Machine learningArtificial intelligenceLandslide detectionLandslide susceptibility assessmentConvolutional neural networksRemote sensingMultimodal data fusionThe WHO (World Health Organization) study reports that, between 1998-2017, 4.8 million people have been affected by landslides with more than 18000 deaths. ...
Object-based segmentation and machine learning classification for landslide detection from multi-temporal WorldView-2 imagery Landslides are pervasive hazards that pose significant risk to human populations. Routine quantification of landslide occurrence is necessary for ... OP Parker - 《San Francisco Stat...
Constructing site-specific multivariate probability distribution model using Bayesian machine learning. J. Eng. Mech. 145 (1), 04018126. [5] Ding, A., Zhang, Q., Zhou, X., Dai, B., 2016. Automatic recognition of landslide based on CNN and texture change detection. In:Proceedings of the...
Landslide identification using machine learning techniques: Review, motivation, and future prospects Sreelakshmi S. Vinod Chandra S. S. E. Shaji Earth Science Informatics(2022) Associated content A more dynamic understanding of landslide risk
using machine learning (ML) models such as logistic regression (LR), support vector machine (SVM), random forest (RF), extreme gradient boosting (Xgboost), or deep learning (DL) models such as convolutional neural network (CNN) and long short time memory (LSTM). As the input data for ...
Gorsevski, P.V., Brown, M.K., Panter, K., Onasch, C.M., Simic, A., Snyder, J., 2016.Landslide detection and susceptibility mapping using LiDAR and an artificial neural network approach: a case study in the Cuyahoga Valley National Park, Ohio.Landslides 13, 467. https://doi.org/...
However, change detection requires much image pre-procession of radiation correction and geometric correction. There is numerous research about landslide mapping based on post-event image, which aims to build automatic detection models using machine learning framework, such as support vector machine (SVM...
categorical dependent variable with the help of independent variables using Eq.(2).(9)Logy/y−1=b0+b1x1+b2x2+⋯bnxn (d) Identify and explain anomalies landslides: Microsoft Power BI’s line chart supports AI-based anomaly detection. Given a sequence of real values, that is,x=x1,x2...
et al. Investigating landslide data balancing for susceptibility mapping using generative and machine learning models. Landslides, 2024. DOI:10.1007/s10346-024-02352-3 26. Pucoe, G., Obagbuwa, I.C. Deep Learning Approach with a Convolutional Neural Network for Landslide Detection Using Remotely...
Lu H et al (2024) Active landslide detection using integrated remote sensing technologies for a wide region and multiple stages: a case study in southwestern China. Sci Total Environ, 172709 Ma X, Rong H, Yan Y (2024) GPS-RTK mapping technology in remote sensing dynamic monitoring of geologi...