Monitoring the Subsidence in Wan’an Town of Deyang Based on PS-InSAR Technology (Sichuan, China) DOI Open Access
Hongyi Guo, Antonio Miguel Martínez Graña, José Ángel González Delgado

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(22), P. 10010 - 10010

Published: Nov. 16, 2024

In recent years, land subsidence has become a crucial factor affecting urban safety and sustainable development, especially in Wan’an Town. To accurately monitor analyze the Town, this study uses PS-InSAR technique combined with an improved DEM for detailed research on PS-InSAR, or Permanent Scatterer Interferometric SAR, is suitable high-precision monitoring of surface deformation. The natural neighbor interpolation method optimizes data, improving its spatial resolution accuracy. study, multiple periods SAR imagery data Town were collected preprocessed through radiometric calibration, phase unwrapping, other steps. Using technique, information permanent scatterers (PS points) was extracted to establish deformation model preliminarily Concurrently, optimized using enhance Finally, analysis results indicate that by have higher accuracy resolution, providing more accurate reflection topographical features found provided Town’s features. By combining from 2016 2024 calculated. area showed varying degrees subsidence, rates ranging 6 mm/year 10 mm/year. Four characteristic areas analyzed causes influencing factors. findings contribute understanding guiding planning, support geological disaster warning prevention.

Language: Английский

Deformation Slope Extraction and Influencing Factor Analysis Using LT-1 Satellite Data: A Case Study of Chongqing and Surrounding Areas, China DOI Creative Commons
Jielin Liu, Chong Xu,

Binbin Zhao

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(1), P. 156 - 156

Published: Jan. 5, 2025

The use of satellite imagery for surface deformation monitoring has been steadily increasing. However, the study extracting slopes from data requires further advancement. This limitation not only poses challenges subsequent studies but also restricts potential deeper exploration and utilization data. LT-1 satellite, China’s largest L-band synthetic aperture radar offers a new perspective monitoring. In this study, we extracted in Chongqing its surrounding areas China based on generated by LT-1. Twelve factors were selected to analyze their influence slope deformation, including elevation, topographic position, slope, landcover, soil, lithology, relief, average rainfall intensity, distances rivers, roads, railways, active faults. A total 5863 identified, covering an area 140 km2, mainly concentrated central part area, with highest density reaching 0.22%. Among these factors, intensity was found have greatest impact slope. These findings provide valuable information geological disaster early warning management areas, while demonstrating practical value

Language: Английский

Citations

2
Regional Research Intensity and ESG Indicators in Italy: Insights from Panel Data Models and Machine Learning DOI

Costantiello Alberto,

Carlo Drago,

Massimo Arnone

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Integrated machine learning models for enhancing tropical rainfall prediction using NASA POWER meteorological data DOI Creative Commons
Azlan Saleh, Mou Leong Tan,

Zaher Mundher Yaseen

et al.

Journal of Water and Climate Change, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 22, 2024

ABSTRACT This research evaluates the performance of deep learning (DL) models in predicting rainfall George Town, Penang, utilizing open-source NASA POWER meteorological data, which includes variables such as rainfall, dew point, solar radiation, wind speed, relative humidity, and temperature. study introduces a newly developed hybrid DL based on integration 2D convolutional neural network (CNN2D) with bidirectional recurrent (BRNN) gated unit (BGRU). The proposed models, CNN2D–BGRU BRNN–BGRU, were compared against standalone CNN2D, BRNN, BGRU. results indicate that BRNN–BGRU model is most effective, root mean square error (RMSE) value 2.59, absolute (MAE) 1.97, Pearson correlation coefficient (PCC) 0.79, Willmott index (WI) 0.88. In 3-day prediction, also performed best, test WI 0.83, PCC 0.69, RMSE 3.02, MAE 2.34. consistently excels multi-step tropical regions using dataset. These findings can contribute to development advanced rainfall-predicting systems for more effective management water resources flooding urban areas.

Language: Английский

Citations

1
Multi-scale monitoring and safety assessment of a prefabricated subway station integrating space-borne InSAR, ground-based machine vision and internal-distributed fiber optic sensors DOI Creative Commons
Chengyu Hong, Jinyang Zhang, Yaxuan Zhang

et al.

International Journal of Digital Earth, Journal Year: 2024, Volume and Issue: 17(1)

Published: Dec. 15, 2024

Safety monitoring of prefabricated subway stations is essential for early detection potential damages to mitigate major accidents. This study developed an integrated multi-scale safety assessment and strategy a station by combining space-borne synthetic aperture radar interferometry (InSAR), ground-based machine vision, internal-distributed fiber optic sensing (DFOS) technologies. Compared the traditional single-data-source-monitoring method, proposed space-ground-internal integration designed monitor subaway stations. includes mm level ground subsidence, submm structural surface deformation, microstrain internal strain field. Taking Shapu Station in Shenzhen as research site, spatiotemporal evolution land underground settlement convergence well changes were monitored. Then, data fusion methodology InSAR, DFOS measurements was presented effective station. The results indicated that deformation occurred during backfill period, dangerous assembly ring increased (the seventh at lowest level) when section completed.

Language: Английский

Citations

1
Monitoring the Subsidence in Wan’an Town of Deyang Based on PS-InSAR Technology (Sichuan, China) DOI Open Access
Hongyi Guo, Antonio Miguel Martínez Graña, José Ángel González Delgado

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(22), P. 10010 - 10010

Published: Nov. 16, 2024

In recent years, land subsidence has become a crucial factor affecting urban safety and sustainable development, especially in Wan’an Town. To accurately monitor analyze the Town, this study uses PS-InSAR technique combined with an improved DEM for detailed research on PS-InSAR, or Permanent Scatterer Interferometric SAR, is suitable high-precision monitoring of surface deformation. The natural neighbor interpolation method optimizes data, improving its spatial resolution accuracy. study, multiple periods SAR imagery data Town were collected preprocessed through radiometric calibration, phase unwrapping, other steps. Using technique, information permanent scatterers (PS points) was extracted to establish deformation model preliminarily Concurrently, optimized using enhance Finally, analysis results indicate that by have higher accuracy resolution, providing more accurate reflection topographical features found provided Town’s features. By combining from 2016 2024 calculated. area showed varying degrees subsidence, rates ranging 6 mm/year 10 mm/year. Four characteristic areas analyzed causes influencing factors. findings contribute understanding guiding planning, support geological disaster warning prevention.

Language: Английский

Citations

0