Comprehensive framework for the integration and analysis of geo-environmental data for urban geohazards

Zhang, Xinyu; Zhang, Junqiang; Liu, Gang; Tian, Yuan; Sun, Yongzheng; Xu, Lirui; Wang, Song

doi:10.1007/s12145-021-00642-1

Cited by 3 publications

(2 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The problem of urban surface deformation is a common problem in today's world, which seriously threatens the basic buildings of the city and our personal safety [1][2][3]. The causes of urban surface deformation include human factors and natural factors [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Urban Surface Deformation Management: Assessing Dangerous Subsidence Areas through Regional Surface Deformation, Natural Factors, and Human Activities

Chen

et al. 2022

Sustainability

View full text Add to dashboard Cite

Geological disasters caused by surface deformation are common, especially in urban areas, which seriously impede urbanization’s sustainable development. Monitoring and analysis with high spatial and temporal resolution are particularly important to assess the risk of geological disasters caused by urban deformation. This study uses Sentinel-1A satellite imagery to obtain the surface deformation time series of Nanchang City based on SBAS-InSAR and PS-InSAR techniques and is combined with wavelet period analysis and gray correlation analysis to determine the correlation between deformation area and climate environment. This study shows that there was a large-scale subsidence trend in the central urban area of Nanchang in those two years, and an uplift trend in the agro-ecological areas in the southeast. A periodic analysis further shows that the areas with larger changes in surface deformation are more affected by changes in precipitation. This study, integrated with external data, examines the possibility of subsidence disasters occurring along subway lines in areas with large deformation magnitudes from multiple angles.

show abstract

Section: Introductionmentioning

confidence: 99%

Urban Surface Deformation Management: Assessing Dangerous Subsidence Areas through Regional Surface Deformation, Natural Factors, and Human Activities

Chen

et al. 2022

Sustainability

View full text Add to dashboard Cite

show abstract

“…Early research utilized behavioral data and discovered that an auditory stimulus influences the reaction time (RT) of a synchronous or nearly synchronous visual stimulus (Mcdonald et al, 2000;Shams et al, 2000;Laura et al, 2005;Zhang X. et al, 2022) and the reverse is also true (Platt and Warren, 1972;Bertelson, 1999). These results indicate that a simultaneous or near-simultaneous bimodal stimulus reduces stimulation uncertainty (Calvert et al, 2000), potentially supporting the early integration framework or enhancing stimulation response for the late framework (Stein et al, 1989;Zhang et al, 2021). However, external factors, such as the state of the experimental subjects, may be overlooked.…”

Section: Introductionmentioning

confidence: 99%

The effects of attention in auditory–visual integration revealed by time-varying networks

Jiang

Shi

et al. 2023

Front. Neurosci.

View full text Add to dashboard Cite

Attention and audiovisual integration are crucial subjects in the field of brain information processing. A large number of previous studies have sought to determine the relationship between them through specific experiments, but failed to reach a unified conclusion. The reported studies explored the relationship through the frameworks of early, late, and parallel integration, though network analysis has been employed sparingly. In this study, we employed time-varying network analysis, which offers a comprehensive and dynamic insight into cognitive processing, to explore the relationship between attention and auditory-visual integration. The combination of high spatial resolution functional magnetic resonance imaging (fMRI) and high temporal resolution electroencephalography (EEG) was used. Firstly, a generalized linear model (GLM) was employed to find the task-related fMRI activations, which was selected as regions of interesting (ROIs) for nodes of time-varying network. Then the electrical activity of the auditory-visual cortex was estimated via the normalized minimum norm estimation (MNE) source localization method. Finally, the time-varying network was constructed using the adaptive directed transfer function (ADTF) technology. Notably, Task-related fMRI activations were mainly observed in the bilateral temporoparietal junction (TPJ), superior temporal gyrus (STG), primary visual and auditory areas. And the time-varying network analysis revealed that V1/A1↔STG occurred before TPJ↔STG. Therefore, the results supported the theory that auditory-visual integration occurred before attention, aligning with the early integration framework.

show abstract

Escape routes and safe points in natural hazards. A case study for soil

Karpouza,

Skilodimou,

Kaviris

et al. 2024

Engineering Geology

View full text Add to dashboard Cite

Comprehensive framework for the integration and analysis of geo-environmental data for urban geohazards

Cited by 3 publications

References 27 publications

Urban Surface Deformation Management: Assessing Dangerous Subsidence Areas through Regional Surface Deformation, Natural Factors, and Human Activities

Urban Surface Deformation Management: Assessing Dangerous Subsidence Areas through Regional Surface Deformation, Natural Factors, and Human Activities

The effects of attention in auditory–visual integration revealed by time-varying networks

Escape routes and safe points in natural hazards. A case study for soil

Contact Info

Product

Resources

About