☆ 4.7 Article

Machine learning powered high-resolution co-seismic landslide detection

GONDWANA RESEARCH (2023)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Geosciences, Multidisciplinary

Fossil brachiopod identification using a new deep convolutional neural network

Haizhou Wang et al.

Summary: The study introduces a new and efficient method for automatically identifying brachiopod fossils using a tailored Transpose Convolutional Neural Network (TCNN). Compared to the traditional Convolution Neural Network (CNN), the TCNN achieves higher identification accuracy on a smaller training dataset.

GONDWANA RESEARCH (2022)

添加到收藏夹

Article Geosciences, Multidisciplinary

Prediction of undrained shear strength using extreme gradient boosting and random forest based on Bayesian optimization

Wengang Zhang et al.

Summary: This study applies XGBoost and RF methods to predict the USS of soft clays, showing that these approaches outperform traditional methods. Bayesian optimization is used to determine model hyperparameters, leading to more accurate and robust models.

GEOSCIENCE FRONTIERS (2021)

添加到收藏夹

Article Geosciences, Multidisciplinary

Landslide identification using machine learning

Haojie Wang et al.

Summary: This paper proposes a novel machine-learning and deep-learning method to identify natural-terrain landslides using integrated geodatabases. The method was demonstrated to have high accuracy in a case study, with CNN achieving the highest identification accuracy. By utilizing machine learning and deep learning techniques, the proposed method shows outstanding robustness and great potential in tackling the landslide identification problem.

GEOSCIENCE FRONTIERS (2021)

添加到收藏夹

Review Geosciences, Multidisciplinary

Pathways and challenges of the application of artificial intelligence to geohazards modelling

Abhirup Dikshit et al.

Summary: The application of artificial intelligence and machine learning in geohazard modeling has been rapidly growing, bringing new possibilities for practical applications in geohazards through data-driven research. Future developments should focus on consecutive events, integrating physical models, and developing interpretable models capable of handling large amounts of data.

GONDWANA RESEARCH (2021)

添加到收藏夹

Article Environmental Sciences

An Automated Snow Mapper Powered by Machine Learning

Haojie Wang et al.

Summary: Snow plays a crucial role in preserving fresh water and influencing regional climate and environment. With the use of modern satellite Earth observations, an automated snow mapping system, called AutoSMILE, was developed based on machine learning. The system demonstrated high performance in accurately mapping snow depth in a mountainous region, showing its potential for large-scale high-accuracy snow mapping and monitoring.

REMOTE SENSING (2021)

添加到收藏夹

Article Engineering, Geological

AI-powered landslide susceptibility assessment in Hong Kong

Haojie Wang et al.

Summary: The study introduces a novel AI-powered object-based landslide susceptibility assessment method that defines landslide and non-landslide objects based on historical statistics, constructs samples, and utilizes AI techniques for prediction. A comprehensive case study in Hong Kong demonstrates the superiority of this method over traditional approaches and produces territory-wide landslide susceptibility maps using AI algorithms.

ENGINEERING GEOLOGY (2021)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Landslide detection based on contour-based deep learning framework in case of national scale of Nepal in 2015

Bo Yu et al.

COMPUTERS & GEOSCIENCES (2020)

添加到收藏夹

Review Geosciences, Multidisciplinary

State-of-the-art review of soft computing applications in underground excavations

Wengang Zhang et al.

GEOSCIENCE FRONTIERS (2020)

添加到收藏夹

Article Engineering, Geological

A novel physically-based model for updating landslide susceptibility

H. J. Wang et al.

ENGINEERING GEOLOGY (2019)

添加到收藏夹

Article Engineering, Geological

Evaluating volume of coseismic landslide clusters by flow direction-based partitioning

R. L. Fan et al.

ENGINEERING GEOLOGY (2019)

添加到收藏夹

Article Environmental Sciences

Repeat-pass SAR interferometry for land cover classification: A methodology using Sentinel-1 Short-Time-Series

Francescopaolo Sica et al.

REMOTE SENSING OF ENVIRONMENT (2019)

添加到收藏夹

Article Engineering, Electrical & Electronic

Landslide Detection of Hyperspectral Remote Sensing Data Based on Deep Learning With Constrains

Chengming Ye et al.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2019)

添加到收藏夹

Article Environmental Sciences

Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection

Omid Ghorbanzadeh et al.

REMOTE SENSING (2019)

添加到收藏夹

Article Engineering, Geological

Evolution of debris flow activities in Gaojiagou Ravine during 2008-2016 after the Wenchuan earthquake

R. L. Fan et al.

ENGINEERING GEOLOGY (2018)

添加到收藏夹

Article Engineering, Geological

Coseismic landslides triggered by the 8th August 2017 Ms 7.0 Jiuzhaigou earthquake (Sichuan, China): factors controlling their spatial distribution and implications for the seismogenic blind fault identification

Xuanmei Fan et al.

LANDSLIDES (2018)

添加到收藏夹

Article Geography, Physical

Impact of the 2008 Wenchuan earthquake in China on subsequent long-term debris flow activities in the epicentral area

S. Zhang et al.

GEOMORPHOLOGY (2017)

添加到收藏夹

Article Environmental Sciences

Semi-automated landslide inventory mapping from bitemporal aerial photographs using change detection and level set method

Zhongbin Li et al.

REMOTE SENSING OF ENVIRONMENT (2016)

添加到收藏夹

Article Geosciences, Multidisciplinary

Multivariate adaptive regression splines and neural network models for prediction of pile drivability

Wengang Zhang et al.

GEOSCIENCE FRONTIERS (2016)

添加到收藏夹

Article Multidisciplinary Sciences

Evolution of Mass Movements near Epicentre of Wenchuan Earthquake, the First Eight Years

Shuai Zhang et al.

SCIENTIFIC REPORTS (2016)

添加到收藏夹

Review Multidisciplinary Sciences

Deep learning

Yann LeCun et al.

NATURE (2015)

添加到收藏夹

Article Environmental Sciences

Identification of Forested Landslides Using LiDar Data, Object-based Image Analysis, and Machine Learning Algorithms

Xianju Li et al.

REMOTE SENSING (2015)

添加到收藏夹

Article Engineering, Geological

Multi-hazard scenarios and consequences in Beichuan, China: The first five years after the 2008 Wenchuan earthquake

L. M. Zhang et al.

ENGINEERING GEOLOGY (2014)

添加到收藏夹

Article Engineering, Geological

Three (nearly) complete inventories of landslides triggered by the May 12, 2008 Wenchuan Mw 7.9 earthquake of China and their spatial distribution statistical analysis

Chong Xu et al.

LANDSLIDES (2014)

添加到收藏夹

Article Environmental Sciences

Co-seismic landslide inventory and susceptibility mapping in the 2008 Wenchuan earthquake disaster area, China

Li Wei-le et al.

JOURNAL OF MOUNTAIN SCIENCE (2013)

添加到收藏夹

Article Geography, Physical

Object-oriented identification of forested landslides with derivatives of single pulse LiDAR data

Miet Van Den Eeckhaut et al.

GEOMORPHOLOGY (2012)

添加到收藏夹

Article Geosciences, Multidisciplinary

Assessment of risks of loose landslide deposits formed by the 2008 Wenchuan earthquake

S. Zhang et al.

NATURAL HAZARDS AND EARTH SYSTEM SCIENCES (2012)

添加到收藏夹

Article Geosciences, Multidisciplinary

Spatial distribution of landslides triggered by the 2008 Ms 8.0 Wenchuan earthquake, China

F. C. Dai et al.

JOURNAL OF ASIAN EARTH SCIENCES (2011)

添加到收藏夹

Article Environmental Sciences

Object-oriented mapping of landslides using Random Forests

Andre Stumpf et al.

REMOTE SENSING OF ENVIRONMENT (2011)

添加到收藏夹

Article Geography, Physical

Characterising spectral, spatial and morphometric properties of landslides for semi-automatic detection using object-oriented methods

Tapas R. Martha et al.

GEOMORPHOLOGY (2010)

添加到收藏夹

Article Engineering, Environmental

Analysis of the geo-hazards triggered by the 12 May 2008 Wenchuan Earthquake, China

R. Q. Huang et al.

BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT (2009)

添加到收藏夹

Article Remote Sensing

Detecting translational landslide scars using segmentation of Landsat ETM+ and DEM data in the northern Cascade Mountains, British Columbia

J Barlow et al.

CANADIAN JOURNAL OF REMOTE SENSING (2003)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.