绘制历史滑坡活动的地图,使用基于Swin变压器的转移学习方法.
Fei Chen1, Zhihua Liang2, Zhengyuan Cheng2
1School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China.
Sensors (Basel, Switzerland)
|January 10, 2026
概括
这项研究引入了一种先进的模型,用于创建历史滑坡库存,这对于理解地质影响至关重要. 开发的方法有效地在十年内绘制了山体滑坡的地图,有助于区域稳定性分析.
科学领域:
- 地质科学 地质科学
- 遥感 遥感 遥感 遥感
- 人工智能的人工智能
背景情况:
- 历史上的山体滑坡库存对于分析山体滑坡模式和地质影响至关重要.
- 历史滑坡测绘的高效技术尚不发达,导致全球库存稀缺.
- 现有的山体滑坡检测方法对于全面的历史绘图缺乏效率.
研究的目的:
- 开发一个先进的山体滑坡检测模型,以高效地绘制历史的山体滑坡地图.
- 为了重建温川地震影响地区十年规模的山体滑坡库存.
- 评估模型的性能和滑坡的时空活动.
主要方法:
- 开发了一个Swin变压器架构,与金字塔分割注意力机制集成,用于地震检测.
- 雇员网络微调用于跨领域的适应.
- 应用该模型来重建温川地震地区十年的山体滑坡库存.
主要成果:
- 与最先进的模型相比,拟议的模型展示了优越的时间转移映射性能.
- 重建的历史滑坡地图表现出高度准确和完整.
- 滑坡活动在2008年至2021年之间普遍稳定,受高度,斜率和角度的影响.
结论:
- 开发的方法有效地重建了历史的山体滑坡库存,对时空空间分析有价值.
- 调查结果为区域稳定性分析和生态环境恢复提供了关键的见解.
- 该研究支持在城市规划和基础设施投资方面做出明智决策.
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