利用机器学习算法根据 PSI 时间序列预测地表运动

IF 3 3区地球科学 Q2 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY

International Journal of Remote Sensing Pub Date : 2024-03-27 DOI:10.1080/01431161.2024.2331977

Nur Yagmur, G. Taskin, N. Musaoglu, E. Erten

引用次数: 0

摘要

地表移动是一个关键问题，需要及时检测和监测，以确保安全。为解决这一问题，对表面变形的检测和连续监测已成为一项重要的技术。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Forecasting surface movements based on PSI time series using machine learning algorithms

Surface movements pose a critical issue requiring prompt detection and monitoring to ensure safety. To address this concern, the detection and continuous monitoring of surface deformations have gai...

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来源期刊

International Journal of Remote Sensing 工程技术-成像科学与照相技术

CiteScore

7.00

自引率

5.90%

发文量

219

审稿时长

4.8 months

期刊介绍： The International Journal of Remote Sensing ( IJRS) is concerned with the theory, science and technology of remote sensing and novel applications of remotely sensed data. The journal’s focus includes remote sensing of the atmosphere, biosphere, cryosphere and the terrestrial earth, as well as human modifications to the earth system. Principal topics include: • Remotely sensed data collection, analysis, interpretation and display. • Surveying from space, air, water and ground platforms. • Imaging and related sensors. • Image processing. • Use of remotely sensed data. • Economic surveys and cost-benefit analyses. • Drones Section: Remote sensing with unmanned aerial systems (UASs, also known as unmanned aerial vehicles (UAVs), or drones).