Application of Shore-Based Video and Unmanned Aerial Vehicles (Drones): Complementary Tools for Beach Studies

Lewicka

et al. 2020

JMSE

The human impact on the ecosystem has been particularly evident in the last century; it transforms the Earth’s surface on an unprecedented scale and brings about irreversible changes. One example is an oceanographic phenomenon known as a tombolo, i.e., a narrow belt connecting the mainland with an island lying near the shore formed as a result of sand and gravel being deposited by sea currents. The phenomenon contributes to an increase in the biogenic substance content in the littoral zone, which leads to increased cyanobacteria blooming in the summer period. Moreover, the debris accumulation in the littoral zone results in the mud formation, which makes the beach landscape less attractive. One of the main features of the tombolo phenomenon is its variability of shape, which includes the form of both the shore and the seabed adjacent to it. Therefore, to describe its size and spatio-temporal variability, it is necessary to apply methods for geodetic (the land) and hydrographic (the sea) measurements that can be carried out in different ways. The aim of the paper is to present the methodology for carrying out measurements of the tombolo oceanographic phenomenon using Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV) on the example of a waterbody adjacent to the Sopot pier. It also presents the results of surveys carried out in November 2019 within this area. The study demonstrated that the integration of two measuring devices whose development began in the second decade of the 20th century, i.e., UAVs and USVs, enables accurate (even up to several centimeters) and reliable determination of the scale and variability of the phenomena occurring in the littoral zone.

Section: Discussionmentioning

confidence: 99%

Methodology for Carrying out Measurements of the Tombolo Geomorphic Landform Using Unmanned Aerial and Surface Vehicles near Sopot Pier, Poland

Lewicka

et al. 2020

JMSE

“…Finally, tourism is also an important industry in some West African countries, with its impacts on coastal areas. The construction of infrastructure such as ports, hotels, and other recreational facilities directly on the coast has been responsible for clearing coastal vegetation, filling wetlands, and increasing sewage and solid waste loads (Giardino et al 2017a) and, in some cases, has contributed to accelerated coastal erosion (Appeaning 2009;Andrieu 2018;Angnuureng et al 2020;Dada et al 2021).…”

Section: Socio-environmental Threatsmentioning

confidence: 99%

Coastal Zone Changes in West Africa: Challenges and Opportunities for Satellite Earth Observations

et al. 2022

Self Cite

The West African coastal population and ecosystems are increasingly exposed to a multitude of hazards. These are likely to be exacerbated by global climate change and direct impacts from local human activities. Our ability to understand coastal changes has been limited by an incomplete understanding of the processes and the difficulty of obtaining detailed data. Recent advances in satellite techniques have made it possible to obtain rich coastal data sets that provide a solid foundation for improving climate change adaptation strategies for humanity and increasing the resilience of ecosystems for sustainable development. In this article, we review West African coastal layout and current socio-environmental challenges together with key parameters that can be monitored and several coastal management programs that rely on satellite techniques to monitor indicators at the regional level. The social, technical and scientific problems and difficulties that hinder the interest of coastal practitioners and decision-makers to use the satellite data are identified. We provide a roadmap to precisely respond to these difficulties and on how an improved satellite earth observation strategy can better support future coastal zone management in West Africa.

“…The image data can be analyzed to evaluate the reliability, durability, and bearing capacity of bridges [ 16 ]. Moreover, UAVs have been widely used in different industries for monitoring, such as beach problem studies [ 17 , 18 ], the change of coastal zone [ 19 ] topographic mapping to observe the environment [ 20 ], and constructing a map model to estimate the shoreline changes [ 21 ]. In the real measurement environment, UAVs are susceptible to wind, elevating force, component vibration, and other factors, resulting in irregular movement during their flight.…”

Section: Introductionmentioning

confidence: 99%

Comparisons of Differential Filtering and Homography Transformation in Modal Parameter Identification from UAV Measurement

Zhang

Chen

et al. 2021

Sensors

This paper proposes a differential filtering method for the identification of modal parameters of bridges from unmanned aerial vehicle (UAV) measurement. The determination of the modal parameters of bridges is a key issue in bridge damage detection. Accelerometers and fixed cameras have disadvantages of deployment difficulty. Hence, the actual displacement of a bridge may be obtained by using the digital image correlation (DIC) technology from the images collected by a UAV. As drone movement introduces false displacement into the collected images, the homography transformation is commonly used to achieve geometric correction of the images and obtain the true displacement of the bridge. The homography transformation is not always applicable as it is based on at least four static reference points on the plane of target points. The proposed differential filtering method does not request any reference points and will greatly accelerate the identification of the modal parameters. The displacement of the points of interest is tracked by the DIC technology, and the obtained time history curves are processed by differential filtering. The filtered signals are input into the modal analysis system, and the basic modal parameters of the bridge model are obtained by the operational modal analysis (OMA) method. In this paper, the power spectral density (PSD) is used to identify the natural frequencies; the mode shapes are determined by the ratio of the PSD transmissibility (PSDT). The identification results of three types of signals are compared: UAV measurement with differential filtering, UAV measurement with homography transformation, and accelerometer-based measurement. It is found that the natural frequencies recognized by these three methods are almost the same. This paper demonstrates the feasibility of UAV-differential filtering method in obtaining the bridge modal parameters; the problems and challenges in UAV measurement are also discussed.