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GI1.2

Autonomous Uncrewed Aircraft Systems (UAS): Geoscience Research Platforms for the 21st century

Autonomous and unmanned systems are changing the way that we collect and process geoscience data. Their capabilities and potential applications will only continue to grow. Automated systems are now used for routine data collection in high risk environments, emergency response activities, and precision agriculture for species composition monitoring and evaluating vegetation health. The aim of this session is to bring together geoscience researchers to present on the newest systems, payloads, and research goals. We invite contributions from those integrating these autonomous systems into their scientific research, system and sensor development teams, as well as those operators working on the integration of unmanned aircraft systems into manned airspace. The session brings together experts in all aspects of autonomous and unmanned system mission planning, regulations, operations, data collection, processing, and analysis to foster interdisciplinary research and knowledge-transfer across the sciences.

Convener: Misha Krassovski | Co-convener: Juri Klusak
Presentations
| Mon, 23 May, 08:30–09:33 (CEST)
 
Room 0.51

Mon, 23 May, 08:30–10:00

08:30–08:37
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EGU22-281
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ECS
Hédi Katreiner et al.

After a nuclear accident in the Fukushima Dai-ichi reactor in 2011, huge amounts of radioactive material were released into the air. The contaminated area was first surveyed by a fleet of 15 vehicles equipped with GM tubes, followed by traditional airborne measurements. These methods were extremely time-consuming, expensive and enhanced the risk for human lives. After the disaster, a drone with a radiation sensor was sent to survey radiation levels using similar technology. This method speeded up the evaluation and did not risk human lives, but the measuring device was heavy and expensive. Since then, many research have been investigating how to perform a radiation survey task with less weight, more cheaply and yet effectively at different distance scales.

The aim of our research is to find out the optimized parameters to detect large radiation anomalies by a low-cost radiation sensor mounted on a drone. What are the best altitude, drone speed, integration time, for the most reliable description of the anomaly. What is the altitude dependence of the gamma dose at certain circumstances and how can we extend the measured radiation level values in 3 dimension?

A survey was carried out in the area of Kővágószőlős, not far from the city of Pécs (Hungary), where a uranium mine had been operating until 1997. The remediation has been succesfully completed, but according to the geological conditions of Kővágószőlős, anomalous radiation can be measured at few locations (U ore outcrops). The survey used a DJI Matrice 210 V2 RTK drone and a Japanese radiation measuring device, the Safecast bGeige Nano Kit. The Safecast bGeige Nano Kit uses a Geiger-Müller counter, sunk to a depth of 1 cm to measure gamma radiation. It averages the number of impulses every 5 seconds and then calculates a 60s average from that (CPM). The device also includes a GPS unit, adds a time-stamp to the GPS data and writes it to an SD card. All of these are covered by a thick, waterproof polycarbonate housing, allowing only gamma radiation to enter the GM tube.

During the survey, this instrument was mounted on the drone and then flown at different altitudes; 5, 15 and 25 meters above the ground in uncovered terrain. The survey also included an elevation profile measurement of an anomaly, moving upwards every 10 metres up to 120 metres.

This low-cost device has been able to detect effectively larger anomalies. It can also be said that in an uncovered area, the device provides almost equal values up to a height of about 15 metres from the ground; above this altitude its reliability decreases.

BK is supported by the NRDI Fund of Hungary, Thematic Excellence Programme no. TKP2020-NKA-06 (National Challenges Subprogramme) funding scheme. FV is supported by EFOP-3.6.3-VEKOP-16-2017-00001: Talent Management in Autonomous Vehicle Control Technologies – The Project is financed by the Hungarian Government and co-financed by the European Social Fund. The bGeigie device is supported by Gábor Garamhegyi and the Gábor Dénes School.

How to cite: Katreiner, H., Horváth, Á., Vörös, F., Pál, M., Tóth, S., Várhegyi, A., and Kovács, B.: Gamma dose rate detection and mapping using a drone-mounted Safecast sensor, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-281, https://doi.org/10.5194/egusphere-egu22-281, 2022.

08:37–08:44
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EGU22-1375
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ECS
Szymon Śledź and Marek Ewertowski

The Structure-from-Motion (SfM) approach for developing digital elevation models and orthomosaics has been known and used in photogrammetry for several decades. Using appropriate algorithms, SfM software combines images taken from different angles and distances based on the characteristic points determined in each image. Years of practice and experience have allowed researchers to provide a solid description of the applicability and limitations of this method, but still the impact of input processing parameters in software on the quality of photogrammetric products has not been fully recognized. This study aimed to identify the most advantageous processing workflow to fill this research gap by testing 375 different setup variations in the Agisoft Metashape software for the same set of images acquired with an unmanned aerial vehicle in a proglacial area. The purpose of the experiment was to determine three workflows: 1) with the shortest calculations time; 2) as accurate as possible, regardless of the time taken for the calculations; 3) the optimum, which is a compromise between accuracy and computation time.

Each of the 375 processing setup variations was assessed based on final product accuracy, i.e., orthomosaics and digital elevation models. Three workflows were selected based on calculating the height differences between the digital elevation models and the control points that did not participate in their georeferencing. The analysis of root mean square errors (RMSE) and standard deviations indicate that excluding some of the optimization parameters during the camera optimization stage results in high RMSE and an increase in values of errors’ standard deviation. Furthermore, it has been shown that increasing the detail of individual processing steps in software does not always positively affect the accuracy of the resulting models. The experiment resulted in the development of three different workflows in the form of Python scripts for Agisoft Metashape software, which will help users to process image sets efficiently in the context of earth surface dynamics studies.

The research was funded by the National Science Center OPUS project number 2019/35/B/ST10/03928.

How to cite: Śledź, S. and Ewertowski, M.: Evaluation of the influence of Structure-from-Motion software processing parameters on the quality of digital elevation models and orthomosaics in the context of earth surface dynamics., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1375, https://doi.org/10.5194/egusphere-egu22-1375, 2022.

08:44–08:51
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EGU22-1610
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ECS
Haiyu Wang et al.

In order to explore the influence of slope shape on the development of ephemeral gully, 225 ephemeral gullies were obtained by visual interpretation based on the unmanned aerial photography of Langerzigou in Jingbian County, Shaanxi Province. The number and length of ephemeral gullies, the distance from the gully head to the watershed and the gully density were calculated. The original slope DEM was obtained by interpolating the elevation points on the ephemeral gully watershed, and the DEM was used to extract the terrain curvature to describe the hillslope shape, and then analyze the relationship between the slope shape and the ephemeral gully index. The results showed that: (1) the DEM after the elevation point interpolation on the ephemeral gully watershed was used to synthesize the ephemeral gully, which can well describe the original slope topographic features before the development of the ephemeral gully. (2) From the point of view of single slope shape, the gully density of the transverse concave slope was the highest, and the number of ephemeral gullies, the average distance from the gully head to the watershed of the longitudinal concave slope were the largest. the average length of the ephemeral gully and the number of the longitudinal convex slope were the largest. From the point of view of the combined slope shape, the average length of the ephemeral gully and the average distance from the gully head to the watershed on the biconvex slope and the convex slope were larger than those on the biconvex slope and the concave-convex slope. The ephemeral gully length of double concave slope was significantly different from that of double convex slope and convex concave slope (P<0.05); The ephemeral gully length of concave convex slope was significantly different from that of double convex slope and convex concave slope (P<0.05); There was a significant difference in the distance from the trench head to the watershed between the concave convex slope and the concave convex slope (P<0.1). (3) The curvature distribution characteristics of different forms of slope shallow ditch development were analyzed.

How to cite: Wang, H., Pang, G., Wang, C., Wang, L., and Long, Y.: Study on the Influence of Slope Shape on the Development of Ephemeral Gully Based on UAV, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1610, https://doi.org/10.5194/egusphere-egu22-1610, 2022.

08:51–08:58
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EGU22-5278
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ECS
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Highlight
Yunsong Liu et al.

Unmanned Aerial Vehicles (UAVs) have provided a cost-effective way to fill in gaps between in-situ (ground-based) and remote-sensing observations. In this study, a lightweight CO2 sensor system suitable for operations on board small UAVs has been developed and validated. The CO2 system autonomously performs in situ measurements, allowing for its integration into various platforms. It is based on a low-cost commercial nondispersive near-infrared (NDIR) CO2 sensor (Senseair AB, Sweden), with a total weight of 1058 g, including batteries. A series of accuracy and linearity tests showed that the precision is within ±1 ppm for 1σ at 1 Hz. Variability due to temperature and pressure changes was derived from environmental chamber experiments. Additionally, the system has been validated onboard a manned aircraft against a reference instrument (Picarro, USA), revealing an accuracy of ±2 ppm (1σ) at 1 Hz and ±1 ppm (1σ) at 1 min (0.02 Hz). Integration on a quad-copter led to improvements in the calibration strategy for practical applications. The developed system has been deployed in an intensive flight campaign (a total of 16 flights per day), with horizontal flights performed at a low altitude (100 m AGL). The designed system highlights the capacity to detect CO2 concentration changes at 1 Hz and spatial gradients and to provide accurate plume dispersion maps. It proved to be a good complementary measurement tool to the ground-based co-located observations performed by the Picarro G2401. This study gives a practical example of the process to be followed for the integration of a lightweight atmospheric sensor into a mobile (UAV) platform. Details of the measurement system and field implementations are described in this study to support future UAV platform applications for atmospheric trace gas measurements and closing the gaps in the monitoring of the current carbon cycle.

How to cite: Liu, Y., Paris, J.-D., Vrekoussis, M., Antoniou, P., Constantinides, C., Desservettaz, M., Keleshis, C., Laurent, O., Leonidou, A., Philippon, C., Vouterakos, P., Quéhé, P.-Y., Bousquet, P., and Sciare, J.: Improvements of a low-cost CO2 commercial NDIR sensor for UAV atmospheric mapping applications, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5278, https://doi.org/10.5194/egusphere-egu22-5278, 2022.

08:58–09:05
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EGU22-5354
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ECS
Niklas Karbach et al.

Investigating the chemical composition of volcanic plumes is an important method for obtaining geochemical information of volcanic systems, determining the environmental impact of volcanic outgassing and providing indications of impending activity of the volcano under investigation. However, sampling is not easy, particularly because of immediate meteorological influences on volcanic plume dispersion, but also, of course, because of potential hazards associated with sampling immediately at the rim of volcanic craters. 

When remote sensing methods are not available, UAVs offer the possibility of bringing measurement systems to the scene. Standard parameters that are commonly measured are SO2 and CO2, as well as a number of atmospheric state parameters such as pressure, temperature, and relative humidity. In flight data transmission via radio telemetry plays a significant role, as of course both orography and current meteorology make it otherwise difficult to locate the volcanic plume from several kilometers away. In addition to key components such as SO2, CO2, and water, there are also a number of other components of interest to geoscientists, such as H2S, CO, H2, and halogen compounds. Larger drones, such as the DJI Matrice M210 or the DJI M300, can be used to fly those research based measurement systems in parallel. This allows for the chemical characterization of highly transient plume structures simultaneously at two locations or at large distances from the source including the free troposphere. Results of such measurements carried out at Mt Etna and Vulcano Island, Italy during the last two years are presented in this contribution. Larger drone systems (with the DJI Matrice M210, DJI M300) have the disadvantage that they have a comparatively high weight and therefore make it difficult to bring to the sampling site which might not be accessible by car. Smaller drones like the DJI Mavic 3 significantly reduce the weight one has to carry. In addition, the relatively high cost of the larger drone systems prevents their use for daily monitoring tasks. Therefore, we have equipped a comparatively small drone (DJI Mavic 3) with suitable radio telemetry and sensors to gather basic chemical information in volcanic plumes with an extra-lightweight system. We will introduce this new miniaturized instrumentation and present first results of measurements with the new setup.

How to cite: Karbach, N., Geil, B., Gutiérrez, X., Hoor, P., Dötterl, A., Bobrowski, N., and Hoffmann, T.: Chemical characterization of volcanic plumes with multifunction UAVs and extra-lightweight drones: Concepts and first applications, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5354, https://doi.org/10.5194/egusphere-egu22-5354, 2022.

09:05–09:12
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EGU22-5661
Elio Romano et al.

Accurate estimates of canopy cover (CC),tree and stand structure are required to manage poplar plantations effectively. However, traditional measurements are limited by the cost and time-consuming nature of field methods, which inherently have limited the large scale adoption of in situ approaches. Satellite remote sensing has the advantage of broader geographical coverage, but its spatial and temporal resolution is often not suited for tree- to stand-scale applications as required in precision plantation forestry. Recently, unmanned aerial vehicles (UAVs) have become very popular in forestry. In this contribution, we tested the use of UAVs for retrieving plot-level canopy and stand attributes in hybrid poplar plantations, which were sampled in Northern Italy. A multispectral camera sensor was equipped to a multi-rotor UAV, and was used to acquire orthorectified images of 50 poplar plantations, each 0.25 ha in size, with varying age and plant density. In addition, field optical measurements of canopy structure made by digital cover photography and mensurational attributes derived from tree inventory were also performed and used as ground truth data.

The very high resolution of UAV imagery (<10 cm) allowed to efficiently perform a Simple Linear Iterative Clustering (SLIC) algorithm for superpixels generation, which was used to delineate individual poplar crowns automatically. The segmented images were then processed using Gray-Level Co-occurrence Matrices (GLCM) to calculate specific texture attributes, which were benchmarked against ground truth measurements.

Results indicated that multispectral UAVs can estimate canopy and stand structure attributes in poplar plantations reliably and accurately. Based on model performance indicators, the best model is that relating stand features to image dissimilarity. Its RMSE is in line with the standard deviations of the observed values, meaning that the error associated with the prediction is in line with the uncertainty of the calibration dataset.

The basal area, the volume of the trunk and the crown volume were the most correlated attributes with image dissimilarity valued from GLCM.By contrast, crown cover (CC) and leaf area index (LAI) were the model's attributes that could fit the worse following the clustering effect of plants’ age and the leverage occurring in some stands that results in ground truth data overestimation.

We concluded that use of UAVs can be considered an efficient tool in poplar plantation forestry. Considering the multi-scale nature of poplar plantation interventions, UAVs are particularly relevant as they can bridge between field and satellite measurements. Regarding the latter, the high resolution of UAV imagery also allows calibrating metrics from coarser scale satellite products, avoiding or reducing the need for field calibration efforts.

How to cite: Romano, E., Brambilla, M., Bisaglia, C., Giannetti, F., Tattoni, C., Puletti, N., and Chianucci, F.: Estimating canopy and stand structure in hybrid poplar plantations from multispectral UAV imagery, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5661, https://doi.org/10.5194/egusphere-egu22-5661, 2022.

09:12–09:19
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EGU22-10511
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Highlight
Abraham Mejia-Aguilar et al.

Mountain agriculture is a vital social-economic activity in Europe, including the alpine Province of South Tyrol, Italy. Here, apple orchards and vineyards are extensively cultivated. Besides the difficulty to cultivate in mountain terrain (steep slopes, difficult accessibility, extreme weather conditions), the plants are exposed to a combination of biotic and abiotic stresses that can result in diseases caused by pathogens. It results in the loss of the yield and quality of products, economic losses, reducing food security with severe ecological impacts, and affects many ecosystem services (such as agrotourism).

This work presents a proximal sensing technique based on an unmanned aerial platform with a payload consisting of multi and hyperspectral optical cameras. Such platforms are suitable to access rugged terrains in a short time to map the presence of diseases and pests, as well they provide imagery for the optimal management of farms. We study three different experiments: apple orchard, vineyard, and forestry, observing Apple proliferation, Flavescence dorée, and Pine processionary, respectively. We aim at a non-invasive and non-destructive method to monitor plant diseases in the direction of high-precision mapping agriculture applications by exploring supervised classification methods based on ground data to distinguish healthy and unhealthy trees.

How to cite: Mejia-Aguilar, A., Barthel, D., Chuprikova, E., McLeod, B. A., Trenti, M., Kerschbamer, C., Prechsl, U., and Janik, K.: UAV-based precision mapping techniques for disease and pest identification, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10511, https://doi.org/10.5194/egusphere-egu22-10511, 2022.

09:19–09:26
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EGU22-11912
Luca Cicala et al.

In some environmental applications, satellite acquisitions could not be able to provide all the information necessary to characterize the problem at hand due, for example, to limited spatial resolution or inadequate revisit time. However, in these cases, they can be used for preliminary investigation of the area of interest with the purpose to guide subsequent acquisitions with higher spatial resolution made by means of aerial sensing. This work presents an innovative application combining both satellite acquisitions and aerial close-range sensing implemented via drones in autonomous and coordinated flight. The case study concerns the discovery of illegal micro-dumps and other environmental hazards in Campania Region (Italy). The envisioned workflow includes the detection of target environmental criticalities in very high-resolution optical satellite images and a methodology to plan and adaptively re-plan a survey mission of a team of drones aimed at confirming the presence of a micro-dump and at its characterization. The processing of satellite images is validated on real data in a significative application context, while the performance of the acquisition strategy performed by the drone team are characterized trough simulations on a pre-analysed geographical area.

How to cite: Cicala, L., Amitrano, D., Cesario Vincenzo, A., Gargiulo, F., Gigante, G., Nebula, F., Palumbo, R., Parrilli, S., Pascarella, D., and Tufano, F.: Discovery and characterization of environmental hazards by means of dynamic coordination of drones driven by satellite detection maps, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11912, https://doi.org/10.5194/egusphere-egu22-11912, 2022.

09:26–09:33
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EGU22-12130
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ECS
Tim Dunker et al.

We present a platform for open-path tunable diode laser absorption spectroscopy between a drone and a base station. This is a step towards an open-path measurement between two collaborating drones, which to our knowledge has not yet been achieved. Such a system enables mapping of remote (permafrost tundra, e.g.) or hazardous areas (landfills, e.g.) and localization of emissions. We use a commercially available quad-copter drone that carries a reflector and a LED for being tracked. The base station consists of a self-made pan-tilt unit that carries a camera to track the drone, and the optical measurement system. The base station is controlled through a field--programmable gate array. We decided to built the base station ourselves to ensure a fast response, enabling tracking of the drone. To demonstrate the concept, our tunable diode laser absorption setup is tailored towards the detection of ammonia (NH3) because of its fairly strong absorption, and thus comparatively easy detectability. The distributed feedback laser operates at a centre wavelength of 1512 nm, with a bandwidth of approximately 2 nm (full width at half maximum), and a typical output power of 10 mW. We characterize the stability of the drone, the reflector, and the laser system. We aim to further develop this concept such that it (a) can be implemented on two collaborating drones, without the need for a base station, and (b) to measure other greenhouse gases or pollutants, such as methane or hydrogen sulphide.

How to cite: Dunker, T., Berge, A., Haugholt, K. H., Moore, R. J. D., and Tørring, H.: Concept for open-path gas measurements between a drone and a base station, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12130, https://doi.org/10.5194/egusphere-egu22-12130, 2022.