Meijun Jin
Biographic Data
| ID | 7904271 |
|---|---|
| NAME | Meijun Jin |
| GIVEN NAMES | Meijun |
| FAMILY NAME | Jin |
| SIGNATURE | JIN M |
| AFFILIATIONS | Taiyuan University of Technology |
| VERIFIED | No |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Villager emergency evacuation behavior in disaster response via rural on-site drill in plateau area
Integrating X‐Ray Computed Tomography and Hydraulic Properties for Soil Quality Assessment Under Soil Compaction
Soil compaction poses a significant threat to soil quality and sustainability, necessitating advanced assessment methods. We hypothesized that incorporating x‐ray computed tomography (XCT)‐derived pore characteristics with hydraulic properties would significantly enhance the development of a soil quality index (SQI) under soil compaction. Ninety soil samples were collected from the surface layer (0–20 cm) of five sites representing varying soil t…
Exploring Spatial Influence of Remotely Sensed PM2.5 Concentration Using a Developed Deep Convolutional Neural Network Model
Currently, more and more remotely sensed data are being accumulated, and the spatial analysis methods for remotely sensed data, especially big data, are desiderating innovation. A deep convolutional network (CNN) model is proposed in this paper for exploiting the spatial influence feature in remotely sensed data. The method was applied in investigating the magnitude of the spatial influence of four factors-population, gross domestic product (GDP)…
Spatiotemporal Variability of Remotely Sensed PM2.5 Concentrations in China from 1998 to 2014 Based on a Bayesian Hierarchy Model
With the rapid industrial development and urbanization in China over the past three decades, PM2.5 pollution has become a severe environmental problem that threatens public health. Due to its unbalanced development and intrinsic topography features, the distribution of PM2.5 concentrations over China is spatially heterogeneous. In this study, we explore the spatiotemporal variations of PM2.5 pollution in China and four great urban areas from 1998…
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Spatiotemporal Variability of Remotely Sensed PM2.5 Concentrations in China from 1998 to 2014 Based on a Bayesian Hierarchy Model
With the rapid industrial development and urbanization in China over the past three decades, PM2.5 pollution has become a severe environmental problem that threatens public health. Due to its unbalanced development and intrinsic topography features, the distribution of PM2.5 concentrations over China is spatially heterogeneous. In this study, we explore the spatiotemporal variations of PM2.5 pollution in China and four great urban areas from 1998…
Exploring Spatial Influence of Remotely Sensed PM2.5 Concentration Using a Developed Deep Convolutional Neural Network Model
Currently, more and more remotely sensed data are being accumulated, and the spatial analysis methods for remotely sensed data, especially big data, are desiderating innovation. A deep convolutional network (CNN) model is proposed in this paper for exploiting the spatial influence feature in remotely sensed data. The method was applied in investigating the magnitude of the spatial influence of four factors-population, gross domestic product (GDP)…
Villager emergency evacuation behavior in disaster response via rural on-site drill in plateau area
Integrating X‐Ray Computed Tomography and Hydraulic Properties for Soil Quality Assessment Under Soil Compaction
Soil compaction poses a significant threat to soil quality and sustainability, necessitating advanced assessment methods. We hypothesized that incorporating x‐ray computed tomography (XCT)‐derived pore characteristics with hydraulic properties would significantly enhance the development of a soil quality index (SQI) under soil compaction. Ninety soil samples were collected from the surface layer (0–20 cm) of five sites representing varying soil t…
Air Quality and Health Impacts (2 works) · Environmental Science (2 works) · Geography (2 works) · Mathematics (2 works) · Population (2 works) · Statistics (2 works) · Urban Transport and Accessibility (2 works) · Air Quality Monitoring and Forecasting (1 work) · Artificial Intelligence (1 work) · Beijing (1 work)