Analysing slope dynamics of Kaleköy (Türkiye) dam reservoir with Sentinel-1 SAR time series and Sentinel-2 spectral indices DOI
Beste Tavus, Sultan Kocaman, Hakan A. Nefeslioğlu

и другие.

Environmental Earth Sciences, Год журнала: 2024, Номер 83(17)

Опубликована: Авг. 27, 2024

Язык: Английский

Dynamic landslide susceptibility mapping over last three decades to uncover variations in landslide causation in subtropical urban mountainous areas DOI
Peifeng Ma, Li Chen, Chang Yeon Yu

и другие.

Remote Sensing of Environment, Год журнала: 2025, Номер 326, С. 114800 - 114800

Опубликована: Май 16, 2025

Язык: Английский

Процитировано

1
Experimental and numerical investigations of bending mechanical properties and fracture characteristics of cemented tailings-waste rock backfill under three-point bending DOI
Tong Gao, Aixiang Wu, Shaoyong Wang

и другие.

Construction and Building Materials, Год журнала: 2024, Номер 447, С. 138149 - 138149

Опубликована: Авг. 31, 2024

Язык: Английский

Процитировано

5
A new InSAR-based framework for assessing tailings dam failure risks: With the robust separation of consolidation settlements DOI Creative Commons
Zefa Yang, Xiangyu Huang, Jingze Li

и другие.

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2025, Номер 140, С. 104602 - 104602

Опубликована: Май 22, 2025

Язык: Английский

Процитировано

0
Interpretable PCA and SVM-Based Leak Detection Algorithm for Identifying Water Leakage Using SAR-Derived Moisture Content and InSAR Closure Phase DOI Creative Commons
Yan Yan,

Xujie Le,

Taoli Yang

и другие.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Год журнала: 2024, Номер 17, С. 15136 - 15147

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

2
Using Advanced InSAR Techniques and Machine Learning in Google Earth Engine (GEE) to Monitor Regional Black Soil Erosion—A Case Study of Yanshou County, Heilongjiang Province, Northeastern China DOI Creative Commons

Yanchen Gao,

Jiahui Yang, Xiaoyu Chen

и другие.

Remote Sensing, Год журнала: 2024, Номер 16(20), С. 3842 - 3842

Опубликована: Окт. 16, 2024

The black soil region experiences complex erosion due to natural processes and intense human activities, leading degradation adverse ecological agricultural impacts. However, the complexities involved in quantifying regional poses remarkable challenges accurately assessing current status of for effective conservation. To solve this issue, we proposed a new method monitoring using Interferometric synthetic aperture radar (InSAR) technology machine learning algorithms within Google Earth Engine platform. not only enables regional-scale monitoring, but also ensures high accuracy measurement (millimeter-level). susceptibility study area (Yanshou County, Heilongjiang Province, Northeastern China) was classified random forest refine monitored predicted erosion. results indicate that five-year (2016–2021) deformation Yanshou County −11.08 mm, with significant mean cumulative −8.08 mm yr−1 occurring 2017. driving factor analysis shows subject compound effect water freeze–thaw erosion, closely related crop phenological stages. indicates 73.3% susceptible higher probability river areas, at altitudes, on steep slopes. good vegetation cover can reduce risk some extent. This offers perspective China. holds potential future expansion monitor larger thereby guiding strategies development protection agriculturally important soil.

Язык: Английский

Процитировано

2
Energy damage evolution and mesoscopic failure mechanism of cemented waste rock tailing backfill under axial compression DOI
Tianyu Zhu, Zhonghui Chen, Zhongyu Wang

и другие.

Structures, Год журнала: 2024, Номер 71, С. 108057 - 108057

Опубликована: Дек. 16, 2024

Язык: Английский

Процитировано

2
Enhanced Tailings Dam Beach Line Indicator Observation and Stability Numerical Analysis: An Approach Integrating UAV Photogrammetry and CNNs DOI Creative Commons
Kun Wang, Zheng Zhang,

Xiuzhi Yang

и другие.

Remote Sensing, Год журнала: 2024, Номер 16(17), С. 3264 - 3264

Опубликована: Сен. 3, 2024

Tailings ponds are recognized as significant sources of potential man-made debris flow and major environmental disasters. Recent frequent tailings dam failures growing trends in fine outputs underscore the critical need for innovative monitoring safety management techniques. Here, we propose an approach that integrates UAV photogrammetry with convolutional neural networks (CNNs) to extract beach line indicators (BLIs) conduct enhanced evaluations. The significance real 3D geometry construction numerical analysis is investigated. results demonstrate optimized You Only Look At CoefficienTs (YOLACT) model outperforms recognizing boundary line, achieving a mean Intersection over Union (mIoU) 72.63% Pixel Accuracy (mPA) 76.2%. This shows promise future integration autonomously charging UAVs, enabling comprehensive coverage automated BLIs. Additionally, anti-slide seepage stability evaluations impacted by shape water condition configuration. proposed provides more conservative calculations, suggesting simplified 2D modeling may underestimate stability, potentially affecting designs regulatory decisions. Multiple methods suggested cross-validation. crucial balancing regulations economic feasibility, helping prevent excessive unsustainable burdens on enterprises advancing towards goal zero harm people environment management.

Язык: Английский

Процитировано

1
Analysing slope dynamics of Kaleköy (Türkiye) dam reservoir with Sentinel-1 SAR time series and Sentinel-2 spectral indices DOI
Beste Tavus, Sultan Kocaman, Hakan A. Nefeslioğlu

и другие.

Environmental Earth Sciences, Год журнала: 2024, Номер 83(17)

Опубликована: Авг. 27, 2024

Язык: Английский

Процитировано

0