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Fruit tree frost, an agricultural meteorological disaster primarily occurring in spring, severely impacts the growth and development of trees and fruit set. Therefore, exploring the temperature change rules of fruit trees during frost events is of considerable importance. This study used a T40 unmanned aerial vehicle (UAV) as the test vehicle based on the air disturbance frost prevention principle. The airflow field change pattern of the UAV was explored using the computational fluid dynamics simulation method, and the reliability of the multi-rotor UAV in frost prevention was verified using field tests. Setting the UAV height at 6.0 m above the ground and the rotor speed at 1000 r min−1, it was found that under the conditions of the inverse temperature phenomenon, the temperatures of different altitude layers will eventually converge to a stable value when the UAV down-rotating airflow is disturbed, which could be completed rapidly within 20 s. The results of the field test also showed that when the fruit trees reached the critical temperature of frost at the flowering stage, UAV intervention could have a substantial effect on the warming of the near-surface layers, whose warming amplitude was in the range of 2.5 °C–3 °C. This study provides a reliable method for mitigating frost, which serves as an important theoretical and guiding basis for improving agricultural frost disasters in China. • A multi-rotor UAV is used to test frost protection performance on fruit trees. • The temperature field characterizations are obtained. • The anti-frost effectiveness of UAV intervention is confirmed. [ABSTRACT FROM AUTHOR]

Featured Application: An aerial seeding system for rapeseed based on an air-assisted centralized metering device and a commercialized multi-rotor crop protection UAV (unmanned aerial vehicle) is presented. To improve the overall mechanization level of rapeseed production in China, especially in some hilly regions where ground machinery cannot enter the fields or can only enter with very low economic benefits, a special aerial seeding system for rapeseed based on a miniature air-assisted centralized metering device was designed and tested in this study. Unlike existing commercial aerial seeding systems, the proposed seed meter was a miniaturized version derived from the traditional air-feeding seed meter on ground planters. The new version contained a redesigned seed feeding component to overcome problems of serious air backflow to the seed box and difficult seed feeding after miniaturization. Three groups of experiments were designed and conducted to optimize the parameters of the seed meter and test its performance. Results from the orthogonal experiment showed that the seed feeding component performed best when the seed layer thickness was 45 mm, the rotational speed of the gear disc was 45 r/min, and the airflow pressure was 2450 Pa. Results from the static workbench test showed that the designed seeding system had a maximum average total sowing efficiency of 537.17 g/min, with the maximum values of the stability variation coefficient of total seeding rate (seven ports) and the consistency variation coefficient between each port was 2.37% and 4.89%, respectively. Field tests further proved that the designed aerial seeding system could work stably, uniformly, and efficiently, so that the agronomic requirements of rape crop planting could be well met. [ABSTRACT FROM AUTHOR]

The karst strata in the southwestern mountainous areas of China are extensively developed, creating a fragile geological environment. Landslide geological disasters occur frequently in these areas due to high annual rainfall, concentrated time periods, and frequent human engineering activities. Conventional ground geophysical methods face challenges in complex terrains, making it difficult to quickly and reliably obtain underground structures in landslide-prone areas. The semi-airborne transient electromagnetic method (SATEM) combines ground-based transmission and airborne reception of electromagnetic responses. This method, characterized by large emission magnetic moment and rapid data collection in the air, offers advantages in detecting deep geological structures in complex terrain areas. This article presents the application of a newly developed loop source SATEM system, integrated with multi-rotor unmanned aerial vehicles (UAVs), to conduct deep geological structure detection experiments on a large-scale landslide. The inversion results clearly depict the spatial distribution of the Feixianguan Formation and Longtan Formation, as well as vertical fractures developed in the strata due to underground coal mining. The detection test demonstrates the applicability of the SATEM method in detecting underground structures in Karst Plateau special landform areas, providing a new detection approach for similar regions. [ABSTRACT FROM AUTHOR]

Identification of forest burn severity is essential for fire assessments and a necessary procedure in modern forest management. Due to the low efficiency and labor intensity of the current post-fire field survey in China's Forestry Standards, the limitation of temporal resolution of satellite imagery, and poor objectivity of manual interpretations, a new method for automatic extraction of forest burn severity based on small visible unmanned aerial vehicle (UAV) images is proposed. Taking the forest fires which occurred in Anning city of Yunnan Province in 2019 as the study objects, post-fire imagery was obtained by a small, multi-rotor near-ground UAV. Some image recognition indices reflecting the variations in chlorophyll loss effects in different damaged forests were developed with spectral characteristics customized in A and C, and the texture features such as the mean, standard deviation, homogeneity, and shape index of the length–width ratio. An object-oriented method is used to determine the optimal segmentation scale for forest burn severity and a multilevel rule classification and extraction model is established to achieve the automatic identification and mapping. The results show that the method mentioned above can recognize different types of forest burn severity: unburned, damaged, dead, and burnt. The overall accuracy is 87.76%, and the Kappa coefficient is 0.8402, which implies that the small visible UAV can be used as a substitution for the current forest burn severity survey standards. This research is of great practical significance for improving the efficiency and precision of forest fire investigation, expanding applications of small UAVs in forestry, and developing an alternative for forest fire loss assessments in the forestry industry. [ABSTRACT FROM AUTHOR]

Background: Nanguo pear is a distinctive pear variety in northeast China, grown mainly in mountainous areas. Due to terrain limitations, ground-based pesticide application equipment is difficult to use. This limitation could be overcome by using unmanned aerial vehicles (UAVs) for pesticide application in Nanguo pear orchards. This study evaluated the spraying performance of two UAVs in the Nanguo pear orchards and compared them with a manually used backpack electric sprayer (BES). The study also analyzed the effect of canopy size on droplet deposition and ground loss, and evaluated two sampling methods, leaf sampling and telescopic rod sampling., Results: Compared to BESs, droplet deposition is lower for UAVs, but the actual pesticide active ingredient deposition is not necessarily lower given the solution concentration. The droplet deposition varies among different UAVs due to structural differences. Under the same UAV operating parameters, droplet deposition on trees with smaller canopy sizes is typically greater than that on trees with larger canopy sizes, and the ground loss was also more severe. Although telescopic rod sampling is a quick and convenient method, it can only reflect the trend of droplet deposition, and the data error is greater compared with leaf sampling., Conclusion: UAVs can achieve better droplet deposition in mountainous Nanguo pear orchards and does almost no harm to the operators compared with the BES. However, canopy size needs to be considered to adjust the application volume rate. Telescopic rods can be used for qualitative analyses, but are not recommended for quantitative analyses. © 2024 Society of Chemical Industry., (© 2024 Society of Chemical Industry.)

In recent years, multi-rotor Unmanned Aerial Vehicles (UAVs) have been employed in the field of plant protection in China. Spray drift has been considered a major impact in agriculture aerial spraying, and spray quality in the application of plant protection products. The downwash including wake vortices and downward wind field plays a major role in the dispersal and deposition of pesticide spray released by nozzle(s) equipped in aircraft. Differ from the fixed-wing UAV, the downwash flow of multi-rotor UAV resulted from the rotation of the rotor. Therefore, a study on off-target drift and ground deposit concerning the rotor rotation was simulated through a series of Computational Fluid Dynamics (CFD) simulations to obtain the influence of downwash. The discrete Phase Model (DPM) was taken to simulate the motion of droplet particles since it is an appropriate way to simulate discrete phases in the flow field and can track particle trajectory. In this study, the parameters of CFD simulations were acquired by three kinds of actual replicated experiments. The simulation analysis mainly obtains the droplet drift and deposition rule, the influence of eddy current, and downwash flow caused by the rotor rotation. The results showed that the downwash distribution below different rotors was different owing to the flight angle of inclination, "behind" is the greatest, "middle" is secondly, and "forward" is the smallest in value(behind, middle, and forward represent three regions below rotors along flight direction). According to the simulation results, two methods of reducing droplet drift were put forward and specific simulations were carried out to prove their feasibility. The results of this study can provide theoretical support for improving the spray quality of UAVs and reducing the drift of droplets. [ABSTRACT FROM AUTHOR]

Traditional villages are important carriers of cultural heritage, and the quantitative study of their spatial characteristics is an important approach to their preservation. However, the rapid extraction, statistics, and estimation of the rich spatial characteristic indicators in these villages have become bottlenecks in traditional village research. This paper employs UAV (unmanned aerial vehicle) and handheld laser scanners to acquire three-dimensional point cloud data and construct a spatial feature three-dimensional calculation workflow of "field data collection—data processing—data analysis and application", which enables the rapid acquisition, processing, and analysis of three-dimensional village data. Typical case studies are conducted in Liukeng Village, China, focusing on the quantification of village spatial characteristics at three levels: topography, streets and alleys, and individual buildings, as well as comparative studies of multiple villages across different regions. The quantification of three-dimensional data reveals the regularity of village spatial characteristics and uncovers the spatial wisdom embedded in the site selection and spatial structure of traditional villages. This paper establishes a complete technical route for the quantitative analysis of villages, deepens public understanding of the diverse value of traditional villages, and provides technical support for research and practice in related fields. [ABSTRACT FROM AUTHOR]

In China, unmanned aerial vehicles (UAVs) are increasingly used for broadcast application of agricultural inputs such as pesticides, fertilizers, and seeds. UAVs have the potential for site-specific precision agriculture, facilitating precise management of fertilization, plant protection, and irrigation to reduce environmental footprint of farming. There has been research on the use of UAVs in agriculture, but less is known about UAV-based precision agriculture, particularly pattern management. To close these research gaps, this paper conducted structured in-depth interviews with 18 experts from various fields related to UAVs in Chinese agriculture to study the status quo, drivers, and barriers of adopting UAVs, focusing on UAV-based precision agriculture, particularly pattern management. The results show that the adoption of UAVs in China is influenced by farmers' production characteristics, farmers' perceptions about UAVs, and social factors. UAV-based precision agriculture is at the initial stage in China, and the promotion of this approach still needs to overcome technical barriers such as improving the accuracy of crop measurements, developing real-time UAV positioning systems, and enhancing the response time of variable-rate spraying systems, as well as socio-economic barriers like farmers' limited UAV-related knowledge, small farm sizes, and lack of technical assistance. [ABSTRACT FROM AUTHOR]

In recent years, unmanned aerial vehicles (UAVs) have become widely used in emergency investigations of major natural hazards over large areas; however, UAVs are less commonly employed to investigate single geohazards. Based on a number of successful investigations in the Three Gorges Reservoir area, China, a complete UAVbased method for performing emergency investigations of single geo-hazards is described. First, a customized UAV system that consists of a multi-rotor UAV subsystem, an aerial photography subsystem, a ground control subsystem and a ground surveillance subsystem is described in detail. The implementation process, which includes four steps, i.e., indoor preparation, site investigation, on-site fast processing and application, and indoor comprehensive processing and application, is then elaborated, and two investigation schemes, automatic and manual, that are used in the site investigation step are put forward. Moreover, some key techniques and methods - e.g., the layout and measurement of ground control points (GCPs), route planning, flight control and image collection, and the Structure from Motion (SfM) photogrammetry processing - are explained. Finally, three applications are given. Experience has shown that using UAVs for emergency investigation of single geo-hazards greatly reduces the time, intensity and risks associated with on-site work and provides valuable, high-accuracy, high-resolution information that supports emergency responses. [ABSTRACT FROM AUTHOR]

Modelling of glacier and ice sheet micro-topography is meaningful for the understanding of interactions between local ice mass and climate. Here, we used an Unmanned Aerial Vehicle (UAV) platform composed of a DJI Phantom 4 and a D-RTK mobile station to model the surface micro-topography around Zhongshan Station of China, East Antarctica. Two UAV survey types (vertical and oblique aerial photogrammetry) were performed during the China's 35th Antarctic expedition (CHINARE) in 2018–2019. Six surveys were obtained by the SfM-MVS technology. Then, we extracted the features of glacier surface micro-topography (blue ice, crevasses, ice doline and melt-water). It's noteworthy that traces of melt-water and a large ice doline appeared on the surface of Dalk Glacier in December 2018. Finally, we concluded that surface micro-topographic features, observable in the UAV-derived models but unavailable on satellite images, may reveal hints for interactions between surface and beneath processes in regional polar glacier. [ABSTRACT FROM AUTHOR]

This study presents an innovative method for large-scale surface water quality assessment in rugged terrain areas, specifically tailored for regions like the Qinba Mountains. The approach combines the use of high-resolution (10 cm) multispectral data acquired by unmanned aerial vehicles (UAVs) with synchronized ground sampling and 1 m resolution multispectral imagery from China's Gaofen-2 satellite. By integrating these technologies, the study aims to capitalize on the convenience and synchronized observation capabilities of UAV remote sensing, while leveraging the broad coverage of satellite remote sensing to overcome the limitations of each individual technique. Initially, a multispectral estimation model is developed for key water quality parameters, including chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP), utilizing data from UAVs and coordinated ground samples. Subsequently, a comparison is made between the spectral band ratios (R/G and NIR/G) obtained from the UAV data and those from the Gaofen-2 satellite data, revealing a substantial similarity. Ultimately, this integrated methodology is successfully employed in monitoring water quality across a vast area, particularly along the midstream of the Hanjiang River in the Qinba Mountain region. The results underscore the feasibility, advantages, improved efficiency, and enhanced accuracy of this approach, making it particularly suitable for large-scale water quality monitoring in mountainous terrain. Furthermore, this method reduces the burden associated with traditional ground-based spectral acquisitions, paving the way for a more practical and cost-effective solution in monitoring vast water bodies. [ABSTRACT FROM AUTHOR]

Backgrounds: UAVs for crop protection hold significant potential for application in mountainous orchard areas in China. However, certain issues pertaining to UAV spraying need to be addressed for further technological advancement, aimed at enhancing crop protection efficiency and reducing pesticide usage. These challenges include the potential for droplet drift, limited capacity for pesticide solution. Consequently, efforts are required to overcome these limitations and optimize UAV spraying technology. Methods: In order to balance high deposition and low drift in plant protection UAV spraying, this study proposes a plant protection UAV spraying method. In order to study the operational effects of this spraying method, this study conducted a UAV spray and grid impact test to investigate the effects of different operational parameters on droplet deposition and drift. Meanwhile, a spray model was constructed using machine learning techniques to predict the spraying effect of this method. Results and discussion: This study investigated the droplet deposition rate and downwind drift rate on three types of citrus trees: traditional densely planted trees, dwarf trees, and hedged trees, considering different particle sizes and UAV flight altitudes. Analyzing the effect of increasing the grid on droplet coverage and deposition density for different tree forms. The findings demonstrated a significantly improved droplet deposition rate on dwarf and hedged citrus trees compared to traditional densely planted trees and adopting a fixed-height grid increased droplet coverage and deposition density for both the densely planted and trellised citrus trees, but had the opposite effect on dwarfed citrus trees. When using the grid system. Among the factors examined, the height of the sampling point exhibited the greatest influence on the droplet deposition rate, whereas UAV flight height and droplet particle size had no significant impact. The distance in relation to wind direction had the most substantial effect on droplet drift rate. In terms of predicting droplet drift rate, the BP neural network performed inadequately with a coefficient of determination of 0.88. Conversely, REGRESS, ELM, and RBFNN yielded similar and notably superior results with a coefficient of determination greater than 0.95. Notably, ELM demonstrated the smallest root mean square error. [ABSTRACT FROM AUTHOR]

Introduction: Leaf area index (LAI) is a critical physiological and biochemical parameter that profoundly affects vegetation growth. Accurately estimating the LAI for winter wheat during jointing stage is particularly important for monitoring wheat growth status and optimizing variable fertilization decisions. Recently, unmanned aerial vehicle (UAV) data and machine/depth learning methods are widely used in crop growth parameter estimation. In traditional methods, vegetation indices (VI) and texture are usually to estimate LAI. Plant Height (PH) unlike them, contains information about the vertical structure of plants, which should be consider. Methods: Taking Xixingdian Township, Cangzhou City, Hebei Province, China as the research area in this paper, and four machine learning algorithms, namely, support vector machine(SVM), back propagation neural network (BPNN), random forest (RF), extreme gradient boosting (XGBoost), and two deep learning algorithms, namely, convolutional neural network (CNN) and long short-term memory neural network (LSTM), were applied to estimate LAI of winter wheat at jointing stage by integrating the spectral and texture features as well as the plant height information from UAV multispectral images. Initially, Digital Surface Model (DSM) and Digital Orthophoto Map (DOM) were generated. Subsequently, the PH, VI and texture features were extracted, and the texture indices (TI) was further constructed. The measured LAI on the ground were collected for the same period and calculated its Pearson correlation coefficient with PH, VI and TI to pick the feature variables with high correlation. The VI, TI, PH and fusion were considered as the independent features, and the sample set partitioning based on joint x-y distance (SPXY) method was used to divide the calibration set and validation set of samples. Results: The ability of different inputs and algorithms to estimate winter wheat LAI were evaluated. The results showed that (1) The addition of PH as a feature variable significantly improved the accuracy of the LAI estimation, indicating that wheat plant height played a vital role as a supplementary parameter for LAI inversion modeling based on traditional indices; (2) The combination of texture features, including normalized difference texture indices (NDTI), difference texture indices (DTI), and ratio texture indices (RTI), substantially improved the correlation between texture features and LAI; Furthermore, multi-feature combinations of VI, TI, and PH exhibited superior capability in estimating LAI for winter wheat; (3) Six regression algorithms have achieved high accuracy in estimating LAI, among which the XGBoost algorithm estimated winter wheat LAI with the highest overall accuracy and best results, achieving the highest R² (R² = 0.88), the lowest RMSE (RMSE=0.69), and an RPD greater than 2 (RPD=2.54) Discussion: This study provided compelling evidence that utilizing XGBoost and integrating spectral, texture, and plant height information extracted from UAV data can accurately monitor LAI during the jointing stage of winter wheat. The research results will provide a new perspective for accurate monitoring of crop parameters through remote sensing. [ABSTRACT FROM AUTHOR]

The development in uncrewed aerial vehicle (UAV) technologies over the past decade has led to a plethora of platforms that can potentially enable greenhouse gas emission quantification. Here, we report the development of a new air sampler, consisting of a pumped stainless coiled tube of 150 m in length with controlled time stamping, and its deployment from an industrial UAV to quantify CO 2 and CH 4 emissions from the main coking plant stacks of a major steel maker in eastern China. Laboratory tests show that the time series of CO 2 and CH 4 measured using the sampling system is smoothed when compared to online measurement by the cavity ring-down spectrometer (CRDS) analyzer. Further analyses show that the smoothing is akin to a convolution of the true time series signals with a heavy-tailed digital filter. For field testing, the air sampler was mounted on the UAV and flown in virtual boxes around two stacks in the coking plant of the Shagang Group (steel producer). Mixing ratios of CO 2 and CH 4 in air and meteorological parameters were measured from the UAV during the test flight. A mass-balance computational algorithm was used on the data to estimate the CO 2 and CH 4 emission rates from the stacks. Using this algorithm, the emission rates for the two stacks from the coking plant were calculated to be 0.12±0.014 t h -1 for CH 4 and 110±18 t h -1 for CO 2 , the latter being in excellent agreement with material-balance-based estimates. A Gaussian plume inversion approach was also used to derive the emission rates, and the results were compared with those derived using the mass-balance algorithm, showing a good agreement between the two methods. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Underground coal mining will inevitably cause serious ground deformation, and therefore, preventive mining-induced deformation analysis (MIDA) is of great importance in assisting mining planning and decision-making. Current web-based Geographic Information System (webGIS)-based applications usually use 2D GIS data and lack a holistic framework. This study presents a multi-scalar oblique photogrammetry-supported unified 3D webGIS framework for MIDA applications to fill this gap. The developed web platform uses multiple open-source JavaScript libraries, and the prototype system provides user-friendly interfaces for GIS data collecting and corresponding database establishment, geo-visualization and query, dynamic prediction, and spatial overlapping analysis within the same framework. The proposed framework was tested and evaluated in the Qianyingzi mining area in eastern China. The results demonstrated that multi-scalar oblique photogrammetry balances data quality and acquisition efficiency and provides a good source of GIS datasets, and the web-based platform has a good absolute and relative spatial accuracy verified by two types of validation data. Practical application results proved the feasibility and reliability of the system. The developed web-based MIDA prototype system attains an appealing performance and can be easily extended to similar geoscience applications. [ABSTRACT FROM AUTHOR]

Plant protection drones are fast and efficient application machines that are characterised by high application efficiency and no damage to crops. They are particularly suitable for small areas of farmland and mountainous terrain in regions such as Asia and are currently the dominant insecticide application technology in China. The presence of wind is a prerequisite for the spread and dissemination of airborne diseases and it can directly influence the distance and height of ascent of pathogenic spores. This paper investigates the effect of downwash airflow generated by the flight altitude of a plant protection drone on the horizontal distribution, vertical distribution and ground distribution of powdery mildew spores in wheat. Monitoring the changing dynamics of airborne powdery mildew conidia using spore traps. The test results show that: the number of powdery mildew pathogenic spores is related to various factors such as weather, relative humidity and wind speed; the release of spores is greatly influenced by airflow disturbances but has little effect at the early stages of sporulation; the disease is caused by the accumulation process of pathogenic spores and in the control of powdery mildew in wheat, preventive spraying should be carried out within 2–3 days of the germination of pathogenic spores. The study lays the foundation for further in-depth research on the spread of powdery mildew spores and improved pest control, and provides a basis for scientific and rational spraying and control by agricultural drones. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is being used in our daily lives, in all situations and in particular those concerning service systems. However, there is an absence of the ability of the conceptual structure, thematic structure, intellectual structure, and research trends of AI and disruptive technologies in service systems. The main purpose of this study was to carry out a bibliometric analysis of the scientific production of AI and disruptive technologies in service systems based on Elsevier's Scopus database. To do so, keywords were chosen and then data outputs such as the number of published documents, top authors and citations, top journals, countries, and affiliations with the highest number of productions, and network analysis using R-based "biblioshiny" software. The main results showed the growing interest in the subject in the last five years, pointed out current themes and research trends, and revealed the intellectual structure of the field, namely the importance of smart services, cloud computing, and smart sustainable cities. The number of articles for this study reached 1,323, the growth rate has increased in the last five years and the main sources have been reported. China, South Korea and the USA were the leading countries on the subject, and the top 10 authors of influence showed. The word cloud and word growth were presented, as well as the co-citation clusters and co-occurrence network revealed important aspects, and finally the thematic map and the thematic evolution of the subject showed the important concepts. It is hoped that this research will supply future directions for researchers in the area while highlighting the potential of quantitative methods. [ABSTRACT FROM AUTHOR]

Plant protection unmanned aircraft vehicles (UAVs) were developed rapidly in China. The operation performances of different models of UAVs were different. This paper systematically studied droplet deposition distribution; pesticide-mixture utilization rate; operational efficiency; wheat-disease control efficacy; and a comprehensive score of three types of UAVs, a boom sprayer, and a knapsack sprayer. The results showed the descending order of the droplet penetration rate of the pesticide application equipment (PAE) was boom sprayer; UAVs; and knapsack sprayer. The pesticide-mixture utilization rates of the UAVs and boom sprayer were more than 50% while that of the knapsack electric sprayer was only 27.8%. The UAVs' average labor productivity was 5.75 ha per man-hour, which was slightly less than that of the boom sprayer and 21.3 times that of the knapsack sprayer. The control efficacy of each machine on wheat Fusarium head blight was more than 90%. The average performance comprehensive score of the UAVs was 0.812, which was slightly lower than the score of 0.929 for the 3WPZ-700 self-propelled boom sprayer but much higher than the score of 0.399 for the 3WBD-18 knapsack electric sprayer. The results clearly showed the potential of UAVs for improving the pesticide-mixture utilization rate and operational efficiency, as well as the wheat Fusarium head blight control efficacy. [ABSTRACT FROM AUTHOR]

In recent years, the development of airborne magnetic survey technology based on unmanned aerial vehicles (UAVs) has been rapidly advancing. The commonly used systems are the fixed-wing UAV-based, multi-rotors UAV-based, and unmanned helicopters-based magnetic survey systems. And, a type of hybrid UAV that uses a vertical takeoff and landing (VTOL) and fixed-wing cruise mode is increasingly being used to carry airborne magnetic survey systems. To meet the requirements of most UAVs for small-sized and lightweight payloads, a miniature magnetic survey system was developed and integrated into a hybrid fixed-wing UAV and formed an aeromagnetic survey system. And, a peripheral mineral exploration test was conducted in a known porphyry copper–gold deposit in southeastern China using the system. By processing the collected magnetic data with 3D inversion of susceptibilities, potential ore-bearing intrusive rocks were quickly identified and delineated, providing clues for peripheral mineral exploration in the mining area. [ABSTRACT FROM AUTHOR]

Research on the inversion of forest aboveground biomass based on airborne light detection and ranging (LiDAR) data focuses on finding the relationship between the two, such as established linear or nonlinear models. However, these models may have poorer estimation accuracy for tree-components biomass and cannot guarantee the additivity of each component. Therefore, we aimed to develop an error-in-variable biomass model system that ensures both the compatibility of the individual tree component biomass with the diameter at breast height and the additivity of component biomass. The system we developed used the airborne LiDAR data and field-measured data of principis-rupprechtii (Larix gmelinii var.) trees, collected from north China. Our model system not only ensured the additivity of nonlinear biomass models, it also accounted for the impact of measurement errors. We first selected the airborne LiDAR-derived variable with the highest contribution to the biomass of each component and then developed an inversion model system with that variable as an independent variable and with the biomass of each component as the dependent variable using allometric functions. Moreover, two model estimation methods, two-stage error (TSEM) and nonlinear seemingly unrelated regression (NSUR) with one-step, two-step, and summation methods, were also applied, and their performances were compared. The results showed that both NSUR-one-step and TSEM-one-step led to similar parameter estimates and performance for a system, and the fitting accuracy of a model system was not very attractive. The variance function included in a model system reduced the heteroscedasticity effectively and improved the model accuracy. Overall, this study successfully combined the error-in-variable modeling with the airborne LiDAR data, proposed methods that can be used for the extension of component biomass from an individual tree to a stand and that might improve the estimation accuracy of carbon storage. A compatible model system can be further improved if various sources of error in the variables are identified, and their impacts on the system are effectively accounted for. [ABSTRACT FROM AUTHOR]

Food security is a key target in the UN Sustainable Development Goals (SDGs) and is also one of the biggest challenges for China, the largest developing country in population in the world. Massive attention has been directed to the future impacts of hydrometeorological extremes on crop yield. However, knowledge gaps still stand concerning the effectiveness of irrigation, as the largest water consumption sector, on agricultural production under different climate scenarios. Here we showed the drought based on the modified Palmer Drought Severity Index and analyzed the drought-induced wheat yield losses in irrigated and non-irrigated agriculture across China according to three methods including the Multiple Linear Regression method, Deep Learning algorithm, and Erosion-Productivity Impact Calculator model. We found that the droughts become more intensive in the future, and drought-induced wheat yield loss under RCP8.5 scenario was expected to reach 32–49%. Intercomparison of drought-induced wheat yield changes between irrigated and non-irrigated agriculture indicated significantly less drought-induced crop-yield losses given sufficient irrigation under the RCP2.6 and RCP6.0 scenarios. However, our results under RCP8.5 suggested that the effectiveness of irrigation in enhancing food security is minor under this high-emission future climate scenario. These findings allowed us to revisit the effectiveness of irrigation in a warming climate and highlighted the importance of climate change mitigation in food security. [ABSTRACT FROM AUTHOR]

Based on the CH-3 and WH-110A unmanned aerial vehicle (UAV) platforms, we independently developed aeromagnetic systems for fixed-wing UAVs (FUAV) and modified unmanned helicopters (MUH), respectively. These systems overcome key technological challenges in system integration, aeromagnetic compensation, and electromagnetic (EM) compatibility. We conducted a 1:100,000 aeromagnetic test using both systems in a tidal flat area in Jiangsu province, China. Both systems successfully completed 240 line km measurement lines and collected high-quality data with magnetic compensation accuracies of 0.01428 nT and 0.04690 nT, respectively. The dynamic noise was below 0.14 nT, accounting for 95.72% and 100% of the measurements. These results indicate that both systems offer high measurement accuracy, efficiency, low cost, convenience, and flexibility. We compared the two aeromagnetic systems based on their system parameters, integration modes, magnetic compensation methods and effects, and practical applications. By comprehensively analyzing their characteristics and application fields, we provide guidance for UAV-based aeromagnetic surveys in mineral exploration, basic geological survey and other related fields. And the FUAV and MUH aeromagnetic systems presented in this paper serve as a valuable reference for future research in this area. [ABSTRACT FROM AUTHOR]

Mining of mineral resources exposes various minerals to oxidizing environments, especially sulfide minerals, which are decomposed by water after oxidation and make the water in the mine area acidic. Acid mine drainage (AMD) from mining can pollute surrounding rivers and lakes, causing serious ecological problems. Compared with traditional field surveys, unmanned aerial vehicle (UAV) technology has advantages in terms of real-time imagery, security, and image accuracy. UAV technology can compensate for the shortcomings of traditional technology in mine environmental surveys and effectively improve the implementat ion efficiency of the work. UAV technology has gradually become one of the important ways of mine environmental monitoring. In this study, a UAV aerial photography system equipped with a Red, Green, Blue (RGB) camera collected very-high-resolution images of the stone coal mining area in Ziyang County, northwest China, and classified the very-high-resolution images by support vector machine (SVM), random forest (RF), and U-Net methods, and detected the distribution of five types of land cover, including AMD, roof, water, vegetation, and bare land. Finally, the accuracy of the recognition results was evaluated based on the land-cover map using the confusion matrix. The recognition accuracy of AMD using the U-Net method is significantly better than that of SVM and RF traditional machine-learning methods. The results showed that a UAV aerial photography system equipped with an RGB camera and the depth neural network algorithm could be combined for the competent detection of mine environmental problems. [ABSTRACT FROM AUTHOR]

To make appropriate decisions in the evaluation phase of the exterior design of subway trains, an optimal selection method was proposed based on multi-level gray relational analysis. The exterior design factors of subway trains were analyzed to construct an index system for design evaluation. The significance of each index was compared through an analytic hierarchy process. The correlation coefficient of each index in the plan was calculated through gray relational analysis to obtain the weighted correlation degree of each design scheme. The optimal selection of the exterior design of Guangzhou Metro Line 6 in China was considered as an example. Four types of subjects were recruited: professional designers, students majoring in design, subway train design experts, and subway passengers in Guangzhou. The weight of each index in the evaluation system was calculated using questionnaire scoring. Virtual simulation software was applied to evaluate the human factors related to each scheme. The indices in each plan were then scored to calculate the correlation coefficient and the overall correlation degree; and finally, the optimal selection was obtained. The results showed that it was practical to evaluate and optimize the exterior design of subway trains based on multi-level gray relational analysis. In the evaluation index system, the weights of technology, human factors, aesthetics, and culture were 0.517, 0.297, 0.099, and 0.087, respectively, which showed that technology had the greatest impact on the system, while human factors, aesthetics, and culture were useful complements. Our results showed that Design Scheme 1 was unsuitable as an optimization scheme due to the high escape window. Meanwhile, Design Scheme 2 was optimal overall, from a technical perspective. Design Scheme 3 was the best in terms of the escape window index (a human factor). Design Schemes 3 and 4 were optimally assessed from aesthetic and cultural perspectives. This study is conducive to the optimization of the exterior design of subway trains, can be used to inform design iteration, and provides a reference for the optimal selection of design schemes for other urban rail trains. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Pesticide Science / Nongyaoxue Xuebao is the property of Chinese Journal of Pesticide Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

It remains challenging to control Tomicus spp., a pest with fast spreading capability, leading to the death of large numbers of Pinus yunnanensis (Franch.) and posing a severe threat to ecological security in southwest China. Therefore, it is crucial to effectively and accurately monitor the damage degree for Pinus yunnanensis attacked by Tomicus spp. at large geographical scales. Airborne hyperspectral remote sensing is an effective, accurate means to detect forest pests and diseases. In this study, we propose an innovative and precise classification framework to monitor the damage degree of Pinus yunnanensis infected by Tomicus spp. using hyperspectral UAV (unmanned aerial vehicle) imagery with machine learning algorithms. First, we revealed the hyperspectral characteristics of Pinus yunnanensis from a UAV-based hyperspectral platform. We obtained 22 vegetation indices (VIs), 4 principal components, and 16 continuous wavelet transform (CWT) features as the damage degree sensitive features. We classified the damage degree of Pinus yunnanensis canopies infected by Tomicus spp. via three methods, i.e., discriminant analysis (DA), support vector machine (SVM), and backpropagation (BP) neural network. The results showed that the damage degree detected from the BP neural network, combined with 16 CWT features, achieved the best performance (training accuracy: 94.05%; validation accuracy: 94.44%). [ABSTRACT FROM AUTHOR]

Battery-powered multi-rotor UAVs (Unmanned Aerial Vehicles) have been employed as chemical applicators in agriculture for small fields in China. Major challenges in spraying include reducing the influence of environmental factors and appropriate chemical use. Therefore, the objective of this research was to obtain the law of droplet drift and deposition by CFD (Computational Fluid Dynamics), a universal method to solve the fluid problem using a discretization mathematical method. DPM (Discrete Phase Model) was taken to simulate the motion of droplet particles since it is an appropriate way to simulate discrete phase in flow field and can track particle trajectory. The figure of deposition concentration and trace of droplet drift was obtained by controlling the variables of wind speed, pressure, and spray height. The droplet drifting models influenced by different factors were established by least square method after analysis of drift quantity to get the equation of drift quantity and safe distance. The relationship model, Yi(m), between three dependent variables, wind speed Xw(m s−1), pressure Xp(MPa) and spray height Xh(m), are listed as follows: The edge drift distance model was Y1 = 0.887Xw + 0.550Xp + 1.552Xh − 3.906 and the correlation coefficient (R2) was 0.837; the center drift distance model was Y2 = 0.167Xw + 0.085Xp + 0.308Xh − 0.667 and the correlation coefficient (R2) was 0.774; the overlap width model was Y3 = 0.692xw + 0.529xp + 1.469xh − 3.374 and the correlation coefficient (R2) was 0.795. For the three models, the coefficients of the three variables were all positive, indicating that the three factors were all positively correlated with edge drift distance, center drift distance, and overlap width. The results of this study can provide theoretical support for improving the spray quality of UAV and reducing the drift of droplets. [ABSTRACT FROM AUTHOR]

Air-assisted sprayers are the mainstream orchard plant protection machinery in China. During the usage of sprayers, the pesticide droplets carried by strong air jets from sprayers enter into the target canopy. Therefore, the distribution of airflow field in the canopy has significant influence on the spatial movement of the droplets and the adhesion and penetration of the droplets inside the canopy. To enhance the working performance of sprayers, it is imperative to study their use in tree canopies. Based on computational fluid dynamics (CFD), the k-ε turbulence model, and the SIMPLE algorithm, a 3D simulated model of the spatial distribution of the airflow field in and around the tree canopy was established based on the porous model in this paper. The model was used to simulate and calculate the air field distribution of an air-assisted orchard sprayer under different operating parameters. The results showed that the optimal operation effect was achieved when the driving speed and the air speed of the fan outlet were 1 m/s and 20 m/s, respectively, while the air speed in the canopy was not less than 2 m/s. The 36 points measured in the canopy were compared with the simulated results through field experiments. It showed that average relative error between the measured and simulated values was 13.85%, and the overall goodness-of-fit was 0.97656. The model accurately simulated the airflow distribution in the canopy and provided a basis for optimizing the operating parameters of the air-assisted sprayers in orchards. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In aeromagnetic measurement, accurate compensation for the interference magnetic field generated by the aircraft platform due to the aircraft maneuvering in the Earth's magnetic field is an important prerequisite for the accurate identification of the magnetic anomaly signal of the detection target. The flaws of the traditional calibration flight scheme in aeromagnetic interference compensation are firstly analyzed, and then an improved scheme is proposed, featuring smaller calibration flight areas, more simplified maneuvers, shorter flight route and less influence from the magnetometer's direction and extreme weather. The improved scheme can enhance the robustness of the aeromagnetic interference compensation matrix and improve the compensation efficiency, and thus both the solved magnetic compensation coefficients and compensation effects are significantly improved. The experimental results of the aeromagnetic interference compensation in an area of Inner Mongolia of China show that the average accuracy of the repeated survey lines, which are compensated by the improved scheme, can be increased by 5 and 3 nT, respectively, compared with the uncompensated results and the results compensated by the traditional scheme. Therefore, the effectiveness and superiority of the improved calibration flight scheme is fully proved. Plain Language Summary: Aeromagnetic measurement technology is the most economical and effective technical means to obtain high‐precision and high‐resolution geomagnetic information. Because the aircraft used in aeromagnetic measurement is composed of ferromagnetic materials, it will produce an interference magnetic field when maneuvering in the Earth's magnetic field. In order to obtain pure geomagnetic field measurement data, it is necessary to compensate the interference magnetic field. The traditional calibration flight scheme is widely used in the aeromagnetic interference compensation, and has played an important role in the existing aeromagnetic measurement. However, with the continuous improvement of the measurement accuracy of airborne magnetometers, there are higher requirements for calibration, and some defects of the traditional calibration flight scheme are found in practice. Hence, an improved calibration flight scheme is proposed in this paper, which features smaller calibration area, shorter flight route, simplified maneuvers and less influence from the direction of the magnetometer. The experimental results show that the modified scheme can improve the average accuracy of repeated survey lines by 3 nT compared with the traditional one. Therefore, the improved scheme can be directly applied in the aeromagnetic interference compensation of scalar, vector and gradient magnetic measurement of manned and unmanned aerial vehicle (UAV). Key Points: An improved calibration flight scheme is proposed in the aeromagnetic interference compensationEffectiveness and superiority of the improved calibration flight scheme are validated by actual flight dataCompared with the traditional scheme, the improved one can increase the average accuracy of repeated lines by 3 nT [ABSTRACT FROM AUTHOR]

The rapid urbanization in China is accompanied by increasingly serious air pollution. Particulate matter and ozone are the main air pollutants, and the study of their vertical distribution and correlation plays an important role in the synergistic air pollution control. In this study, we performed Lidar- and UAV-based observations in spring in Nanjing, China. The average concentrations of surface ozone and PM2.5 during the observation period are 87.78 µg m−3 and 43.48 µg m−3, respectively. Vertically, ozone reaches a maximum in the upper boundary layer, while the aerosol extinction coefficient decreases with height. Generally, ozone and aerosol are negatively correlated below 650 m. The correlation coefficient increases with altitude and reaches a maximum of 0.379 at 1875 m. Within the boundary layer, ozone and aerosols are negatively correlated on days with particulate pollution (PM2.5 > 35 μg m−3), while on clean days they are positively correlated. Above the boundary layer, the correlation coefficient is usually positive, regardless of the presence of particulate pollution. The UAV study compensates for Lidar detections below 500 m. We found that ozone concentration is higher in the upper layers than in the near-surface layers, and that ozone depletion is faster in the near-surface layers after sunset. [ABSTRACT FROM AUTHOR]

Regarded as a marked category of global forests, forest plantations not only have great significance for the development of the global economy, but also contribute ecological and social benefits. The accurate acquisition of the multi-scale (from individual tree to landscape level) and near-real-time information of structural parameters in plantations is the premise of decision-making in sustainable management for the whole forest farm, and it is also the basis for the evaluation of forest productivity in stands. The development and synergetic applications of multi-source and multi-platform remote sensing technology provide a technical basis for the highly accurate estimation of multi-scale forest structural parameters. In this study, we developed an advanced framework for estimating these parameters of forest plantations in multiple scales (individual tree, plot and landscape levels) based on the Unmanned Aircraft System Light Detection and Ranging (UAS-LiDAR) transects and wall-to-wall Sentinel-2 imagery, combined with the sample plot data in a typical forest farm plantation (mainly Larch, Chinese pine) of Northern China. The position and height of individual trees within the plots were extracted by the LiDAR-based point cloud segmentation (PCS) algorithm, and then different approaches to the extrapolation of forest structural parameters from the plot to landscape level were assessed. The results demonstrate that, firstly, the individual tree height obtained by PCS was of relatively high accuracy (rRMSE = 1.5–3.3%); secondly, the accuracy of the forest structure parameters of the sample plot scale estimated by UAS-LiDAR is rRMSE = 4.4–10.6%; and thirdly, the accuracy of the two-stage upscaling approach by UAS-LiDAR transects as an intermediate stage (rRMSE = 14.5–20.2%) performed better than the direct usage of Sentinel-2 data (rRMSE = 22.9–27.3%). This study demonstrated an advanced framework for creating datasets of multi-scale forest structural parameters in a forest plantation, and proved that the synergetic usage of UAS-LiDAR transects and full coverage medium-resolution satellite imagery can provide a high-precision and low-cost technical basis for the multi-level estimation of forest structural parameters. [ABSTRACT FROM AUTHOR]

Agricultural unmanned aerial vehicles (UAVs), which are a new type of fertilizer application technology, have been rapidly developed internationally. This study combines the agronomic characteristics of rice fertilization with weighted coefficient learning-modified single-neuron adaptive proportional–integral–differential (PID) control technology to study and design an aerial real-time variable fertilizer application control system that is suitable for rice field operations in northern China. The nitrogen deficiency at the target plot is obtained from a map based on a fertilizer prescription map, and the amount of fertilizer is calculated by a variable fertilizer application algorithm. The advantages and disadvantages of the two control algorithms are analyzed by a MATLAB simulation in an indoor test, which is integrated into the spreading system to test the effect of actual spreading. A three-factor, three-level orthogonal test of fertilizer-spreading performance is designed for an outdoor test, and the coefficient of variation of particle distribution Cv (a) as well as the relative error of fertilizer application λ (b) are the evaluation indices. The spreading performance of the spreading system is the best and can effectively achieve accurate variable fertilizer application when the baffle opening is 4%, spreading disc speed is 600 r/min, and flight height is 2 m, with a and b of evaluation indexes of 11.98% and 7.02%, respectively. The control error of the spreading volume is 7.30%, and the monitoring error of the speed measurement module is less than 30 r/min. The results show that the centrifugal variable fertilizer spreader improves the uniformity of fertilizer spreading and the accuracy of fertilizer application, which enhances the spreading performance of the centrifugal variable fertilizer spreader. [ABSTRACT FROM AUTHOR]

Accurate estimation and extrapolation of forest structural parameters in planted forests are essential for monitoring forest resources, investigating their ecosystem services (e.g., forest structure and functions), as well as supporting decisions for precision silviculture. Advances in unmanned aerial vehicle (UAV)-borne Light Detection and Ranging (LiDAR) technology have enhanced our ability to precisely characterize the 3-D structure of the forest canopy with high flexibility, usually within forest plots and stands. For wall-to-wall forest structure mapping in broader landscapes, samples (transects) of UAV-LiDAR datasets are a cost-efficient solution as an intermediate layer for extrapolation from field plots to full-coverage multispectral satellite imageries. In this study, an advanced two-stage extrapolation approach was established to estimate and map large area forest structural parameters (i.e., mean DBH, dominant height, volume, and stem density), in synergy with field plots and UAV-LiDAR and GF-6 satellite imagery, in a typical planted forest of southern China. First, estimation models were built and used to extrapolate field plots to UAV-LiDAR transects; then, the maps of UAV-LiDAR transects were extrapolated to the whole study area using the wall-to-wall grid indices that were calculated from GF-6 satellite imagery. By comparing with direct prediction models that were fitted by field plots and GF-6-derived spectral indices, the results indicated that the two-stage extrapolation models (R2 = 0.64–0.85, rRMSE = 7.49–26.85%) obtained higher accuracy than direct prediction models (R2 = 0.58–0.75, rRMSE = 21.31–38.43%). In addition, the effect of UAV-LiDAR point density and sampling intensity for estimation accuracy was studied by sensitivity analysis as well. The results showed a stable level of accuracy for approximately 10% of point density (34 pts·m−2) and 20% of sampling intensity. To understand the error propagation through the extrapolation procedure, a modified U-statistics uncertainty analysis was proposed to characterize pixel-level estimates of uncertainty and the results demonstrated that the uncertainty was 0.75 cm for mean DBH, 1.23 m for dominant height, 14.77 m3·ha−1 for volume and 102.72 n·ha−1 for stem density, respectively. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Pesticide Science / Nongyaoxue Xuebao is the property of Chinese Journal of Pesticide Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Accelerating the development of agricultural aviation technology is the need of China's modern agricultural construction. With the rise of emerging industries such as artificial intelligence, biotechnology, autonomous navigation, and the Internet of Things, agricultural aviation is further developing toward the direction of intelligence to meet the requirements of efficient and sophisticated agricultural aviation operations. Bionics is a multi-discipline and comprehensive border subject. It is produced by the mutual penetration and integration of life science and engineering science. Bionic technology has received more and more attention in recent years, and breakthroughs have been made in the fields of biomedicine and health, military, brain science and brain-like navigation, and advanced manufacturing. This study summarized the research progress of biomimetic technology in the field of agricultural aviation from three aspects of biological perception, biological behavior, and biological intelligence. On this basis, problems of related research and application of agricultural aircraft in real-time obstacle avoidance, path planning, and intelligent navigation were analyzed. Combined with the practice of the rapid development of agricultural aircraft, research and application of bionic technology suitable for agricultural aircraft were then proposed. Finally, prospects of agricultural aero-bionic technology were also discussed from multiple bionic target fusion, three-dimensional spatial information exploration, sensors, and animal brain system mechanism. This review provides a reference for the development of bionic technology in China's agricultural aviation. [ABSTRACT FROM AUTHOR]

Aerial electrostatic spray technology for agriculture is the integration of precision agricultural aviation and electrostatic spray technology. It is one of the research topics that have been paid close attention to by scholars in the field of agricultural aviation. This study summarizes the development of airborne electrostatic spray technology for agricultural use in China, including the early research and exploration of Chinese institutions and researchers in the aspects of nozzle structure design optimization and theoretical simulation. The research progress of UAV-based aerial electrostatic spray technology for agricultural use in China was expounded from the aspects of nozzle modification, technical feasibility study, influencing mechanism of various factors, and field efficiency tests. According to the current development of agricultural UAVs and the characteristics of the farmland environment in China, the UAV-based aerial electrostatic spray technology, which carries the airborne electrostatic spray system on the plant protection UAVs, has a wide potential in the future. At present, the application of UAV-based aerial electrostatic spray technology has yet to be further improved due to several factors, such as the optimization of the test technology for charged droplets, the impact of UAV rotor wind field, comparison study on charging modes, and the lack of technical accumulation in the research of aerial electrostatic spray technology. With the continuous improvement of the research system of agricultural aviation electrostatic spray technology, UAV-based electrostatic spray technology will give play to the advantages in increasing the droplets deposition on the target and reducing environmental pollution from the application of pesticides. This study is capable of providing a reference for the development of the UAV-based agricultural electrostatic spray technology and the spray equipment. [ABSTRACT FROM AUTHOR]

As a new type of crop protection machinery, the Crop Protection Unmanned Aerial System (CPUAS) has developed rapidly and been widely used in China; currently, how to use the CPUAS scientifically has become a top priority. However, the relationships between the operating parameters of the CPUAS and the effective spraying width (ESW), droplet distribution characteristics, and control effects of insect pests and diseases are not clear yet. Therefore, three levels of flight speed (FS) as 3, 4, and 5 m/s, three levels of flight height (FH) as 1.5, 2.0, and 2.5 m, and spraying volume 2.0 L/min experiments were carried out to investigate the effects of FS and FH on the ESW, droplet deposition uniformity (DDU), and droplet penetration rate (DPR) by using an electric single-rotor CPUAS CE20. Based on the obtained results, combined with the insect pests and diseases occurrence agronomic laws, the optimal operation parameters of the CPUAS were selected to control the wheat aphids, powdery mildew, and head blight. The results showed that the ESW of CE20 was not consistent, the maximum value was 5.78 m, and the minimum one was 2.51 m. The FS had a highly significant impact on ESW (p = 0.0033 < 0.01), while the FH and the interaction between FS and FH had no significant impact on ESW. The coefficients of variation (CV) of the droplet deposition were between 23.3% and 34.4%, which meant good deposition uniformity. The FH (p = 0.0019) and the interaction between FS and FH (p = 0.02) had significant impacts on the DDU. The control effects on aphids were 78.71% (1 day), 84.88% (3 days), and 90.42% (7 days), the control effects on powdery mildew were 77.17% (7 days) and 82.83% (14 days), and the control effect on head blight was 88.32% (20 days). This study proved that by the optimization of parameters and the combination of agronomy, good control effects for insect pests and diseases could be achieved by the CPUAS. The research results would provide some technical supports for CPUAS application. [ABSTRACT FROM AUTHOR]

The Zhuxi tungsten deposit in Jiangxi Province, South China, contains a total W reserve of about 2.86 Mt at an average grade of 0.54 wt% WO3, representing the largest W deposit in the world. Numerous studies on the metallogeny of the deposit have included its timing, the ore‐controlling structures and sedimentary host rocks and their implications for mineral exploration. However, the deep nappe structural style of Taqian–Fuchun metallogenic belt that hosts the W deposit, and the spatial shape and scale of deeply concealed intrusions and their sedimentary host rocks are still poorly defined, which seriously restricts the discovery of new deposits at depth and in surrounding areas of the W deposit. Modern 3D geological modeling is an important tool for the exploration of concealed orebodies, especially in brownfield environments. There are obvious density contrast and weak magnetic contrast in the ore‐controlling strata and granite at the periphery of the deposit, which lays a physical foundation for solving the 3D spatial problems of the ore‐controlling geological body in the deep part of the study area through gravity and magnetic modeling. Gravity data (1:50000) and aeromagnetic data (1:50000) from the latest geophysical surveys of 2016–2018 have been used, firstly, to carry out a potential field separation to obtain residual anomalies for gravity and magnetic interactive inversion. Then, on the basis of the analysis of the relationship between physical properties and lithology, under the constraints of surface geology and borehole data, human–computer interactive gravity and magnetic inversion for 18 cross‐sections were completed. Finally, the 3D geological model of the Zhuxi tungsten deposit and its periphery have been established through these 18 sections, and the spatial shape of the intrusions and strata with a depth of 5 km underground were obtained, initially realizing "transparency" for ore‐controlling bodies. According the analysis of the geophysical, geochemical, and geological characteristics of the Zhuxi tungsten deposit, we discern three principles for prospecting and prediction in the research area, and propose five new exploration targets in its periphery. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Quantitative estimation of rill erosion research plays a significant role in the understanding of rill formation and their development mechanisms, which is lacking presently. In this paper, rill erosion is quantified to analyze and evaluate the spatial and temporal distribution in typical gully heads of the Loess Plateau of China. Although several studies have carried rill erosion quantification, the variability analysis of rill erosion rates at different slope position is limited primarily because of the unavailability of high resolution elevation models. Using the low-altitude photography with Unmanned Aerial Vehicles (UAVs), digital surface models (DSMs) with centimeter accuracy were generated, and then geometrical parameters of a total of 1,129 rills at tableland-slope (T-S), hillslope (S), and slopes affected by artificial vegetation (SV) in the study were counted. Then, spatial and temporal development as well as erosion rates of the rills at the three sites were compared. Although many studies revealed the erosion law at the S position, few studies have linked the development of rills at the T-S position, and artificial afforestation at the SV position exacerbates the rill erosion. Furthermore, based on the centimeter-resolution DSMs obtained by the two-stage UAV photography, we found that the slope gradient which was the most susceptible to rill erosion were 5-10°, 35-50°, and 65-80° at T-S, S and SV sites, respectively. At the SV, rill incision was the most sensitive to slope changes, and rill incision potential proved to be the greatest. Generally, the higher the rill erosion depth, the smaller the frequency of occurrence, but this trend was mitigated at the SV position. Therefore, urgent action is needed to control rill erosion caused by artificial afforestation on hillslopes to alleviate and eliminate the adverse effects of vegetation planting on rill erosion on the Loess Plateau of China. [ABSTRACT FROM AUTHOR]

On 15 March 2019, a fatal deep-seated landslide occurred at the village of Zaoling in Xiangning County of Shanxi Province, China. Extending to an area of about 120 m by 85 m, with an estimated displaced mass volume of 72,000 m3, the landslide left 20 people dead, 13 injured, and 8 buildings destroyed. There were no precursory signals prior to the event, and usual triggering mechanisms for a landslide were absent. Investigation conducted immediately after the incident revealed that the landslide was initiated in a 1.0 to 1.5-m thick-softened layer located at 40 m depth along the contact between the loess and interbedded paleosol layer. This softened layer was highly saturated due to the perched water on top of the relatively impervious paleosol layer and became a critical weak zone since the shear strength of loess is very sensitive to water content. We suggest that the perched water originated from extensive long-term unsaturated seepage of rainwater and local rapid percolation along preferential channels such as sinkholes and root network. The Zaoling landslide confirms that unlike most landslides in non-loess areas, loess landslides can occur without identifiable triggering events. They can result from gradual build up of instability due to slow (in the span of hundred years) accumulation of deep soil water. Based on the lessons learned from this landslide event, suggestions are given for the planning of urban and rural development in loess areas. Due to the fact that the process leading to the development of such a landslide is largely concealed, further research should be aimed at gaining a more thorough understanding of the mechanism of this landslide type. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Pesticide Science / Nongyaoxue Xuebao is the property of Chinese Journal of Pesticide Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Since goaf water can cause water inrush, collapse or other severe geological hazards in coal mining, its detection has become a significant issue. As the grounded electrical source airborne transient electromagnetic (GREATEM) system can provide considerable prospecting depth, lateral resolution, and high detection efficiency, the method may be suitable for goaf water detection. To verify the feasibility, a field electromagnetic survey over Qinshui coal mine (Shanxi province, China) was conducted, and the system was used to detect the geoelectric characteristics of goaf water. After data acquisition, data processing, and apparent resistivity calculation, the resistivity profile of survey area is clearly presented, which is consistent with the information provided by Shanxi Coal Geology Geophysical Surveying Exploration Institute, China. The result shows that the application of GREATEM system is an effective technique for resistivity detection of goaf water, and can reduce the risks in coal mining. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)