Spatial Density Distribution Research Articles

Fishery Resource Evaluation with Hydroacoustic and Remote Sensing in Yangjiang Coastal Waters in Summer

Yangjiang coastal waters provide vital spawning grounds, feeding grounds, and nursery areas for many commercial fish species. It is important to understand the spatial distribution of fish for the management, development, and protection of fishery resources. In this study, an acoustic survey was conducted from 29 July to 5 June 2021. Meanwhile, remote sensing data were collected, including sea surface temperature (SST), chlorophyll concentration (Chla), sea surface salinity (SSS), and sea surface temperature anomaly (SSTA). The spatial distribution of density and biomass of fish was analyzed based on acoustic survey data using the geostatistical method. Combining with remote sensing data, we explored the relation between fish density and the environment based on the GAMs model. The results showed that fish are mainly small individuals. The horizontal distri-bution of fish density had a characteristic of high nearshore and low offshore. In the vertical direc-tion, fish are mainly distributed in surface-middle layers in shallow waters (<10 m) and in middle-bottom layers in deeper waters (>10 m), respectively. The deviance explained in the optimal GAM model was 59.2%. SST, Chla, SSS, and longitude were significant factors influencing fish density distribu-tion with a contribution of 35.3%, 11.8%, 6.5%, and 5.6%, respectively. This study can pro-vide a scientific foundation and data support for rational developing and protecting fishery re-sources in Yangjiang coastal waters.

Spatial quantization of exciton-polariton condensates in optically induced traps

We study the formation of exciton-polariton condensates in potlike traps created by optical pumping in a planar microcavity with embedded quantum wells. The trap is formed by a repulsive reservoir of incoherent excitons excited by a ring-shaped nonresonant laser beam. Polariton condensates confined in a trapping potential are subject to spatial confinement leading to energy quantization. We reveal experimentally the discrete spectrum of polariton eigenstates in an optical trap that can be characterized by a pair of quantum numbers, azimuthal and radial quantum numbers, that correspond to the number of nodes of a condensate wave function in the corresponding directions. The occupation numbers of the eigenstates of a polariton condensate are determined by the overlap integral of the condensate wave function and the exciton reservoir spatial density distribution. The nonresonant pumping scheme enables engineering the shape and size of the trap, that allows to selectively excite specific superpositions of the eigenstates of a polariton condensate in each experiment. We demonstrate both single- and multiple-mode polariton lasing in an optical trap.

Correlation of mineral density and elastic modulus of dog dentin using μ-CT and nanoindentation

This study sought to 1) investigate the spatial distribution of mineral density of dog dentin using µ-CT and 2) characterize the relationship between the elastic modulus and mineral density of dog dentin using nanoindentation and µ-CT. Maxillary canine teeth of 10 mature dogs were scanned with a µ-CT then sectioned in the transverse and vertical planes and tested using nanoindentation. Spatial distribution of mineral density and elastic modulus was quantified. Results demonstrated significant spatial variation in mineral density and elastic modulus. Mineral density and elastic modulus generally increased from the dentin-pulp interface to the dentino-enamel junction and from the crown base to the crown tip. Significant site dependent correlations between mineral density and elastic modulus were determined (0.021 > R2 > 0.408). The results of this study suggest that while mineral density is a mediator of elastic modulus, other mediators such as collagen content may contribute to the mechanical behavior of dog dentin.

Three-dimensional ordering of water molecules reflecting hydroxyl groups on sapphire (001) and α-quartz (100) surfaces.

Water molecules on oxide surfaces influence the chemical reactivity and molecular adsorption behavior of oxides. Herein, three-dimensional atomic force microscopy (3D-AFM) and molecular dynamics simulations are used to visualize the surface hydroxyl (OH) groups and their hydration structures on sapphire (001) and α-quartz (100) surfaces at the atomic-scale. The obtained results revealed that the spatial density distributions and hydrogen-bonding strengths of surface OH groups affect their local hydration structures. In particular, the force curves obtained by 3D-AFM suggest that the hydration forces of water molecules intensify at sites where water molecules strongly interact with the surface OH groups. The insights obtained in this study deepen our understanding of the affinities of Al2O3 and SiO2 for water molecules and contribute to the use of 3D-AFM in the investigation of atomic-scale hydration structures on various surfaces, thereby benefiting a wide range of research fields dealing with solid-liquid interfaces.

INFLUENCE MECHANISM OF STAGNATION-POINT FLOW ON LIQUID-PHASE SPRAY PENETRATION LENGTH UNDER ENGINE-LIKE CONDITIONS

Formulation of liquid-phase spray penetration length (LPL) is one of the basic research works of direct injection (DI) engines. To predict the spray evolution and LPL in the limited space more accurately, the diffused background-illumination extinction imaging (DBI) technology and highspeed schlieren method were employed to detect the liquid- and vapor-phase spray development in a constant volume combustion chamber (CVCC). The experimental results show that the LPL of the impinging spray is significantly smaller than that of the free spray when the LPL is close to the impinging distance. When the LPL is much smaller than the impinging distance, the LPL of impinging spray is the same as that of free spray. Furthermore, based on the CFD simulation and the stagnation-point flow theory, the spatial distribution of velocity, pressure, and density at the near-wall surface was analyzed in detail. Due to part of the spray kinetic energy was converted into potential energy, creating a sharp increase in pressure and density near the stagnation point, which suppressed the movement of fuel droplets, resulting in a significantly smaller LPL. Moreover, a novel LPL prediction model is introduced, which considering the inhibiting effect of wall on spray penetration and demonstrates enhanced predictive capability of experimental results.

Bringing ultimate depth to scanning tunnelling microscopy: deep subsurface vision of buried nano-objects in metals.

A method for subsurface visualization and characterization of hidden subsurface nano-structures based on scanning tunelling microscopy/spectroscopy (STM/STS) has been developed. Nano-objects buried under a metal surface up to several tens of nanometers can be visualized through the metal surface and characterized with STM without destroying the sample. This non-destructive method exploits quantum well (QW) states formed by partial electron confinement between the surface and buried nano-objects. The specificity of STM allows for nano-objects to be singled out and easily accessed. Their burial depth can be determined by analysing the oscillatory behaviour of the electron density at the surface of the sample, while the spatial distribution of electron density can give additional information about their size and shape. The proof of concept was demonstrated with different materials such as Cu, Fe, and W in which the nanoclusters of Ar, H, Fe and Co were buried. For each material, the maximal depth of subsurface visualisation is determined by the material parameters and ranges from several nanometers to several tens of nanometers. To demonstrate the ultimate depth of subsurface STM-vision as the principal limit of our approach, the system of Ar nanoclusters embedded into a single-crystalline Cu(110) matrix has been chosen since it represents the best combination of the mean free path, smooth interface and inner electron focusing. With this system we experimentally demonstrated that Ar nanoclusters of several nanometers large buried as deep as 80 nm can still be detected, characterized and imaged. The ultimate depth of this ability is estimated to be 110 nm. This approach using QW states paves the way for enhanced 3D characterization of nanostructures hidden well below a metallic surface.

Early amygdala and ERC atrophy linked to 3D reconstruction of rostral neurofibrillary tau tangle pathology in Alzheimer’s disease

Previous research has emphasized the unique impact of Alzheimer’s Disease (AD) pathology on the medial temporal lobe (MTL), a reflection that tau pathology is particularly striking in the entorhinal and transentorhinal cortex (ERC, TEC) early in the course of disease. However, other brain regions are affected by AD pathology during its early phases. Here, we use longitudinal diffeomorphometry to measure the atrophy rate from MRI of the amygdala compared with that in the ERC and TEC in cognitively unimpaired (CU) controls, CU individuals who progressed to mild cognitive impairment (MCI), and individuals with MCI who progressed to dementia of the AD type (DAT), using a dataset from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Our results show significantly higher atrophy rates of the amygdala in both groups of ‘converters’ (CU→MCI, MCI→DAT) compared to controls, with rates of volume loss comparable to rates of thickness loss in the ERC and TEC. We localize atrophy within the amygdala within each of these groups using fixed effects modeling. Controlling for the familywise error rate highlights the medial regions of the amygdala as those with significantly higher atrophy in both groups of converters than in controls. Using our recently developed method, referred to as Projective LDDMM, we map measures of neurofibrillary tau tangles (NFTs) from digital pathology to MRI atlases and reconstruct dense 3D spatial distributions of NFT density within regions of the MTL. The distribution of NFTs is consistent with the spatial distribution of MR measured atrophy rates, revealing high densities (and atrophy) in the amygdala (particularly medial), ERC, and rostral third of the MTL. The similarity of the location of NFTs in AD and shape changes in a well-defined clinical population suggests that amygdalar atrophy rate, as measured through MRI may be a viable biomarker for AD.

黄河源园区高寒草地碳储量估算及其影响因素

PDF HTML阅读 XML下载 导出引用 引用提醒 黄河源园区高寒草地碳储量估算及其影响因素 DOI: 10.5846/stxb202207152024 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 2021年度全国草原资源调查项目(DD20211601);国家自然科学基金项目(41371125) Estimated carbon storage and influencing factors of alpine grassland in the source region of the Yellow River Author: Affiliation: Fund Project: The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:高寒草地碳储量及其影响因素研究是认识青藏高原草地生态系统乃至陆地生态系统碳循环和气候变化的关键之一。利用2021年8月上旬地面调查数据与同期高分6号遥感数据建立回归关系,在反演研究区植被地上、地下生物量碳密度和0-40cm土壤层有机碳密度基础上,估算了黄河源园区高寒草地有机碳储量,并通过路径分析探讨了土壤理化性质对碳密度的影响驱动机制。结果表明:(1)2021年黄河源园区地上生物量、地下生物量、0-40cm土壤层碳密度分别为37.65g/m2、1305.28g/m2、4769.11g/m2;总碳储量为100.44Tg(1Tg=1012g),植被层和土壤层碳储量分别分为22.06Tg、78.38Tg,占总碳密度的21.96%、78.04%。(2)黄河源园区高寒草甸和高寒草原两种草地类型地上生物量碳密度分别为41.27g/m2、30.76g/m2;地下生物量碳密度分别为1661.41g/m2、618.74g/m2;0-40cm土壤层有机碳密度分别为5790.99g/m2、2804.04g/m2;研究区碳密度总体呈现南高北低的空间分布现状,分布格局与地表植被类型分布特点较为吻合;(3)路径分析表明,研究区土壤理化性质与草地碳密度关系密切,其中地上生物量碳密度主要受土壤全磷含量和土壤含水率驱动,地下生物量碳密度主要受土壤全氮含量和容重驱动,土壤有机碳密度主要受地下生物量碳密度、土壤容重和pH值驱动。 Abstract:The study of alpine grassland carbon storage and its influencing factors is one of the keys to understand the carbon cycle and climate change of grassland ecosystem and even terrestrial ecosystem on the Qinghai Tibet Plateau. In this paper, the regression relationship between the ground survey data in early August 2021 and the remote sensing data of Gaofen-6 in the same period was established. Based on the inversion of the above-ground and below-ground biomass carbon density of vegetation and the organic carbon density of 0-40 cm soil layer in the study area, the organic carbon storage of alpine grassland in the source region of the Yellow River was estimated, and the driving mechanism of the impact of soil physical and chemical properties on carbon density was discussed through path analysis. The results showed that: (1) In 2021, the above-ground biomass, below-ground biomass and carbon density of 0-40 cm soil layer in the source region of the Yellow River were 37.65 g/m2, 1305.28 g/m2 and 4769.11 g/m2, respectively. The total carbon storage was 100.44 Tg (1 Tg=1012 g). The carbon storage of vegetation layer and soil layer was 22.06 Tg and 78.38 Tg, accounting for 21.96% and 78.04% of the total carbon density respectively. (2) The above-ground biomass carbon density of alpine meadow and alpine steppe in the source region of the Yellow River was 41.27 g/m2 and 30.76 g/m2 respectively; The below-ground biomass carbon density was 1661.41 g/m2 and 618.74 g/m2 respectively; The organic carbon density of 0-40 cm soil layer was 5790.99 g/m2 and 2804.04 g/m2 respectively; The spatial distribution of carbon density in the study area was generally high in the south and low in the north, and the distribution pattern was consistent with the distribution characteristics of surface vegetation types. (3) Path analysis showed that the physical and chemical properties of soil in the study area were closely related to the carbon density of grassland. The above-ground biomass carbon density was mainly driven by soil total phosphorus content and soil moisture, the below-ground biomass carbon density was mainly driven by soil total nitrogen content and soil bulk, and the soil organic carbon density was mainly driven by the below-ground biomass carbon density, soil bulk and pH. 参考文献 相似文献 引证文献

Оцінка радіоекологічної ситуації для території природного заповідника «Древлянський» станом на 2023 р.

Technological methods for preparing geospatial data for assessing the radioecological situation and visualizing the results using geographic information system (GIS) software packages are presented in the article. The current levels of soil l37Cs contamination density within the grid of forest quarters of the reserve are given. The article emphasizes that the current levels of radiation contamination in the reserve have an irregular distribution. In this work, the procedure for data preparation was developed and technological methods were tested to assess the current state of the radioactively contaminated territory by forest quarters. The interpolation method was used to eliminate unevenness in the mapping layer of the source data. Radioecological zoning of the territory based on the density of soil contamination with l37Cs for 2023 was carried out to determine the suitability of the territory for the implementation of forest protection measures. Critical areas that generate hazardous levels of dose load for the employees of the Reserve were identified on the maps. The spatial distribution of forest fallout density was calculated. The spatial distribution of radiation contamination of timber and flammable fuel material within the forest quarters of the reserve was estimated. The analysis of the current radioecological situation for the territory of the Drevlians Reserve showed the effectiveness of using modern ArcGIS and MapInfo software packages. Such software combines the following capabilities: preparation of information matrices for calculations and interpolation, in case of limited input data, grouping and classification by values, formation of thematic data sets for storage and further display of results on map schemes.

THE USE OF HARD AND SOFT BALL MODELS FOR LATTICE DISTORTION EVALUATION IN B2 HIGH-ENTROPY SHAPE MEMORY ALLOYS

The applicability of two most common approaches to distortion evaluation in high-entropy shape memory alloys with B2 structure was discussed. The distortion was calculated for a two-component TiNi alloy and six-component Ti-Hf-Zr-Ni-Cu-Co alloys of different chemical composition using the hard and soft ball models. Both models were shown to be inapplicable for calculating lattice distortion because they predict a high distortion value even for two-component Ti49Ni51 alloy. The very high distortion values obtained for all alloys indicate that the alloys would have to form only an amorphous structure. However, this is inconsistent with experimental studies, showing that all the studied alloys crystallize from the melt with the formation of the B2 phase. A modification of the considered models is proposed, taking into account that the TiNi alloy is a chemical compound (intermetallic compound) formed with a change in the spatial distribution of electron density around the nuclei of interacting atoms and, as a consequence, a change in the atomic sizes. The proposed approach gives the distortion values that are consistent with the previously established criteria for crystal structure stability for alloys with a less than 5% content of additional components.

ADDPC-SMOTE: An Oversampling Algorithm Based on Density Difference Peak Clustering and Spatial Distribution Entropy

ADDPC-SMOTE: An Oversampling Algorithm Based on Density Difference Peak Clustering and Spatial Distribution Entropy

Two-dimensional fluid simulation of spatial distribution of dust particles in a capacitively coupled silane plasma

In this work, we develop a two-dimensional fluid model to study the spatial density distributions of dust particles in a radio frequency capacitively coupled silane plasma. Unlike those scenarios based on the one-dimensional fluid model, in this work, the nonuniformity of the radial density distributions of dust particles is attributed mainly to the radial components of the electric field force and the ion drag force acting on the dust particles, leading to the two local density peaks near the electrode edges. It seems that dust particles tend to overcome the support of the electric field force and move much closer to the electrodes, as one of the density peaks indicates. Moreover, with the decrease of the radii of the discharge electrodes or the distance between them, the radial component of the ion drag force is enhanced, resulting in more dust particles gathering near the electrode edge region, and forming a ring-shaped particle density distribution. In the case of the discharge electrodes wrapped with dielectric materials, the uniformity of the radial density distributions of dust particles between the two electrodes is improved. Finally, the vortex motion of a single dust particle near the electrode edge region is also simulated in this work.

Hidden-nucleons neural-network quantum states for the nuclear many-body problem

Understanding how protons and neutrons self-organize to form atomic nuclei requires solving the nuclear many-body Schr\"odinger equation. This work addresses this nontrivial task through a neural network quantum states ansatz that involves additional ``hidden'' degrees of freedom to improve the accuracy of the solution systemically. Light and medium-mass nuclei's energy and spatial density distributions are in excellent agreement with those obtained utilizing exact-diagonalization and diffusion Monte Carlo approaches.

Tunable valley filtering in dynamically strained α−T3 lattices

Mechanical deformations in $\alpha$-$\mathcal{T}_3$ lattices induce local pseudomagnetic fields of opposite directionality for different valleys. When this strain is equipped with a dynamical drive, it generates a complementary valley-asymmetric pseudoelectric field which is expected to accelerate electrons. We propose that by combining these effects by a time-dependent nonuniform strain, tunable valley filtering devices can be engineered that extend beyond the static capabilities. We demonstrate this by implementing an oscillating Gaussian bump centered in a four-terminal Hall bar $\alpha$-$\mathcal{T}_3$ setup and calculating the induced pseudoelectromagnetic fields analytically. Within a recursive Floquet Green-function scheme, we determine the time-averaged transmission and valley polarization, as well as the spatial distributions of the local density of states and current density. As a result of the periodic drive, we detect novel energy regimes with highly valley-polarized transmission, depending on $\alpha$. Analyzing the spatial profiles of the time-averaged local density of states and current density we can relate these regimes to the pseudoelectromagnetic fields in the setup.By means of the driving frequency, we can manipulate the valley-polarized states, which might be advantageous for future device applications.

Multi-scale characteristics of the spatial distribution of space charge density that determines the vertical electric field during dust storms

Multi-scale characteristics of the spatial distribution of space charge density that determines the vertical electric field during dust storms

Interpretation of Radio Wave Scintillation Observed through LOFAR Radio Telescopes

Abstract Radio waves propagating through a medium containing irregularities in the spatial distribution of the electron density develop fluctuations in their intensities and phases. In the case of radio waves emitted from astronomical objects, they propagate through electron density irregularities in the interstellar medium, the interplanetary medium, and Earth’s ionosphere. The LOFAR radio telescope, with stations across Europe, can measure intensity across the VHF radio band and thus intensity scintillation on the signals received from compact astronomical objects. Modeling intensity scintillation allows the estimate of various parameters of the propagation medium, for example, its drift velocity and its turbulent power spectrum. However, these estimates are based on the assumptions of ergodicity of the observed intensity fluctuations and, typically, of weak scattering. A case study of single-station LOFAR observations of the strong astronomical source Cassiopeia A in the VHF range is utilized to illustrate deviations from ergodicity, as well as the presence of both weak and strong scattering. Here it is demonstrated how these aspects can lead to misleading estimates of the propagation medium properties, for example, in the solar wind. This analysis provides a method to model errors in these estimates, which can be used in the characterization of both the interplanetary medium and Earth’s ionosphere. Although the discussion is limited to the case of the interplanetary medium and Earth’s ionosphere, its ideas are also applicable to the case of the interstellar medium.

Effects of Planting Density on Root Spatial and Temporal Distribution and Yield of Winter Wheat

The root system is the only vital organ for plants to connect with soil moisture and nutrients and obtain feedback information. This research aimed to explore the response of different spike type winter wheat varieties to plant and row spacing configurations. Multi-spike and large-spike winter wheat varieties were used as materials. By setting different plant row configurations and planting densities, the spatial and temporal distribution of root length density, root diameter, root dry weight density, and the main control factors of root growth and development of winter wheat during the whole growth period were studied. The results showed that the root system was the most widely distributed and the root diameter was the largest in the 0–40 cm soil depth, with an average root system diameter of more than 0.5 mm. The root length density and root diameter peaked at the heading stage, decreased at the maturity stage, and the root dry weight density peaked at the jointing stage. The jointing stage and heading stage are the most vigorous periods of root growth in winter wheat, when the center of gravity of root growth in winter wheat is gradually moving down. Therefore, the rapid growth and elongation time of a root system can be effectively prolonged at the jointing stage and heading stage, and the root growth rate can be improved. Promoting root thickening can effectively meet the needs for water and nutrients, for the formation and filling of aboveground plants and grains, in the later stage, which is conducive to the formation of aboveground dry matter production and final yield. The root distribution was greatest in the 0–60 cm soil depth, accounting for 95.13–97.84% of the total root length. After the heading stage occurs, the upper roots begin to decline in large quantities. Thus, the jointing stage and heading stage require fertilization and other farmland management operations to increase root nutrients for the ground parts and dry matter accumulation to provide sufficient nutrients so that the number of effective panicles, grain weight, and the number of spike grains coordinate to achieve the highest grain yield. Results showed that the highest yield can be achieved with the planting pattern X2M1. A comprehensive analysis showed that the genetic characteristics of winter wheat varieties were different, and there were some differences in the correlation between wheat yield and root system at the different growth stages. The correlation between the root parameters and yield of multi-spike winter wheat during the overwintering-jointing stage was obvious. For large-spike type winter wheat in the jointing stage, the yield correlation is most obvious.

Characteristics of Soil Organic Carbon in Croplands and Affecting Factors in Hubei Province

SOC storage (SOCS) plays a vital role in global climate change. Understanding the spatial pattern and features of soil organic carbon (SOC) and its influencing factors is important for increasing SOC fixation. However, few studies exist on the organic carbon reserves of farmland on a regional scale. This study revealed the SOCD and SOCS values and distribution using Hubei Province as a sampling region. The results demonstrated that the spatial distributions of farmland system carbon storage and density were uneven, and the spatial heterogeneity was related to geography, cultivated area, and soil type. The SOCD ranged from 0.559 to 10.613 kg/m2, with an average of 3.3710 ± 0.0337 kg/m2, and the soil carbon reserve of the farmland system was ~17.81 Tg. The SOCD varied with topography and soil type: in mountainous cultivated land, it was generally higher than that in hilly land and in the plains. However, the plain cultivated areas contained the highest carbon reserves. Within the farmland system, paddy soil, the dominant soil type, exhibited higher SOCD and larger SOC storage capacity. Soil types with the same physicochemical properties exhibited different organic carbon storage capacity in different geomorphic and regional environments. Specifically, paddy soil was found to have higher SOCD and SOCS than the other soil types, and its soil carbon storage capacity was high; the SOC reserves of wheat-rice tillage were the largest among the main tillage methods. Boosting the soil carbon sink requires fundamental improvement in soil properties by improving soil texture, using conservation tillage to increase soil organic matter, and reducing unnecessary human interference.

Improving the Accuracy of Estimating Forest Carbon Density Using the Tree Species Classification Method

The accurate and effective estimation of forest carbon density is an essential basis for effectively responding to climate change and achieving the goal of carbon neutrality. Aiming at the problem of the significant differences in the forest carbon model parameters of different tree species, this study used the tree forest in Yueyang City, Hunan Province, China, as the study object and used the random forest classification algorithm through the Google Earth Engine platform to classify the dominant tree species within the forested range of the study area based on the image elements. The overall accuracy in the forest/non-forest classification (primary classification) was 93.79% with a Kappa of 0.9145. The overall accuracy in the dominant species classification (secondary classification) was 87.30% with a Kappa of 0.7747. Based on the classification, a multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) were constructed for different dominant tree species by combining some Forest Resource Inventory data and remote sensing data. The results showed that the RF model had a significantly higher coefficient of determination (R2 = 0.4054–0.7602) than the MLR (R2 = 0.0900–0.4070) and SVM (R2 = 0.1650–0.4450) as well as a substantially lower RMSE and MAE; its spatial distribution of forest carbon density ranged from 3.06 to 62.80 t·hm−2. Compared with the spatial distribution of the forest carbon density (4.64 to 31.96 t·hm−2) without the classification of dominant species, the method eliminated the problems of severe overfitting and significant underestimation of peak values when estimating under unclassified conditions. The method provides a reference for the remote sensing inversion of forest carbon density on a large scale.

Development of Digital Device Using ZigBee for Environmental Monitoring in Underground Mines

In underground mines, various mining activities may generate dust or vibrations, affecting workers’ health and safety. Therefore, for worker safety, we must monitor the environment and identify possible risks. However, it is difficult to install multiple sensors and acquire data simultaneously because of the difficulties of connecting to an external network in underground mines. This study developed a digital device to share acquired data by combining ZigBee communication technology with an accelerometer and dust sensor. In total, 29 vibration modules, 14 dust modules, and 2 coordinator modules were installed at Taeyoung EMC’s Samdo Mine in Samcheok, Republic of Korea. Because of its application, we could detect changes in vibration and dust before and after blasting. The dust density of the devices close to the blasting point increases rapidly up to about 230 µg/m3 and then decreases to about 180 µg/m3, and the dust density of the devices further increases over time. The dust density was usually maintained at a value of about 100 to 150 µg/m3 before blasting. The spatial distribution of the dust density of multiple devices was visualized using ArcGIS Pro. Although the wireless sensor network is well-established, some modules were temporarily disconnected from the network. In order to solve the problem of unstable network connection in some modules, change of network settings and line of sight analysis are required. Improvements in the technology developed in this study may help prevent potential hazards in underground mines.