Ultra-high Spatial Resolution Research Articles

High spatial resolution multi-channel optically pumped atomic magnetometer based on a spatial light modulator.

Ultra-sensitive multi-channel optically pumped atomic magnetometers based on the spin-exchange relaxation-free (SERF) effect are powerful tools for applications in the field of magnetic imaging. To simultaneously achieve ultra-high spatial resolution and ultra-high magnetic field sensitivity, we proposed a high-resolution multi-channel SERF atomic magnetometer for two-dimensional magnetic field measurements based on a digital micro-mirror device (DMD) as the spatial light modulator for a single vapor cell. Under the optimal experimental conditions obtained via spatial and temporal modulation of the probe light, we first demonstrated that the average sensitivity of the proposed 25-channel magnetometer was approximately 25fT/Hz1/2 with a spatial resolution of 216µm. Then, we measured the magnetic field distribution generated by a gradient coil and compared the experimentally obtained distributions with those calculated via finite element simulation. The obtained g value of 99.2% indicated good agreement between our experimental results and the theoretical calculations, thereby confirming that our proposed multi-channel SERF magnetometer was effective at measuring magnetic field distributions with an ultra-high spatial resolution.

A novel technique in BDG sensors: combination of phase and frequency correlation techniques

This paper investigates a novel theoretical model based on Brillouin dynamic grating (BDG) sensors with ultrahigh spatial resolution over long sensing length. So far, frequency correlation or phase correlation technique is singly used to measure properties of the BDG sensors, although each of the techniques has its own drawbacks due to either low spatial resolution and short sensing length or processing complexities. We introduce a straightforward theoretical technique in BDG sensors based on the combination of phase and frequency correlations (CPFC) in a polarization-maintaining fiber. Correlation peak points in the CPFC technique are points where the correlation peaks in the phase correlation technique are matched with the correlation peaks in the frequency correlation technique. The spatial resolution in this novel technique is the same as the spatial resolution of the phase correlation technique. The peaks of the frequency correlation technique have no effect on the final spatial resolution of the CPFC technique and can only increase its sensing length. Long sensing length with no complexity and short calculation process are advantages of the CPFC technique. By simulation of this innovative theoretical technique, a 9 mm spatial resolution over 17.7 km sensing length has achieved, which to the best of our knowledge is the longest sensing length in millimeter range spatial resolution reported so far in BDG sensors.

AUTOMATED CO-REGISTRATION OF INTRA-EPOCH AND INTER-EPOCH SERIES OF MULTISPECTRAL UAV IMAGES FOR CROP MONITORING

Abstract. The application of UAV-based aerial imagery has advanced exponentially in the past two decades. This can be attributed to UAV operational flexibility, ultra-high spatial resolution, inexpensiveness, and UAV-based sensors enhancement. Nonetheless, the application of multitemporal series of multispectral UAV imagery still suffers significant misregistration errors, and therefore becoming a concern for applications such as precision agriculture. Direct image georeferencing and co-registration is commonly done using ground control points; this is usually costly and time consuming. This research proposes a novel approach for automatic co-registration of multitemporal UAV imagery using intensity-based keypoints. The Speeded Up Robust Features (SURF), Binary Robust Invariant Scalable Keypoints (BRISK), Maximally Stable Extremal Regions (MSER) and KAZE algorithms, were tested and parameters optimized. Image matching performance of these algorithms informed the decision to pursue further experiments with only SURF and KAZE. Optimally parametrized SURF and KAZE algorithms obtained co-registration accuracies of 0.1 and 0.3 pixels for intra-epoch and inter-epoch images respectively. To obtain better intra-epoch co-registration accuracy, collective band processing is advised whereas one-to-one matching strategy is recommended for inter-epoch co-registration. The results were tested using a maize crop monitoring case and the; comparison of spectral response of vegetation between the UAV sensors, Parrot Sequoia and Micro MCA was performed. Due to the missing incidence sensor, spectral and radiometric calibration of Micro MCA imagery is observed to be key in achieving optimal response. Also, the cameras have different specifications and thus differ in the quality of their respective photogrammetric outputs.

Ultra-high spatial resolution BOLD fMRI in humans using combined segmented-accelerated VFA-FLEET with a recursive RF pulse design.

To alleviate the spatial encoding limitations of single-shot echo-planar imaging (EPI) by developing multi-shot segmented EPI for ultra-high-resolution functional MRI (fMRI) with reduced ghosting artifacts from subject motion and respiration. Segmented EPI can reduce readout duration and reduce acceleration factors, however, the time elapsed between segment acquisitions (on the order of seconds) can result in intermittent ghosting, limiting its use for fMRI. Here, "FLEET" segment ordering, where segments are looped over before slices, was combined with a variable flip angle progression (VFA-FLEET) to improve inter-segment fidelity and maximize signal for fMRI. Scaling a sinc pulse's flip angle for each segment (VFA-FLEET-Sinc) produced inconsistent slice profiles and ghosting, therefore, a recursive Shinnar-Le Roux (SLR) radiofrequency (RF) pulse design was developed (VFA-FLEET-SLR) to generate unique pulses for every segment that together produce consistent slice profiles and signals. The temporal stability of VFA-FLEET-SLR was compared against conventional-segmented EPI and VFA-FLEET-Sinc at 3T and 7T. VFA-FLEET-SLR showed reductions in both intermittent and stable ghosting compared to conventional-segmented and VFA-FLEET-Sinc, resulting in improved image quality with a minor trade-off in temporal SNR. Combining VFA-FLEET-SLR with acceleration, we achieved a 0.6-mm isotropic acquisition at 7T, without zoomed imaging or partial Fourier, demonstrating reliable detection of blood oxygenation level-dependent (BOLD) responses to a visual stimulus. To counteract the increased repetition time from segmentation, simultaneous multi-slice VFA-FLEET-SLR was demonstrated using RF-encoded controlled aliasing. VFA-FLEET with a recursive RF pulse design supports acquisitions with low levels of artifact and spatial blur, enabling fMRI at previously inaccessible spatial resolutions with a "full-brain" field of view.

Low-Cost Unmanned Aerial Multispectral Imagery for Siltation Monitoring in Reservoirs

The recent and continuous development of unmanned aerial vehicles (UAV) and small cameras with different spectral resolutions and imaging systems promotes new remote sensing platforms that can supply ultra-high spatial and temporal resolution, filling the gap between ground-based surveys and orbital sensors. This work aimed to monitor siltation in two large rural and urban reservoirs by recording water color variations within a savanna biome in the central region of Brazil using a low cost and very light unmanned platform. Airborne surveys were conducted using a Parrot Sequoia camera (~0.15 kg) onboard a DJI Phantom 4 UAV (~1.4 kg) during dry and rainy seasons over inlet areas of both reservoirs. Field measurements of total suspended solids (TSS) and water clarity were made jointly with the airborne survey campaigns. Field hyperspectral radiometry data were also collected during two field surveys. Bio-optical models for TSS were tested for all spectral bands of the Sequoia camera. The near-infrared single band was found to perform the best (R2: 0.94; RMSE: 7.8 mg L−1) for a 0–180 mg L−1 TSS range and was used to produce time series of TSS concentration maps of the study areas. This flexible platform enabled monitoring of the increase of TSS concentration at a ~13 cm spatial resolution in urban and rural drainages in the rainy season. Aerial surveys allowed us to map TSS load fluctuations in a 1 week period during which no satellite images were available due to continuous cloud coverage in the rainy season. This work demonstrates that a low-cost configuration allows dense TSS monitoring at the inlet areas of reservoirs and thus enables mapping of the sources of sediment inputs, supporting the definition of mitigation plans to limit the siltation process.

Highly Sensitive Photoacoustic Imaging: A New Strategy for Ultrahigh Spatial Resolution Seismic Physical Model Imaging

Seismic-physical-model imaging (SPM), a successful strategy for the research in seismic wave propagation and wave theoretical predictions, effectively bridges the computation modeling and the field exploration and leads to a nearly ideal setting without a rock matrix. However, the current strategy for SPM imaging, the ultrasonic imaging technology, shows a narrow excitation frequency and a low coupling efficiency, which strongly limit the resolution of the image. Herein, laser ultrasonic imaging strategy, an imaging strategy which merges the large penetration depth of ultrasound imaging and high contrast of optical imaging, is developed for SPM imaging for the first time, where photoacoustic (PA) effect is utilized for the excitation. A customized contrast agent, Co3O4 nanoflake arrays (CONAs), is designed for this special application of photoacoustic imaging in a large-scale via a facile hydrothermal method. The PA properties of the as-prepared CONAs are investigated with both theoretical and experimental methods. The results demonstrate the CONAs enhance the response signal over 16 times due to the strong light absorption, high photoacoustic-to-acoustic transformation efficiency and excellent thermal stability of the CONAs. By applying PA technology with the assistance of CONAs, 3D SPM images with high resolution are achieved.

Numerical Simulation of Ocean Circulation with Ultrahigh Spatial Resolution

This paper provides an overview of publications related to the study of submesoscale ocean variability. The significant progress achieved recently in understanding the special role of submesoscale processes in the formation of ocean circulation and ocean–atmosphere interaction, including modulation of the heat and gas exchange of the two media and their impact on the flux of biogenic elements into the top layer of the ocean, is emphasized. The necessity of conducting a study of submesoscale ocean variability in order to improve the quality of short-term marine forecasts is noted. Marine forecasts of the new level will be based on models with ultrahigh spatial resolution. The models will allow one to describe the reverse cascade of energy in the submesoscale range. In connection with the fact that new instruments capable of conducting 2–10 km surface observations of seas and oceans will be launched in the next five years, the possibilities of using the Black Sea as a testing area for the development of numerical models of circulation in a basin with a resolution of no less than a kilometer and improving methods of analysis and assimilation of observational technologies of the next generation are discussed.

Impact of China\u2019s high speed train window glass on GNSS signals and positioning performance

High speed train (HST) is an excellent platform to perform ultra-high spatial and temporal resolution observations of atmosphere using global navigation satellite systems (GNSS). However, we find that signal attenuation caused by HST window glass is a major barrier for HST-based GNSS applications inside HST chambers. A field experiment is conducted to analyze the effect of HST glass on GNSS signal propagation. In the experiment, GNSS observations are collected and analyzed from a receiver covered with an HST window glass and one with an open-sky view. The size of the HST window glass is 670 mm × 720 mm, with a thickness of 34 mm. The window glass is a double-glazing glass in which each layer has an actual thickness of 6 mm, and the two layers are separated by an air gap of 22 mm. The experiment results indicate that HST window glass can cause significant degradation to GNSS signals and even loss of tracking of the signal. Based on statistical results, HST window glass causes 39%, 56%, 49%, and 59% loss in GPS, GLONASS, Galileo, and BDS signals, respectively. Additionally, up to 20 dB-Hz of carrier-to-noise ratio (C/N0) degradation is also observed in the remaining observations. The significant signal attenuation and loss further lead to the decrease in the number of tracked satellites and occurrence of more cycle slips. The results of the study indicate that 44–230 cycle slips are detected for the HST glass-covered receiver whereas the receiver without glass does not exhibit more than 16 cycle slips. Additionally, the number of GNSS satellites tracked by the HST glass-covered receiver is reduced by 65% owing to the loss of signal. Furthermore, GNSS positioning performances from two receivers are also tested. With respect to GPS + GLONASS static precise point positioning (PPP), HST glass causes a degradation of 1.516 m and 1.159 m in the single-frequency and dual-frequency three-dimensional positioning accuracy, respectively. With respect to the GPS + GLONASS kinematic PPP, the accuracy degradations for single-frequency and dual-frequency kinematic PPP are 2.670 m and 4.821 m, respectively.

Mapping Heterogeneous Urban Landscapes from the Fusion of Digital Surface Model and Unmanned Aerial Vehicle-Based Images Using Adaptive Multiscale Image Segmentation and Classification

Considering the high-level details in an ultrahigh-spatial-resolution (UHSR) unmanned aerial vehicle (UAV) dataset, detailed mapping of heterogeneous urban landscapes is extremely challenging because of the spectral similarity between classes. In this study, adaptive hierarchical image segmentation optimization, multilevel feature selection, and multiscale (MS) supervised machine learning (ML) models were integrated to accurately generate detailed maps for heterogeneous urban areas from the fusion of the UHSR orthomosaic and digital surface model (DSM). The integrated approach commenced through a preliminary MS image segmentation parameter selection, followed by the application of three supervised ML models, namely, random forest (RF), support vector machine (SVM), and decision tree (DT). These models were implemented at the optimal MS levels to identify preliminary information, such as the optimal segmentation level(s) and relevant features, for extracting 12 land use/land cover (LULC) urban classes from the fused datasets. Using the information obtained from the first phase of the analysis, detailed MS classification was iteratively conducted to improve the classification accuracy and derive the final urban LULC maps. Two UAV-based datasets were used to develop and assess the effectiveness of the proposed framework. The hierarchical classification of the pilot study area showed that the RF was superior with an overall accuracy (OA) of 94.40% and a kappa coefficient (K) of 0.938, followed by SVM (OA = 92.50% and K = 0.917) and DT (OA = 91.60% and K = 0.908). The classification results of the second dataset revealed that SVM was superior with an OA of 94.45% and K of 0.938, followed by RF (OA = 92.46% and K = 0.916) and DT (OA = 90.46% and K = 0.893). The proposed framework exhibited an excellent potential for the detailed mapping of heterogeneous urban landscapes from the fusion of UHSR orthophoto and DSM images using various ML models.

Ultra-high-resolution fMRI of Human Ventral Temporal Cortex Reveals Differential Representation of Categories and Domains.

Human ventral temporal cortex (VTC) is critical for visual recognition. It is thought that this ability is supported by large-scale patterns of activity across VTC that contain information about visual categories. However, it is unknown how category representations in VTC are organized at the submillimeter scale and across cortical depths. To fill this gap in knowledge, we measured BOLD responses in medial and lateral VTC to images spanning 10 categories from five domains (written characters, bodies, faces, places, and objects) at an ultra-high spatial resolution of 0.8 mm using 7 Tesla fMRI in both male and female participants. Representations in lateral VTC were organized most strongly at the general level of domains (e.g., places), whereas medial VTC was also organized at the level of specific categories (e.g., corridors and houses within the domain of places). In both lateral and medial VTC, domain-level and category-level structure decreased with cortical depth, and downsampling our data to standard resolution (2.4 mm) did not reverse differences in representations between lateral and medial VTC. The functional diversity of representations across VTC partitions may allow downstream regions to read out information in a flexible manner according to task demands. These results bridge an important gap between electrophysiological recordings in single neurons at the micron scale in nonhuman primates and standard-resolution fMRI in humans by elucidating distributed responses at the submillimeter scale with ultra-high-resolution fMRI in humans.SIGNIFICANCE STATEMENT Visual recognition is a fundamental ability supported by human ventral temporal cortex (VTC). However, the nature of fine-scale, submillimeter distributed representations in VTC is unknown. Using ultra-high-resolution fMRI of human VTC, we found differential distributed visual representations across lateral and medial VTC. Domain representations (e.g., faces, bodies, places, characters) were most salient in lateral VTC, whereas category representations (e.g., corridors/houses within the domain of places) were equally salient in medial VTC. These results bridge an important gap between electrophysiological recordings in single neurons at a micron scale and fMRI measurements at a millimeter scale.

Core-Shell Nanostructure-Enhanced Raman Spectroscopy for Surface Catalysis.

ConspectusThe rational design of highly efficient catalysts relies on understanding their structure-activity relationships and reaction mechanisms at a molecular level. Such an understanding can be obtained by in situ monitoring of dynamic reaction processes using surface-sensitive techniques. Surface-enhanced Raman spectroscopy (SERS) can provide rich structural information with ultrahigh surface sensitivity, even down to the single-molecule level, which makes it a promising tool for the in situ study of catalysis. However, only a few metals (like Au, Ag, and Cu) with particular nanostructures can generate strong SERS effects. Thus, it is almost impossible to employ SERS to study transition metals (like Pt, Pd, Ru, etc.) and other nonmetal materials that are usually used in catalysis (material limitation). Furthermore, SERS is also unable to study model single crystals with atomically flat surface structures or practical nanocatalysts (morphology limitation). These limitations have significantly hindered the applications of SERS in catalysis over the past four decades since its discovery, preventing SERS from becoming a widely used technique in catalysis. In this Account, we summarize the extensive efforts done by our group since the 1980s, particularly in the past decade, to overcome the material and morphology limitations in SERS. Particular attention has been paid to the work using core-shell nanostructures as SERS substrates, because they provide high Raman enhancement and are highly versatile for application on different catalytic materials. Different SERS methodologies for catalysis developed by our group, including the "borrowing" strategy, shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS), and SHINERS-satellite strategy, are discussed in this account, with an emphasis on their principles and applications. These methodologies have successfully overcome the long-standing limitations of traditional SERS, enabling in situ tracking of catalysis at model single-crystal surfaces and practical nanocatalysts that can hardly be studied by SERS. Using these methodologies, we systematically studied a series of fundamentally important reactions, such as oxygen reduction reaction, hydrogen evolution reaction, electrooxidation, CO oxidation, and selective hydrogenation. As such, direct spectroscopic evidence of key intermediates that can hardly be detected by other traditional techniques was obtained. Combined with density functional theory and other in situ techniques, the reaction mechanisms and structure-activity relationships of these catalytic reactions were revealed at a molecular level. Furthermore, the future of SERS in catalysis has also been proposed in this work, which we believe should be focused on the in situ dynamic studies at the single-molecule, or even single-atom, level using techniques with ultrahigh sensitivity or spatial resolution, for example, single-molecule SERS or tip-enhanced Raman spectroscopy. In summary, core-shell nanostructure-enhanced Raman spectroscopies are shown to greatly boost the application of SERS in catalysis, from model systems like single-crystal surfaces to practical nanocatalysts, liquid-solid interfaces to gas-solid interfaces, and electrocatalysis to heterogeneous catalysis to photocatalysis. Thus, we believe this Account would attract increasing attention to SERS in catalysis and opens new avenues for catalytic studies.

Paddy Growing Stages Model Based on Vegetation Indices Using Ultra-High Spatial Resolution Images

Paddy is one of the most important food sources in Indonesia. It is evidenced by the increasing number of national rice consumption averagely at 6.29% per year, particularly in 2011–2015. However, the production seems does not equally match the rise in consumption. Estimates in rice production are relatively unreliable. It is due to the uneven planting time in several areas and a conventional method applied to estimate the production. This study proposes alternative methods to estimate rice production. This study aims to analyze the paddy growing stages and determine the most optimal model to estimate the paddy growing stages based on the vegetation indices. This study used the excellence of remote sensing technology especially for paddy field monitoring, emphasizing on paddy growing stages assessment. An airborne remote sensing platform, specifically the Unmanned Aerial Vehicle (UAV) is used to map the rice field in Bekasi Regency, West Java Province. Through mapping at low altitude, the UAV can produce images with ultra-high resolution, so it is very well used for mapping the paddy growing stages with diverse characteristics. Several vegetation indices, derived from Red, Green, and Blue (RGB) bands, namely Normalized Green Red Difference Index (NGRDI), Excess Green Vegetation Index (ExG), and Visible Atmospherically Resistant Index (VARI). Furthermore, the regression model is used to obtain the most optimal model of the three vegetation indices used for estimating the paddy growing stages. The result showed that the UAV with RGB bands could be used as a sensor to determine the relationship between vegetation indices to the paddy growing stages and the most optimal model for estimating the paddy growing stages based on the vegetation indices is ExG (R2 = 0.88).

Measuring Surface Moisture on a Sandy Beach based on Corrected Intensity Data of a Mobile Terrestrial LiDAR

Surface moisture plays a key role in limiting the aeolian transport on sandy beaches. However, the existing measurement techniques cannot adequately characterize the spatial and temporal distribution of the beach surface moisture. In this study, a mobile terrestrial LiDAR (MTL) is demonstrated as a promising method to detect the beach surface moisture using a phase-based Z&F/Leica HDS6100 laser scanner mounted on an all-terrain vehicle. Firstly, two sets of indoor calibration experiments were conducted so as to comprehensively investigate the effect of distance, incidence angle and sand moisture contents on the backscattered intensity by means of sand samples with an average grain diameter of 0.12 mm. A moisture estimation model was developed which eliminated the effects of the incidence angle and distance (it only relates to the target surface reflectance). The experimental results reveal both the distance and incidence angle influencing the backscattered intensity of the sand samples. The standard error of the moisture model amounts to 2.0% moisture, which is considerably lower than the results of the photographic method. Moreover, a field measurement was conducted using the MTL system on a sandy beach in Belgium. The accuracy and robustness of the beach surface moisture derived from the MTL data was evaluated. The results show that the MTL is a highly suitable technique to accurately and robustly measure the surface moisture variations on a sandy beach with an ultra-high spatial resolution (centimeter-level) in a short time span (12 × 200 m per minute).

Электронный микроскоп JEM-ARM300F2 - сверхвысокое пространственное разрешение и возможность субангстремного анализа

Электронный микроскоп JEM-ARM300F2 - сверхвысокое пространственное разрешение и возможность субангстремного анализа

Silicon-nanoforest-based solvent-free micro-supercapacitors with ultrahigh spatial resolutionviaIC-compatiblein situfabrication for on-chip energy storage

Through an IC-compatiblein situapproach, 3D silicon/nickel nanoforest based on-chip MSCs achieved ultrahigh spatial resolution and excellent electrochemical performance.

МОНІТОРИНГ МІСЦЕВОСТІ ТА ВИСОТНИХ ПЕРЕШКОД У РАЙОНАХ АЕРОПОРТУ

The urgency of the research. At present, new aviation rules concerning the provision of air navigation information have been introduced in Ukraine. The rules take into account the legislation of the European Union, Eurocontrol documents, ICAO Standards on the accuracy, processing and use of aeronautical data, which include data on terrain and obstacles in the areas of airports. Target setting.One of the factors influencing the safety of civil aviation is the consideration of obstacles on the routes in the form of elevations and high-altitude objects. This is evidenced by accidents and catastrophes of aircraft caused by col-lisions with high-altitude obstacles. Therefore, it is necessary to monitor the ground space in the areas of an airport for the timely detection of obstacles to the updating of the electronic database on terrain and obstacles.Actual scientific researches and issues analysis.Recent open access publications on existing methods of collecting geo-spatial data to determine terrain and obstacles in areas of the airport wer e reviewed.Uninvestigated parts of general matters defining.The analysis of the given sources allows to draw a conclusion that concerning area 1 of the airport which is the territory of the state, the contradictory information on use of this or that method of definition of a relief of district and obstacles is resulted.The research objective. The main purpose of the article is to analyze the methods of monitoring spatial information on terrain and obstacles in area 1 of the airport using space-based radar systems that would meet the requirements of ICAO in this area for the maintenance of electronic databases of terrain and obstacles.The statement of basic materials.The quantitative requirements of ICAO for data on terrain and obstacles in area 1 of theairport are given. The errors of the results of the satellite radar topographic survey (SRTM), which allowed to obtain a digital model of the Earth's topography, were resolutionin the vertical plane 1 m, and in the horizontal plane - 30 m. The method of Permanent Scatterer SAR Interferometry PSInSAR - interferometry of stable reflectors using radars with synthe-sized space-based aperture allows to obtain the accuracy of stable reflectors (natural and man-made objects) in the vertical plane of about 1 m and the error in determining the heights of other objects is 14 m. Currently, the PSInSAR method is used to monitor the subsidence of the earth's surface in cities, which allows to determine the deformation of the earth's surface to the nearest millimeter. The grouping of remote sensing satellites TerraSAR-X and TanDEM-X provided global coverage of the earth's surface with a digital terrain model with an accuracy of at least 2 m in height. The spatial resolution was about 1 m. In 2020, a satellite with a synthesized aperture of the Capella-2 radar survey was launched into Earth orbit. This unique micro satellite weighs 107 kg. Its camera equipment currently has an ultra-high spatial resolution of 50 x 50 cm.Conclusions.Modern methods of satellite radar can determine the planned and altitude position of objects in the area of airport 1 (territory of the state) with accuracy and resolution that meets the requirements of ICAO for the maintenance ofan electronicdatabase of terrain and obstacles. It is proposed to perform the first phase of monitoring objects in the country with the help of satellite radar, and in the second phase of monitoring to involve a ground survey - to clarify the attributive information about the objects detected in the first phase.

An efficient method for estimating dormant season grass biomass in tallgrass prairie from ultra-high spatial resolution aerial imaging produced with small unmanned aircraft systems

Fire is used extensively in prairie grassland management in the Flint Hills region of the midwestern United States, particularly at the end of the dormant season (March–April). A model is used to manage grassland fires in the region to avoid deterioration of air quality beyond acceptable standards. Dormant season dry biomass is an important parameter in the model. The commonly used method for producing high-quality biomass estimates relies on clipping, drying and weighing small biomass samples, which is tedious, expensive and does not scale efficiently to larger areas to provide regional estimates. Small unmanned aircraft systems (sUAS) were used to develop a reliable and more efficient method of biomass estimation based on the correlation between biomass and vegetation canopy height derived from digital surface models (DSMs). A linear regression model was developed from data collected at 11 representative sites in the Kansas Flint Hills region, and the model was validated at two sites. Biomass and canopy heights derived from DSMs were correlated, with a Pearson product moment correlation value of 0.881 (P-value <0.001). Biomass estimated from clipped vegetation at two validation sites positively correlated with model-derived biomass estimates, resulting in linear regression R2-values of 0.90 and 0.74 and Pearson moment correlation coefficients of 0.99 (P<0.001) and 0.86 (P=0.003). The described sUAS method has the potential to increase the efficiency and reliability of dormant season grassland biomass estimates.

THE IMPACT OF FOREST BELTS ON THE ECOLOGICAL CONDITIONS OF AUTOMOBILE TRANSPORT LAND

Environmental pollution by road emissions, including nitrogen oxide, dioxide, lead, was investigated. It was established that roadside green spaces, which are a natural barrier and delay the spread of pollution to the roadside, play an important protective role in the roadside. It was determined that the most common plantating along autotomobile roads are protective forest plantating. These plantings include natural forests and forest plantatings of linear type, which are located in the standardized strips of land along the roads or which are intended for their creation. These forest areas make protective functions and minimize the occurrence of negative impacts to the surrounding areas. Lately intensive construction works are being carried out, the fleet of trucks and cars, public automobile transport is increasing, the requirements for the construction of atomobile roads in accordance with the current environmental norms were substantiated, the necessity for inventory of forest plantations along the roads was substantiated. That is why the situation requires continuous updating of forest belts along the automobile roads. It is found that the most informative methods for the inventory of forest belts are space pictures with ultra-high spatial resolution of about one meter (type ICONOS). The stages and the works` list during the inventory of roadside forest belts were determined. The proposals for forecasting the required number of protective forest belts area in the future were substantiated. The basic State building codes and environmental standards, which are guided during the design and construction of automobile roads, were analyzed.

Single-Molecule Fluorescence Microscopy for Probing the Electrochemical Interface.

The electrochemical interface is an ultrathin interfacial region between the electrode and solution where electrochemical reactions occur. The study of the electrochemical interface continues to be one of the most exciting directions in modern electrochemistry research. Much of our existing knowledge about the electrochemical interface comes from ensemble measurements and ex situ imaging of the electrode surface. Due to its enormous complexity and highly dynamic nature, however, new imaging tools that can probe the interface in situ with ultrahigh spatial and temporal resolution and single-molecule sensitivity are apparently needed. Single-molecule fluorescence microscopy (SMFM) has emerged as a powerful tool that is uniquely suited for studying the electrochemical interface. In this mini-review, we first give a brief overview of various existing SMFM methods for studying electrochemical problems. We then discuss several exciting research topics involving the use of SMFM methods for studying surface-immobilized molecules, single freely diffusing molecules, single molecules as catalytic reaction indicators, and single-molecule labeling and imaging of interfacial nanobubbles. We anticipate that we will continue to see a rapid increase in publications on stochastic electrochemistry of single molecules and nanoparticles. The increased use of SMFM will likely bring new information to our study of the electrochemical interface.

Optical vortex-induced forward mass transfer: manifestation of helical trajectory of optical vortex

The orbital angular momentum of an optical vortex field is found to twist high viscosity donor material to form a micron-scale 'spin jet'. This unique phenomenon manifests the helical trajectory of the optical vortex. Going beyond both the conventional ink jet and laser induced forward mass transfer (LIFT) patterning technologies, it also offers the formation and ejection of a micron-scale 'spin jet' of the donor material even with an ultrahigh viscosity of 4 Pa·s. This optical vortex laser induced forward mass transfer (OV-LIFT) patterning technique will enable the development of next generation printed photonic/electric/spintronic circuits formed of ultrahigh viscosity donor dots containing functional nanoparticles, such as quantum dots, metallic particles and magnetic ferrite particles, with ultrahigh spatial resolution. It can also potentially explore a completely new needleless drug injection.