainties in uncorrected DCVI measurements up to 25% at the altitude of 5 km, 5% at 1 km and around 1% at 0.15 km, which suggests that DCVI can be widely used on small UAS operating below 0.2 km.

scholarly journals An Improved Algorithm for Low-Level Turbulence Forecasting

2018 ◽  
Vol 57 (6) ◽  
pp. 1249-1263 ◽  
Author(s):  
Domingo Muñoz-Esparza ◽  
Robert Sharman
Keyword(s):  
Probability Distributions ◽  
Atmospheric Stability ◽  
Energy Dissipation Rate ◽  
Probability Of Detection ◽  
Percentage Error ◽  
Unmanned Aerial Systems ◽  
Low Level ◽  
Forecasting System ◽  
The One ◽  
Aerial Systems

AbstractA low-level turbulence (LLT) forecasting algorithm is proposed and implemented within the Graphical Turbulence Guidance (GTG) turbulence forecasting system. The LLT algorithm provides predictions of energy dissipation rate (EDR; turbulence dissipation to the one-third power), which is the standard turbulence metric used by the aviation community. The algorithm is based upon the use of distinct log-Weibull and lognormal probability distributions in a statistical remapping technique to represent accurately the behavior of turbulence in the atmospheric boundary layer for daytime and nighttime conditions, respectively, thus accounting for atmospheric stability. A 1-yr-long GTG LLT calibration was performed using the High-Resolution Rapid Refresh operational model, and optimum GTG ensembles of turbulence indices for clear-air and mountain-wave turbulence that minimize the mean absolute percentage error (MAPE) were determined. Evaluation of the proposed algorithm with in situ EDR data from the Boulder Atmospheric Observatory tower covering a range of altitudes up to 300 m above the surface demonstrates a reduction in the error by a factor of approximately 2.0 (MAPE = 55%) relative to the current operational GTG system (version 3). In addition, the probability of detection of typical small and large EDR values at low levels is increased by approximately 15%–20%. The improved LLT algorithm is expected to benefit several nonconventional turbulence-prediction sectors such as unmanned aerial systems and wind energy.

Field Application of UAS-Based Bridge Inspection

2018 ◽  
Vol 2672 (12) ◽  
pp. 72-81 ◽  
Author(s):  
Junwon Seo ◽  
Luis Duque ◽  
James P. Wacker
Keyword(s):  
South Dakota ◽  
Structural Damage ◽  
Image Data ◽  
Field Application ◽  
Unmanned Aerial Systems ◽  
Department Of Transportation ◽  
Bridge Inspection ◽  
Bridge Damage ◽  
Efficient Alternative ◽  
Aerial Systems

The use of Unmanned Aerial Systems (UASs), commonly known as drones, has significantly increased over recent years in the field of civil engineering. In detail, the need for a more efficient alternative for bridge inspection has risen because of the increased interest from bridge owners. The primary goal of this paper is to evaluate the efficiency of a drone as a supplemental bridge inspection tool. To complete this study, a glued laminated (glulam) girder with a composite concrete deck bridge was chosen in South Dakota, and a Dà-Jiāng Innovations (DJI) Phantom 4 drone, was employed to perform the bridge inspection. Based on the literature review, an inspection procedure with a drone was developed to efficiently identify damage on the bridge. A drone-enabled inspection was performed following the procedure, and resulting images were checked with those available in the past inspection report from South Dakota Department of Transportation (DOT). This study includes UAS-based bridge inspection considerations to capture appropriate image data necessary for bridge damage determination. A key finding demonstrated throughout this project is that different types of structural damage on the bridge were identified using the UAS.

scholarly journals Validating UAS-Based Photogrammetry with Traditional Topographic Methods for Surveying Dune Ecosystems in the Spanish Mediterranean Coast

2019 ◽  
Vol 7 (9) ◽  
pp. 297 ◽  
Author(s):  
Luis Bañón ◽  
José Ignacio Pagán ◽  
Isabel López ◽  
Carlos Banon ◽  
Luis Aragonés
Keyword(s):  
Low Cost ◽  
Temporal Frequency ◽  
Satellite System ◽  
Mean Value ◽  
Mediterranean Coast ◽  
Unmanned Aerial Systems ◽  
Aerial Photogrammetry ◽  
The One ◽  
Global Navigation Satellite ◽  
Aerial Systems

In the past few years, unmanned aerial systems (UAS) have achieved great popularity for civil uses. One of the present main uses of these devices is low-cost aerial photogrammetry, being especially useful in coastal environments. In this work, a high-resolution 3D model of a beach section in Guardamar del Segura (Spain) has been produced by employing a low maximum takeoff mass (MTOM) UAS, in combination with the use of structure-from-motion (SfM) techniques. An unprecedented extensive global navigation satellite system (GNSS) survey was simultaneously carried out to statistically validate the model by employing 1238 control points for that purpose. The results show good accuracy, obtaining a vertical root mean square error (RMSE) mean value of 0.121 m and a high point density, close to 30 pt/m2, with similar or even higher quality than most coastal surveys performed with classical techniques. UAS technology permits the acquisition of topographic data with low time-consuming surveys at a high temporal frequency. Coastal managers can implement this methodology into their workflow to study the evolution of complex, highly anthropized dune-beach systems such as the one presented in this study, obtaining more accurate surveys at lower costs.

scholarly journals Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations

2016 ◽  
Vol 10 (3) ◽  
pp. 1075-1088 ◽  
Author(s):  
Yves Bühler ◽  
Marc S. Adams ◽  
Ruedi Bösch ◽  
Andreas Stoffel
Keyword(s):  
Snow Depth ◽  
Laser Scanning ◽  
Depth Distribution ◽  
Cost Effective ◽  
Test Site ◽  
Measurement Technology ◽  
Unmanned Aerial Systems ◽  
Tall Grass ◽  
The One ◽  
Aerial Systems

Abstract. Detailed information on the spatiotemporal snow depth distribution is a crucial input for numerous applications in hydrology, climatology, ecology and avalanche research. Today, snow depth distribution is usually estimated by combining point measurements from weather stations or observers in the field with spatial interpolation algorithms. However, even a dense measurement network like the one in Switzerland, with more than one measurement station per 10 km2 on average, is not able to capture the large spatial variability of snow depth present in alpine terrain.Remote sensing methods, such as laser scanning or digital photogrammetry, have recently been successfully applied to map snow depth variability at local and regional scales. However, in most countries such data acquisition is costly if manned airplanes are involved. The effectiveness of ground-based measurements on the other hand is often hindered by occlusions, due to the complex terrain or acute viewing angles. In this paper, we investigate the application of unmanned aerial systems (UASs), in combination with structure-from-motion photogrammetry, to map snow depth distribution. Compared to manual measurements, such systems are relatively cost-effective and can be applied very flexibly to cover terrain not accessible from the ground. In this study, we map snow depth at two different locations: (a) a sheltered location at the bottom of the Flüela valley (1900 m a.s.l.) and (b) an exposed location on a peak (2500 m a.s.l.) in the ski resort Jakobshorn, both in the vicinity of Davos, Switzerland. At the first test site, we monitor the ablation on three different dates. We validate the photogrammetric snow depth maps using simultaneously acquired manual snow depth measurements. The resulting snow depth values have a root mean square error (RMSE) of less than 0.07 to 0.15 m on meadows and rocks and a RMSE of less than 0.30 m on sections covered by bushes or tall grass, compared to manual probe measurements. This new measurement technology opens the door for efficient, flexible, repeatable and cost-effective snow depth monitoring over areas of several hectares for various applications, if the national and regional regulations permit the application of UASs.

scholarly journals Aerial Imagery Based on Commercial Flights as Remote Sensing Platform

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1658 ◽  
Author(s):  
Toni Mastelic ◽  
Josip Lorincz ◽  
Ivan Ivandic ◽  
Matea Boban
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Aerial Photography ◽  
Storage Capacity ◽  
Image Data ◽  
Aerial Imagery ◽  
Unmanned Aerial Systems ◽  
Sensing Platform ◽  
Temporal And Spatial ◽  
Aerial Systems

Remote sensing is commonly performed via airborne platforms such as satellites, specialized aircraft, and unmanned aerial systems (UASs), which perform airborne photography using mounted cameras. However, they are limited by their coverage (UASs), irregular flyover frequency (aircraft), and/or low spatial resolution (satellites) due to their high altitude. In this paper, we examine the utilization of commercial flights as an airborne platform for remote sensing. Namely, we simulate a situation where all aircraft on commercial flights are equipped with a mounted camera used for airborne photography. The simulation is used to estimate coverage, the temporal and spatial resolution of aerial imagery acquired this way, as well as the storage capacity required for storing all imagery data. The results show that Europe is 83.28 percent covered with an average of one aerial photography every half an hour and a ground sampling distance of 0.96 meters per pixel. Capturing such imagery results in 20 million images or four petabytes of image data per day. More detailed results are given in the paper for separate countries/territories in Europe, individual commercial airlines and alliances, as well as three different cameras.

scholarly journals 3D Calibration Test-Field for Digital Cameras Mounted on Unmanned Aerial Systems (UAS)

2018 ◽  
Vol 10 (12) ◽  
pp. 2017 ◽  
Author(s):  
Valeria-Ersilia Oniga ◽  
Norbert Pfeifer ◽  
Ana-Maria Loghin
Keyword(s):  
Near Infrared ◽  
Low Cost ◽  
Digital Camera ◽  
Field Measurements ◽  
Unmanned Aerial Systems ◽  
Test Field ◽  
Digital Cameras ◽  
Self Calibration ◽  
Technological Developments ◽  
Aerial Systems

Due to the large number of technological developments in recent years, UAS systems are now used for monitoring purposes and in projects with high precision demand, such as 3D model-based creation of dams, reservoirs, historical monuments etc. These unmanned systems are usually equipped with an automatic pilot device and a digital camera (photo/video, multispectral, Near Infrared etc.), of which the lens has distortions; but this can be determined in a calibration process. Currently, a method of “self-calibration” is used for the calibration of the digital cameras mounted on UASs, but, by using the method of calibration based on a 3D calibration object, the accuracy is improved in comparison with other methods. Thus, this paper has the objective of establishing a 3D calibration field for the digital cameras mounted on UASs in terms of accuracy and robustness, being the largest reported publication to date. In order to test the proposed calibration field, a digital camera mounted on a low-cost UAS was calibrated at three different heights: 23 m, 28 m, and 35 m, using two configurations for image acquisition. Then, a comparison was made between the residuals obtained for a number of 100 Check Points (CPs) using self-calibration and test-field calibration, while the number of Ground Control Points (GCPs) variedand the heights were interchanged. Additionally, the parameters where tested on an oblique flight done 2 years before calibration, in manual mode at a medium altitude of 28 m height. For all tests done in the case of the double grid nadiral flight, the parameters calculated with the proposed 3D field improved the results by more than 50% when using the optimum and a large number of GCPs, and in all analyzed cases with 75% to 95% when using a minimum of 3 GCP. In this context, it is necessary to conduct accurate calibration in order to increase the accuracy of the UAS projects, and also to reduce field measurements.

scholarly journals Pervasive Intelligence

2018 ◽  
Vol 4 (1) ◽  
pp. 107-132
Author(s):  
Sebastian Vehlken
Keyword(s):  
Swarm Robotics ◽  
Self Organization ◽  
Unmanned Aerial Systems ◽  
Spatial Intelligence ◽  
Changing Environments ◽  
Robot Swarms ◽  
Peculiar Form ◽  
The One ◽  
And Control ◽  
Aerial Systems

Abstract This article seeks to situate collective or swarm robotics (SR) on a conceptual pane which on the one hand sheds light on the peculiar form of AI which is at play in such systems, whilst on the other hand it considers possible consequences of a widespread use of SR with a focus on swarms of Unmanned Aerial Systems (Swarm UAS). The leading hypothesis of this article is that Swarm Robotics create a multifold “spatial intelligence”, ranging from the dynamic morphologies of such collectives via their robust self-organization in changing environments to representations of these environments as distributed 4D-sensor systems. As is shown on the basis of some generative examples from the field of UAS, robot swarms are imagined to literally penetrate space and control it. In contrast to classical forms of surveillance or even “sousveillance”, this procedure could be called perveillance.

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