Aerial UAV Research Articles

A multidisciplinary approach to study slope instability in the Alboran Sea shoreline: Study of the Tamegaret deep-seated slow-moving landslide in Northern Morocco

Coastal landslides cause great economic damage to human installations along the Mediterranean shoreline. In the Alboran Sea, this phenomenon is very common and causes many problems for residential resorts and road infrastructures in coastal areas. In the last two decades, such slope instability processes were the subject of many studies, which employed multidisciplinary approaches to understand their underlying mechanisms and surficial kinematics in Southern Spain and elsewhere in the Mediterranean. However, advanced and new investigation methods and techniques used in these studies have never been performed in Northern Morocco despite the geomorphological, geological and climatic resemblance between the two regions. In this paper we analyze the mechanisms and processes controlling the Tamegaret slow-moving deep-seated landslide (Northern Morocco) in order to bridge this knowledge gap and to understand landslide slope dynamics on their regional context. To do so, Electrical resistivity Tomography, field investigations and multi-temporal Synthetic Aperture Radar Interferometry (InSAR) were performed to characterize slope instability processes at the study area. The interpretation of Historic aerial photographs and UAV surveys was also conducted to study the major redistribution of mass caused by recent road widening work at the landslide headscarp. Results show that the Tamegaret landslide owes its existence to deep creep processes controlled by a rock flow type gravitational deformation. Extensional tectonic structures and marine erosion processes that eliminate landslide deposits from the foot area constitute the most relevant control factors of this dynamic. InSAR results show that this deep-seated landslide is currently (2017–2019) characterized by very slow displacement rates (2–3 cm/year maximum). Yet, the substantial deformation observed both in the field and on aerial/satellite photographs suggests that the acceleration occurred during the road-widening work which caused major changes to the natural topography in the period (2009–2012). This deformation phase was manifested by local shoreline advancement at the landslide foot area. Such results show that studying historic shoreline variations can be an effective low-cost time-saving tool allowing the reconstruction of active landslide kinematics in coastal areas. On a regional scale, findings of this study highlight the resemblance between the coasts of Southern Spain and Northern Morocco in terms of (i) the geomorphological processes controlling the coastal slope dynamics at the region; (ii) the displacement rates measured in Tamegaret compared to other unstable slopes in the Northern shore of the Alboran Sea and (iii) the bad-engineering on old dormant landslides which compromises their stability. Therefore, we suggest limiting construction work on coastal hillslopes of Northern Morocco in order to prevent bad construction practices from causing economic losses in the Southern shoreline of the Alboran Sea as well.

Application of UAV Aerial Photogrammetry Technology in Topographic Mapping

Application of UAV Aerial Photogrammetry Technology in Topographic Mapping

Application Analysis of UAV Aerial Survey Technology in Transmission Line Survey and Design

Application Analysis of UAV Aerial Survey Technology in Transmission Line Survey and Design

Application of UAV in Rip Current Investigations

Cases of people dying from being swept away on the beach have been widely published on Bali news; this is because not many people know the dangers of rip currents on the beach. Lack of public knowledge about rip currents is caused by a lack of socialization and warning signs of rip currents on the beach. Rip currents are back currents formed by currents coming perpendicular to the shoreline and meeting the curved shoreline. This current can drag someone who is swimming out to sea. In this study, the existence of rip currents was investigated using aerial photographs or UAVs. The observation location was taken in an area that is often used by the Balinese Hindu community to carry out the Ngaben ceremony process. The UAV device was prepared to observe the rip current and measure its speed. Dye Tracer Test was also conducted to observe the movement of rip currents visually. Rip currents are characterized by calmness between rows of breaking waves. The average rip current speed is 0,29 m/s can also be determined by observing the UAV. The speed of this current is influenced by wave energy that propagates to the beach. The difference in bathymetry causes variations in wave height along the beach, and the rip current causes this. The results of this study can be used as an early warning system for people who carry out activities on the beach.

Implementation of SExI–FS (Spatially Explicit Individual-based Forest Simulator) Model using UAV Aerial Photo Data Case Study: Jatinangor ITB Campus

Landscape architecture affected by interaction between built and natural environment such as vegetation. Nowadays, landscape architects are using 3D city models for simulations, which requires highly dynamic and time-varying attributes. 3D city modelling structure has been standardized by CityGML, although researches that are related to the storing of dynamic data had been conducted for the past years, it has not been supported by any standard until this very moment. In dynamizer, it is added as a data structure into a CityGML structure that is already existed, although the existing structure is a static one. Kolbe’s research on dynamic data using CityGML called dynamizer could use the spatial data in more dynamic way by changing its geometric, thematic, or appearance data, but its purpose is not specific for trees or vegetation. In this paper, a method of simulating the vegetation growth using SeXI-FS will be discussed to show the dynamic changes that happen in vegetation as part of the dynamic changes in landscape architecture. The result of this research will be used to address the importance of information on vegetation by studying its changes in Jatinangor ITB Campus and as initial research to build dynamizer in CityGML for landscape architecture.

Next-Generation Digital Ecosystem for Climate Data Mining and Knowledge Discovery: A Review of Digital Data Collection Technologies.

Climate change has been called “the defining challenge of our age” and yet the global community lacks adequate information to understand whether actions to address it are succeeding or failing to mitigate it. The emergence of technologies such as earth observation (EO) and Internet-of-Things (IoT) promises to provide new advances in data collection for monitoring climate change mitigation, particularly where traditional means of data exploration and analysis, such as government-led statistical census efforts, are costly and time consuming. In this review article, we examine the extent to which digital data technologies, such as EO (e.g., remote sensing satellites, unmanned aerial vehicles or UAVs, generally from space) and IoT (e.g., smart meters, sensors, and actuators, generally from the ground) can address existing gaps that impede efforts to evaluate progress toward global climate change mitigation. We argue that there is underexplored potential for EO and IoT to advance large-scale data generation that can be translated to improve climate change data collection. Finally, we discuss how a system employing digital data collection technologies could leverage advances in distributed ledger technologies to address concerns of transparency, privacy, and data governance.

Future directions in drone routing research

AbstractOptimization of routing problems using drones (unmanned aerial vehicles or UAVs) has become an important area of academic research. The purpose of this article is to look to the future and help stimulate drone routing research in directions we hope will prove interesting and fruitful. We discuss opportunities for better modeling of (1) drone capabilities for both existing drones and those likely to be used in the future, (2) constraints on drone performance and operations, (3) different objectives for various drone services, and (4) alternative delivery modes, as well as some areas for methodological advances and some possible new applications. While much of the research to date has leveraged existing TSP (traveling salesman problem), VRP (vehicle routing problem), and arc routing models, we look forward to new contributions from drone research that use better models of more realistic drone types and new drone applications.

An accuracy analysis of mangrove tree height mensuration using forestry techniques, hypsometers and UAVs

Tree height is a fundamental measurement in forest inventory studies and a critical variable for the assessment of tree biomass, carbon stock and site productivity. However, measuring tree height is often a challenging task and may generate errors. This study provides an accuracy analysis of tree heights measured through different methods ranging from traditional techniques (thumb rule and stick method) to trigonometric equipment (clinometer, laser rangefinder, altimeter), and advanced technologies (Unmanned Aerial Vehicle or UAV and distometer). Along with scientific insights for the in situ application of these methods, the factors generating errors in tree height mensuration and its impact on forest biomass estimation were determined. Our results showed that the amount of error varies from one method to another. The amount of error was highest with the thumb rule and stick method (15%) while the range of error was similar for the clinometer (7.7%), laser rangefinder (7.1%) and altimeter (7.5%). Parameters such as tree form, the status of tree (i.e., if a tree was either isolated or within a canopy) and height of tree were found to significantly affect error generation during tree height measurements. Information on the extent to which biomass estimation is influenced by tree height errors associated with the use of different methods and instruments and the direction of error impact (overestimation or underestimation of biomass) are discussed. Finally, we recommend that the choice of method for tree heights in field inventory depends on certain factors such as cost, available time and manpower, required skills, site of observation and amount of error generated by each of the methods.

Accuracy Comparison of Aerial Lidar, Mobile-Terrestrial Lidar, and UAV Photogrammetric Capture Data Elevations over Different Terrain Types

Lidar and other remotely sensed data such as UAV photogrammetric data capture are being collected and utilized for roadway design on an increasing basis. These methods are desirable over conventional survey due to their efficiency and cost-effectiveness over large areas. A high degree of relative accuracy is achievable through the establishment of survey control. In this case study, elevations (z-values) derived from mobile-terrestrial lidar, aerial lidar, and UAV photogrammetric capture collected with survey control were statistically compared to conventionally surveyed elevations. A cost comparison of the methods is also included. Each set of z-values corresponds to a discrete horizontal point originally part of the conventional survey, collected as cross-sections. These cross-sections were surveyed at three approximate tenth-mile sample locations along US-30 near Georgetown, Idaho. The cross-sections were collected as elevational accuracy verification, and each sample location was selected as an area where the mobile-terrestrial lidar in particular was expected to have more difficulty achieving accuracy off the road surface. Processing and analysis were performed in Esri ArcMap 10.6, and all data were obtained from the Idaho Transportation Department, District 5. Overall, the aerial lidar elevations were found to be closest to conventionally surveyed elevations; on road surface and level terrain, mobile-terrestrial and UAV photogrammetric capture elevations were closer to the conventionally measured elevations.

Dynamics of mid-channel bars in the Middle Vistula River in response to ferry crossing abutment construction

Abstract The investigation focused on the non-migrating mid-channel bars that emerged in the river channel as a consequence of river engineering. A reach of around 280 km of Middle Vistula River (Poland) was taken into account as the study site. The most vivid examples of the river engineering works potentially influencing the river channel are the ferry crossings. Along the Middle Vistula River reach, there are 17 ferry crossings that were constructed from 1970s to 1990s. A cartographic analysis was carried out to determine the influence of the ferry crossing construction over the river channel. It was performed on the basis of aerial photographs (traditional aerial photography and UAV photography). In 3 out of 17 potential localizations, the emergence of large non-migrating mid-channel bars was observed. A study of cartographic materials (from 1950s to 2000s) allowed determination of the dynamics of those bars, including time of emergence and the changes of their size.

Coastal Dune Morphology Evolution Combining Lidar and UAV Surveys, Truc Vert beach 2011-2019

Laporte-Fauret, Q.; Castelle, B.; Marieu, V.; Bujan, S.; Michalet, R., and Rosebery. D., 2020. Coastal dune morphology evolution combining Lidar and UAV surveys, Truc Vert beach 2011-2019. In: Malvarez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 163–167. Coconut Creek (Florida), ISSN 0749-0208.In the context of climate change, coastal dunes, which provide significant ecosystem services, are one of the most vulnerable coastal environments. Moreover, the lack of high resolution and large spatial scale data limits our understanding of coastal dunes, which are subject to important morphological variations over a wide range of spatial and temporal scales. This study is focused on combining non-intrusive remote sensing methods including a series of historical aerial photographs, airborne Lidar and UAV surveys in order to better understand the coastal dune morphodynamic on a wide range of spatial and temporal scales. On the time scale of decades, aerial photos indicate a reasonably stable coastal dune position, with large anthropogenic reprofiling and vegetation planting resulting in a reasonably alongshore-uniform morphology. On shorter time scales, the combination of Lidar and UAV 4-km surveys between 2011 and 2019 shows a quasi-steady dune volume increase by approximately 64 m3/m, associated with a foredune crest growth and a landward migration reaching 1.1 m and 0.54 m in average, respectively. On the other hand, the dune foot shows a more complex dynamics, dominated by a large landward migration (shoreline erosion) of approximately 20 m during the outstanding winter of 2013/2014 followed by a slow seaward migration (recovery). This study provides new insight into coastal dune morphological changes driven by both Aeolian and marine processes from the time scale of storm to approximately a decade, highlighting the relevance of UAV surveys for such applications.

Assessment and Use of Unmanned Aerial Vehicle for Civil Structural Health Monitoring

Abstract Unmanned Aerial Vehicles or UAVs can be employed in a multitude of civil applications owing to their ease of use, low maintenance, affordability, high-mobility, and ability to hover. Such vehicles are being utilized for real-time monitoring of road traffic, providing wireless coverage, remote sensing, search and rescue operations, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. They are the next big revolution in technology and civil infrastructure is expected to dominate their more than $45 Billion worth market. This paper surveys the UAV assisted Structural Health Monitoring or SHM literature over the last decade and categorizes UAVs based on their aerodynamics. Further, it presents the payload product line to facilitate the SHM tasks, details the different applications of UAVs exploited in the last decade to support civil structures and discusses the key challenges faced in its application across various domains.

Area Scanning with Reinforcement Learning and MCTS in Smart City Applications

This research project is focused on area scanning in the scope of smart city applications with unmanned aerial vehicles or UAVs. More powerful devices have been designed in terms of range, capacity and sensory capabilities in the recent years. This makes possible easier automation, thus suppressing the need for human resources. Some of the fields of applications include: traffic or pollution monitoring, land surveying, civil security control or natural disaster control and monitoring. With the increased number of UAV applications, the use and development of efficient algorithms is more and more essential. This paper investigates the possibility of using Monte-Carlo Tree Search (MCTS) and Reinforcement Learning (RL) in this area, which are already successful methods in other control tasks.

Research on Balance Device of UAV Aerial Photography Sur- veying and Mapping Instrument

This paper taking the UAV aerial photography mapper balance device as the research object, mainly research and design spiral balance device different from the more common one on the market. Setting a base and a sphere on the bottom of the UAV, when the aircraft is unstable in flight, the balancing device is coordinated with each other under gravity, so that the aerial mapper can maintain a stable position. The device allows the UAV to maintain torque balance in any harsh environment, thus ensuring photographic quality.

基于Cascade R-CNN的并行特征金字塔网络无人机航拍图像目标检测算法

基于Cascade R-CNN的并行特征金字塔网络无人机航拍图像目标检测算法

Geometric Accuracy Assessments of Orthophoto Production from UAV Aerial Images

Orthophoto mosaic is assembled from aerial perspective images through a process called orthorectification, which eliminate photographic tilts and terrain relief effects. These orthorectified images have been resampled from the original ones that may have been prepared from a DTM which does not accurately model the surface. Meanwhile, some proprietary software such as Agisoft utilizes spatially dense 3D point clouds that are generated from a so called Structure from Motion technique to generate the orthophoto. The software provides a black-box method to regard these clouds as DSM, and it utilizes this surface model to project pixels from the original images. This paper investigates geometric accuracy of the produced orthophoto mosaic according to the American Society of Photogrammetry and Remote Sensing (ASPRS) standards. To minimize scale differences among images, a 35mm fixed-lens camera is mounted on a fixed-wing UAV platform. Flight missions are carried out at around 250m flying height controlled by a navigational grade sensor on board to provide spatial resolution of about 27mm. A number of orthophoto mosaics are produced by varying numbers of GCPs, flight paths configuration and terrain relief differences. The geometric accuracies are assessed through a provision of ICPs on each test field area. Coordinates deviations between the ICP and the corresponding orthophotos are framed into a RMSE figures. Within a 95% confidence level, it is revealed that a suitable orthophoto map scale is up to around 1:500. It is recommended that a cross flight configuration to achieve better results.

Forests Growth Monitoring Based on Tree Canopy 3D Reconstruction Using UAV Aerial Photogrammetry

Land cover monitoring is a major task for remote sensing. Comparing to traditional methods for forests monitoring which mostly use orthoimages from satellite or aircraft, there are very few researches use forest 3D canopy structure to monitor the forest growth. UAV aerial can be a novel and feasible platform to provide high resolution and more timely images that can be used to generate high resolution forest 3D canopy. In spring, the small forest is supposed to experience rapid growth. In this research, we used a small UAV to monitor campus forest growth in spring at 2days interval. Each time 140 images were acquired and the ground surface dense point cloud was reconstructed at high precision. Color indexes ExG (Excess Green) was used to extract the green canopy point. The segmented point cloud was triangulated using greedy projection triangulation method into a mesh and its area was calculated. Forest canopy growth was analyzed at 3 level: forest level, selected group level and individual tree level. Logistic curve was used to fit the time series canopy growth. Strong correlation was found R2 = 0.8517 at forest level, R2=0.9652 at selected group level and R2 = 0.9606 at individual tree level. Moreover, high correlation was found between canopy by observing these results, we can conclude that the ground 3D model can act as a useful data type as orthography to monitor the forest growth. Moreover the UAV aerial remote sensing has advantages at monitoring forest in periods when the ground vegetation is growing and changing fast.

Static and Dynamic Algorithms for Terrain Classification in UAV Aerial Imagery

Static and Dynamic Algorithms for Terrain Classification in UAV Aerial Imagery

Fast Aerial UAV Detection Using Improved Inter-frame Difference and SVM

In order to detect UAV in real time, the paper choose to use a dynamic detection method based on two consecutive inter-frame differences method to extract the region of interest. The position of the target appeared on the image was obtained by the method of two consecutive inter-frame difference, and the UAV was detected by the trained SVM classifier. UAV could be detected quickly and accurately in complex background and in different position and angle circumstances. Compared to the traditional HOG + SVM sliding window detection method, the experimental results show that the detecting speed with the methods is obviously improved when the recognition accuracy is invariable.

Distributed operation of collaborating unmanned aerial vehicles for time-sensitive oil spill mapping

Abstract Multiple simple agents working together to achieve a common complex goal embodies the underlying theme of swarm concepts, with decentralized decision-making serving as the new frontier for tackling challenges associated with scalability, fault tolerance, and communication constraints. This paper builds on this emerging paradigm to develop a distributed approach (called PSOil) for off-shore oil spill mapping using a team of unmanned aerial vehicles or UAVs. In-flight waypoint planning is achieved via a new particle swarm mechanics-inspired technique, employing a novel combination of anomaly detection for knowledge extraction, and a stochastic occupancy grid approach for timely processing and frugal sharing of knowledge (with net communications