Search Results (14)

Initiatives such as the United Nations Decade of Ocean Science for Sustainable Development and Seabed 2030 promote seabed mapping worldwide. In Brazil, especially on the Espírito Santo Continental Shelf, high-resolution seabed mapping has revealed an unknown complex seascape. Circular depressions (CDs) were mapped for the first time in the Costa das Algas Marine Protection Area. Herein, we aim to present the CD metrics characteristics and discuss their relationship with morphology and relevance as a habitat based on multibeam bathymetry and ground truthing. A total of 3660 depressions were mapped between 46 and 85 m in depth, reaching an area of 460 m² and 5 m relief. The continental shelf morphology was subdivided into three sectors based on morphology: inter-valleys, valley edges, and valley flanks, and eleven sites were selected for direct sampling/imaging at the CDs along the sectors. The direct sampling was carried out by scuba-diving with video images and sediment samples collected inside and outside the depressions. The deeper central parts of the circular depressions appear to function as a sink, presenting aggregations of rhodoliths or other carbonate fragments. In most inter-valley depressions, mounds were observed along the edges of the depression. We did not have any indication of gas seeps and no clear sedimentological or morphological control on their occurrence. We first hypothesize that their origin results from combined diachronous processes. The circular depressions mapped at high resolution could be related to sea level processes acting during the last glacial period and shelf exposure, i.e., relict features. The CDs are responsible for biomass aggregation and fish bioturbation, forming holes and rubble mounds, representing a modern process occurring on a centimetric scale. The data collected so far indicate that this fine-scale feature is an important habitat for different fish species. The modern maintenance of these structures could be due to low sedimentation regime areas shaped by biotic excavation. Full article

Grasslands are one of the most abundant and biodiverse ecosystems in the world. However, in southern European countries, the abandonment of traditional management activities, such as extensive grazing, has caused many semi-natural grasslands to be invaded by shrubs. Therefore, there is a need to characterize semi-natural grasslands to determine their aboveground primary production and livestock-carrying capacity. Nevertheless, current methods lack a realistic identification of vegetation assemblages where grassland biophysical parameters can be accurately retrieved by the inversion of turbid-medium radiative transfer models (RTMs) in fine-grained landscapes. To this end, in this study we proposed a novel framework in which multiple endmember spectral mixture analysis (MESMA) was implemented to realistically identify grassland-dominated pixels from Sentinel-2 imagery in heterogeneous mountain landscapes. Then, the inversion of PROSAIL RTM (coupled PROSPECT and SAIL leaf and canopy models) was implemented separately for retrieving grassland biophysical parameters, including the leaf area index (LAI), fractional vegetation cover (FCOVER), and aboveground biomass (AGB), from grassland-dominated Sentinel-2 pixels while accounting for non-vegetated areas at the subpixel level. The study region was the southern slope of the Cantabrian Mountains (Spain), with a high spatial variability of fine-grained land covers. The MESMA grassland fraction image had a high accuracy based on validation results using centimetric resolution aerial orthophotographs (R² = 0.74, and RMSE = 0.18). The validation with field reference data from several mountain passes of the southern slope of the Cantabrian Mountains featured a high accuracy for LAI (R² = 0.74, and RMSE = 0.56 m²·m⁻²), FCOVER (R² = 0.78 and RMSE = 0.07), and AGB (R² = 0.67, and RMSE = 43.44 g·m⁻²). This study provides a reliable method to accurately identify and estimate grassland biophysical variables in highly diverse landscapes at a regional scale, with important implications for the management and conservation of threatened semi-natural grasslands. Future studies should investigate the PROSAIL inversion over the endmember signatures and subpixel fractions depicted by MESMA to adequately address the parametrization of the underlying background reflectance by using prior information and should also explore the scalability of this approach to other heterogeneous landscapes. Full article

Hyperspectral imaging technology holds great potential for various stages of the mining life cycle, both in active and abandoned mines, from exploration to reclamation. The technology, however, has yet to achieve large-scale industrial implementation and acceptance. While hyperspectral satellite imagery yields high spectral resolution, a high signal-to-noise ratio (SNR), and global availability with breakthrough systems like EnMAP, EMIT, GaoFen-5, PRISMA, and Tanager-1, limited spatial and temporal resolution poses challenges for the mining sectors, which require decimetre-to-centimetre-scale spatial resolution for applications such as reconciliation and environmental monitoring and daily temporal revisit times, such as for ore/waste estimates and geotechnical assessments. Hyperspectral imaging from drones (Uncrewed Aerial Systems; UASs) offers high-spatial-resolution data relevant to the pit/mine scale, with the capability for frequent, user-defined re-visit times for areas of limited extent. Areas of interest can be defined by the user and targeted explicitly. Collecting data in the visible to near and shortwave infrared (VNIR-SWIR) wavelength regions offers the detection of different minerals and surface alteration patterns, potentially revealing crucial information for exploration, extraction, re-mining, waste remediation, and rehabilitation. This is related to but not exclusive to detecting deleterious minerals for different processes (e.g., clays, iron oxides, talc), secondary iron oxides indicating the leakage of acid mine drainage for rehabilitation efforts, swelling clays potentially affecting rock integrity and stability, and alteration minerals used to vector toward economic mineralisation (e.g., dickite, jarosite, alunite). In this paper, we review applicable instrumentation, software components, and relevant studies deploying hyperspectral imaging datasets in or appropriate to the mining sector, with a particular focus on hyperspectral VNIR-SWIR UASs. Complementarily, we draw on previous insights from airborne, satellite, and ground-based imaging systems. We also discuss common practises for UAS survey planning and ground sampling considerations to aid in data interpretation. Full article

Peatland restoration projects are being employed worldwide as a form of climate change mitigation due to their potential for long-term carbon sequestration. Monitoring these environments (e.g., cover of keystone species) is therefore essential to evaluate success. However, existing studies have rarely examined peatland vegetation at fine scales due to its strong spatial heterogeneity and seasonal canopy development. The present study collected centimetre-scale multispectral Uncrewed Aerial Vehicle (UAV) imagery with a Parrot Sequoia camera (2.8 cm resolution; Parrot Drones SAS, Paris, France) in a temperate peatland over a complete growing season. Supervised classification algorithms were used to map the vegetation at the single-species level, and the Maximum Likelihood classifier was found to perform best at the site level (69% overall accuracy). The classification accuracy increased with the spatial resolution of the input data, and a large reduction in accuracy was observed when employing imagery of >11 cm resolution. Finally, the most accurate classifications were produced using imagery collected during the peak (July–August) or early growing season (start of May). These findings suggest that despite the strong heterogeneity of peatlands, these environments can be mapped at the species level using UAVs. Such an approach would benefit studies estimating peatland carbon emissions or using the cover of keystone species to evaluate restoration projects. Full article

The exposure of Mediterranean forests to large wildfires requires mechanisms to prevent and mitigate their negative effects on the territory and ecosystems. Fuel models synthesize the complexity and heterogeneity of forest fuels and allow for the understanding and modeling of fire behavior. However, it is sometimes challenging to define the fuel type in a structurally heterogeneous forest stand due to the mixture of characteristics from the different types and limitations of qualitative field observations and passive and active airborne remote sensing. This can impact the performance of classification models that rely on the in situ identification of fuel types as the ground truth, which can lead to a mistaken prediction of fuel types over larger areas in fire prediction models. In this study, a handheld mobile laser scanner (HMLS) system was used to assess its capability to define Prometheus fuel types in 43 forest plots in Aragón (NE Spain). The HMLS system captured the vertical and horizontal distribution of fuel at an extremely high resolution to derive high-density three-dimensional point clouds (average: 63,148 points/m²), which were discretized into voxels of 0.05 m³. The total number of voxels in each 5 cm height stratum was calculated to quantify the fuel volume in each stratum, providing the vertical distribution of fuels (m³/m²) for each plot at a centimetric scale. Additionally, the fuel volume was computed for each Prometheus height stratum (0.60, 2, and 4 m) in each plot. The Prometheus fuel types were satisfactorily identified in each plot and were compared with the fuel types estimated in the field. This led to the modification of the ground truth in 10 out of the 43 plots, resulting in errors being found in the field estimation between types FT2–FT3, FT5–FT6, and FT6–FT7. These results demonstrate the ability of the HMLS systems to capture fuel heterogeneity at centimetric scales for the definition of fuel types in the field in Mediterranean forests, making them powerful tools for fuel mapping, fire modeling, and ultimately for improving wildfire prevention and forest management. Full article

Remote-sensing ocean colour studies have already been used to determine coastal water quality, coastal biodiversity, and nutrient availability. In recent years, Unmanned Aerial Vehicles (UAVs) equipped with multispectral sensors, originally designed for agriculture applications, have also enabled water-quality studies of coastal waters. However, since the sea surface is constantly changing, commonly used photogrammetric methods fail when applied to UAV images captured over water areas. In this work, we evaluate the applicability of a five-band multispectral sensor mounted on a UAV to derive scientifically valuable water parameters such as chlorophyll-a (Chl-a) concentration and total suspended solids (TSS), including a new Python workflow for the manual generation of an orthomosaic in aquatic areas exclusively based on the sensor’s metadata. We show water-quality details in two different sites along the Maltese coastline on the centimetre-scale, improving the existing approximations that are available for the region through Sentinel-3 OLCI imagery at a much lower spatial resolution of 300 m. The Chl-a and TSS values derived for the studied regions were within the expected ranges and varied between 0 to 3 mg/m³ and 10 to 20 mg/m³, respectively. Spectral comparisons were also carried out along with some statistics calculations such as RMSE, MAE, or bias in order to validate the obtained results. Full article

Underwater photogrammetry provides a means of generating high-resolution products such as dense point clouds, 3D models, and orthomosaics with centimetric scale resolutions. Underwater photogrammetric models can be used to monitor the growth and expansion of benthic communities, including the assessment of the conservation status of seagrass beds and their change over time (time lapse micro-bathymetry) with OBIA classifications (Object-Based Image Analysis). However, one of the most complex aspects of underwater photogrammetry is the accuracy of the 3D models for both the horizontal and vertical components used to estimate the surfaces and volumes of biomass. In this study, a photogrammetry-based micro-bathymetry approach was applied to monitor Posidonia oceanica restoration actions. A procedure for rectifying both the horizontal and vertical elevation data was developed using soundings from high-resolution multibeam bathymetry. Furthermore, a 3D trilateration technique was also tested to collect Ground Control Points (GCPs) together with reference scale bars, both used to estimate the accuracy of the models and orthomosaics. The root mean square error (RMSE) value obtained for the horizontal planimetric measurements was 0.05 m, while the RMSE value for the depth was 0.11 m. Underwater photogrammetry, if properly applied, can provide very high-resolution and accurate models for monitoring seagrass restoration actions for ecological recovery and can be useful for other research purposes in geological and environmental monitoring. Full article

Conventional motors with complicated electromagnetic structures are difficult to miniaturise for millimetre- and centimetre-sized robots. Instead, small-scale robots are actuated using a variety of functional materials. We proposed a novel robot propelled by a piezoelectric ceramic in this work. The robot advances due to the asymmetric friction created by the spikes on the surface. The structural modelling was completed, static and dynamic models were established to predict the moving characteristics, the prototype was built using three dimensional (3D) printing technology, and the models were evaluated via experiments. Compared with conventional inchworm-type robots, the proposed robot is superior in simple structure because the clamping components are replaced by spikes with asymmetric friction. Compared with SMA (shape memory alloy) actuating inchworm-type robots, it has a faster velocity with higher resolution. Meanwhile, the components are printed through an additive manufacturing process that is convenient and avoids assembly errors. This design could make contributions to many areas, such as pipe inspection, earthquake rescue, and medicine delivery. Full article

Acoustic metamaterials are large-scale materials with small-scale structures. These structures allow for unusual interaction with propagating sound and endow the large-scale material with exceptional acoustic properties not found in normal materials. However, their multi-scale nature means that the manufacture of these materials is not trivial, often requiring micron-scale resolution over centimetre length scales. In this review, we bring together a variety of acoustic metamaterial designs and separately discuss ways to create them using the latest trends in additive manufacturing. We highlight the advantages and disadvantages of different techniques that act as barriers towards the development of realisable acoustic metamaterials for practical audio and ultrasonic applications and speculate on potential future developments. Full article

A field, petrographic and geochemical study of two Triassic–Jurassic carbonate successions from the Maritime Alps, SE France, indicates that dolomitization is related to episodic fracturing and the flow of hydrothermal fluids. The mechanism governing hydrothermal fluids has been documented with the best possible spatio-temporal resolutions specifying the migration and trapping of hydrothermal fluids as a function of depth. This is rarely reported in the literature, as it requires a very wide range of disciplines from facies analysis (petrography) to very diverse and advanced chemical methods (elemental analysis, isotope geochemistry, microthermometry). In most cases, our different recognized diagenetic phases were mechanically separated on a centimetric scale and analyzed separately. The wide range of the δ¹⁸O_VPDB and ⁸⁷Sr/⁸⁶Sr values of diagenetic carbonates reflect three main diagenetic realms, including: (1) the formation of replacive dolomites (Type I) in the eogenetic realm, (2) formation of coarse to very coarse crystalline saddle dolomites (Types II and Type III) in the shallow to deep burial mesogenetic realm, respectively, and (3) telogenetic formation of a late calcite cement (C1) in the telogenetic realm due to the uplift incursion of meteoric waters. The Triassic dolomites show a lower ⁸⁷Sr/⁸⁶Sr ratio (mean = 0.709125) compared to the Jurassic dolomites (mean = 0.710065). The Jurassic calcite (C1_J) shows lower Sr isotopic ratios than the Triassic C1_T calcite. These are probably linked to the pulses of the seafloor’s hydrothermal activity and to an increase in the continental riverine input during Late Cretaceous and Early Cenozoic times. This study adds a new insight into the burial diagenetic conditions during multiple hydrothermal flow events. Full article

Mudrocks are highly heterogeneous in terms of both composition and fabric, with heterogeneities occurring at the submicron to centimetre plus scale. Such heterogeneities are relatively easy to visualise at the micron-scale through the use of modern scanning electron microscopy (SEM) techniques, but due to their inherent fine grain size, can be difficult to place within the greater context of the mudrock as a whole, or to visualise variation when viewed at a centimetre scale. The utilisation of SEM to collect automated high-resolution backscattered (BSE) images (tiles) over whole, polished thin-sections presents a potential large data bank on compositional and fabric changes that can be further processed using simple image analysis techniques to extract data on compositional variation. This can then be plotted graphically in 2D as colour contoured distribution maps to illustrate any observed variability. This method enables the easy visualisation of micron-scale heterogeneity present in mudrock, which are here illustrated and discussed for pyrite and organic content at the larger (thin-section) centimetre scale. This does not require the use of other techniques such as energy dispersive x-ray (EDX) mapping to identify phases present, but instead utilizes BSE images that may already have been collected for textural fabric studies. The technique can also be applied to other phases in mudrocks, such as carbonates and silicates, as well as porosity. Data can also be extracted and used in a similar fashion to bulk compositional analytical techniques such as inductively coupled plasma-atomic emission microscopy (ICP-AES) and carbon, nitrogen and sulphur (CNS) analysis, for average organic carbon and percentage pyrite. Full article

Among grapevine diseases affecting European vineyards, Flavescence dorée (FD) and Grapevine Trunk Diseases (GTD) are considered the most relevant challenges for viticulture because of the damage they cause to vineyards. Unmanned Aerial Vehicle (UAV) multispectral imagery could be a powerful tool for the automatic detection of symptomatic vines. However, one major difficulty is to discriminate different kinds of diseases leading to similar leaves discoloration as it is the case with FD and GTD for red vine cultivars. The objective of this paper is to evaluate the potentiality of UAV multispectral imagery to separate: symptomatic vines including FD and GTD (Esca and black dead arm) from asymptomatic vines (Case 1) and FD vines from GTD ones (Case 2). The study sites are localized in the Gaillac and Minervois wine production regions (south of France). A set of seven vineyards covering five different red cultivars was studied. Field work was carried out between August and September 2016. In total, 218 asymptomatic vines, 502 FD vines and 199 GTD vines were located with a centimetric precision GPS. UAV multispectral images were acquired with a MicaSense RedEdge^® sensor and were processed to ultimately obtain surface reflectance mosaics at 0.10 m ground spatial resolution. In this study, the potentiality of 24 variables (5 spectral bands, 15 vegetation indices and 4 biophysical parameters) are tested. The vegetation indices are selected for their potentiality to detect abnormal vegetation behavior in relation to stress or diseases. Among the biophysical parameters selected, three are directly linked to the leaf pigments content (chlorophyll, carotenoid and anthocyanin). The first step consisted in evaluating the performance of the 24 variables to separate symptomatic vine vegetation (FD or/and GTD) from asymptomatic vine vegetation using the performance indicators from the Receiver Operator Characteristic (ROC) Curve method (i.e., Area Under Curve or AUC, sensibility and specificity). The second step consisted in mapping the symptomatic vines (FD and/or GTD) at the scale of the field using the optimal threshold resulting from the ROC curve. Ultimately, the error between the level of infection predicted by the selected variables (proportion of symptomatic pixels by vine) and observed in the field (proportion of symptomatic leaves by vine) is calculated. The same methodology is applied to the three levels of analysis: by vineyard, by cultivar (Gamay, Fer Servadou) and by berry color (all red cultivars). At the vineyard and cultivar levels, the best variables selected varies. The AUC of the best vegetation indices and biophysical parameters varies from 0.84 to 0.95 for Case 1 and 0.74 to 0.90 for Case 2. At the berry color level, no variable is efficient in discriminating FD vines from GTD ones (Case 2). For Case 1, the best vegetation indices and biophysical parameter are Red Green Index (RGI)/ Green-Red Vegetation Index (GRVI) (based on the green and red spectral bands) and Car (linked to carotenoid content). These variables are more effective in mapping vines with a level of infection greater than 50%. However, at the scale of the field, we observe misclassified pixels linked to the presence of mixed pixels (shade, bare soil, inter-row vegetation and vine vegetation) and other factors of abnormal coloration (e.g., apoplectic vines). Full article

The technique of Faraday tomography is a key tool for the study of magnetised plasmas in the new era of broadband radio-polarisation observations. In particular, observations at metre wavelengths provide significantly better Faraday depth accuracies compared to traditional centimetre-wavelength observations. However, the effect of Faraday depolarisation makes the polarised signal very challenging to detect at metre wavelengths (MHz frequencies). In this work, Faraday tomography is used to characterise the Faraday rotation properties of polarised sources found in data from the LOFAR Two-Metre Sky Survey (LoTSS). Of the 76 extragalactic polarised sources analysed here, we find that all host a radio-loud AGN (Active Galactic Nucleus). The majority of the sources (∼64%) are large FRII radio galaxies with a median projected linear size of 710 kpc and median radio luminosity at 144 MHz of $4\times {10}^{26}$ W Hz${}^{-1}$ (with ∼13% of all sources having a linear size >1 Mpc). In several cases, both hotspots are detected in polarisation at an angular resolution of ∼20${}^{″}$ . One such case allowed a study of intergalactic magnetic fields on scales of 3.4 Mpc. Other detected source types include an FRI radio galaxy and at least eight blazars. Most sources display simple Faraday spectra, but we highlight one blazar that displays a complex Faraday spectrum, with two close peaks in the Faraday dispersion function. Full article

The rapid expansion of cities increases the need of urban remote sensing for a large scale monitoring. This paper provides greater understanding of how TerraSAR-X (TSX) high-resolution abilities enable to reach the spatial precision required to monitor individual buildings, through the use of a 4 year temporal stack of 100 images over Paris (France). Three different SAR modes are investigated for this purpose. First a method involving a whole time-series is proposed to measure realistic heights of buildings. Then, we show that the small wavelength of TSX makes the interferometric products very sensitive to the ordinary building-deformation, and that daily deformation can be measured over the entire building with a centimetric accuracy, and without any a priori on the deformation evolution, even when neglecting the impact of the atmosphere. Deformations up to 4 cm were estimated for the Eiffel Tower and up to 1 cm for other lower buildings. These deformations were analyzed and validated with weather and in situ local data. Finally, four TSX polarimetric images were used to investigate geometric and dielectric properties of buildings under the deterministic framework. Despite of the resolution loss of this mode, the possibility to estimate the structural elements of a building orientations and their relative complexity in the spatial organization are demonstrated. Full article