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DOI Link
2102
BibRef
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Window-Based Morphometric Indices as Predictive Variables for
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BibRef
Xie, W.[Wei],
Li, X.S.[Xiao-Shuang],
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Yang, Y.[Yang],
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Nie, W.[Wen],
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BibRef
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Lim, M.[Michael],
Low-Cost Automatic Slope Monitoring Using Vector Tracking Analyses on
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2103
BibRef
Liu, Y.[Yimo],
Zhang, W.C.[Wan-Chang],
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Risk Factor Detection and Landslide Susceptibility Mapping Using
Geo-Detector and Random Forest Models: The 2018 Hokkaido Eastern
Iburi Earthquake,
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DOI Link
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Batar, A.K.[Amit Kumar],
Watanabe, T.[Teiji],
Landslide Susceptibility Mapping and Assessment Using Geospatial
Platforms and Weights of Evidence (WoE) Method in the Indian
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IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link
2104
BibRef
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Tavus, B.[Beste],
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Kaya, A.[Alperen],
Kocaman, S.[Sultan],
Integration of an InSAR and ANN for Sinkhole Susceptibility Mapping:
A Case Study from Kirikkale-Delice (Turkey),
IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link
2104
BibRef
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Scaringi, G.[Gianvito],
Blahut, J.[Jan],
Melis, M.T.[Maria Teresa],
Funedda, A.[Antonio],
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Erbì, I.[Ivan],
Deiana, G.[Giacomo],
Meloni, M.A.[Mattia Alessio],
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An Infrared Thermography Approach to Evaluate the Strength of a Rock
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DOI Link
2104
BibRef
Miele, P.[Pietro],
di Napoli, M.[Mariano],
Guerriero, L.[Luigi],
Ramondini, M.[Massimo],
Sellers, C.[Chester],
Corona, M.A.[Mariagiulia Annibali],
di Martire, D.[Diego],
Landslide Awareness System (LAwS) to Increase the Resilience and
Safety of Transport Infrastructure: The Case Study of Pan-American
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RS(13), No. 8, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Liang, Z.[Zhu],
Wang, C.M.[Chang-Ming],
Duan, Z.J.[Zhi-Jie],
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Khan, K.U.J.[Kaleem Ullah Jan],
A Hybrid Model Consisting of Supervised and Unsupervised Learning for
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DOI Link
2104
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Wang, Y.B.[Yun-Biao],
Xu, S.B.[Shi-Biao],
Xiao, J.[Jun],
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Wang, Y.[Ying],
Liu, L.P.[Lu-Peng],
Accurate Rock-Mass Extraction From Terrestrial Laser Point Clouds via
Multiscale and Multiview Convolutional Feature Representation,
GeoRS(59), No. 5, May 2021, pp. 4430-4443.
IEEE DOI
2104
Feature extraction, Rocks,
Vegetation mapping, Surface morphology, Lasers,
point clouds labeling
BibRef
Yu, D.B.[Dong-Bo],
Xiao, J.[Jun],
Wang, Y.[Ying],
Efficient Lightweight Surface Reconstruction Method from Rock-Mass
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RS(14), No. 5, 2022, pp. xx-yy.
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2203
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Tseng, C.M.[Chih-Ming],
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Chang, C.M.[Chwen-Ming],
Chue, Y.S.[Yung-Sheng],
Hsieh, S.C.[Shun-Chieh],
Assessment of Rainfall-Induced Landslide Distribution Based on Land
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IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link
2104
BibRef
He, L.F.[Ling-Feng],
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Maximizing Impacts of Remote Sensing Surveys in Slope Stability: A
Novel Method to Incorporate Discontinuities into Machine Learning
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IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Zheng, X.X.[Xiang-Xiang],
He, G.J.[Guo-Jin],
Wang, S.S.[Shan-Shan],
Wang, Y.[Yi],
Wang, G.Z.[Gui-Zhou],
Yang, Z.Y.[Zhao-Ying],
Yu, J.C.[Jun-Chuan],
Wang, N.[Ning],
Comparison of Machine Learning Methods for Potential Active Landslide
Hazards Identification with Multi-Source Data,
IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Maxwell, A.E.[Aaron E.],
Sharma, M.[Maneesh],
Kite, J.S.[J. Steven],
Donaldson, K.A.[Kurt A.],
Maynard, S.M.[Shannon M.],
Malay, C.M.[Caleb M.],
Assessing the Generalization of Machine Learning-Based Slope Failure
Prediction to New Geographic Extents,
IJGI(10), No. 5, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Weidner, L.[Luke],
Walton, G.[Gabriel],
Krajnovich, A.[Ashton],
Classifying rock slope materials in photogrammetric point clouds
using robust color and geometric features,
PandRS(176), 2021, pp. 15-29.
Elsevier DOI
2106
Photogrammetry, Semantic segmentation, Rock slope monitoring,
Color, Feature selection
BibRef
Yang, X.[Xin],
Liu, R.[Rui],
Yang, M.[Mei],
Chen, J.J.[Jing-Jue],
Liu, T.Q.[Tian-Qiang],
Yang, Y.T.[Yuan-Tao],
Chen, W.[Wei],
Wang, Y.T.[Yu-Ting],
Incorporating Landslide Spatial Information and Correlated Features
among Conditioning Factors for Landslide Susceptibility Mapping,
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2106
BibRef
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Tong, L.[Ling],
Pierce, L.E.[Leland E.],
Probability Assessment of Rainfall-Induced Landslides Based on Safety
Factors Using Soil Moisture Estimation From SAR Images,
GeoRS(59), No. 7, July 2021, pp. 5579-5597.
IEEE DOI
2106
Landslides, Synthetic aperture radar, Stability analysis,
Soil moisture, Data models, Vegetation mapping, Radar polarimetry,
synthetic aperture radar (SAR)
BibRef
Armas, I.[Iuliana],
Gheorghe, M.[Mihaela],
Silvax, G.C.[George Catalin],
Shallow Landslides Physically Based Susceptibility Assessment
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RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Guo, X.Y.[Xin-Yi],
Fu, B.H.[Bi-Hong],
Du, J.[Jie],
Shi, P.[Pilong],
Chen, Q.Y.[Qing-Yu],
Zhang, W.Y.[Wen-Yuan],
Applicability of Susceptibility Model for Rock and Loess Earthquake
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RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Wang, Y.[Yue],
Wen, H.[Haijia],
Sun, D.L.[De-Liang],
Li, Y.[Yuechen],
Quantitative Assessment of Landslide Risk Based on Susceptibility
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DOI Link
2107
BibRef
Al-Najjar, H.A.H.[Husam A. H.],
Pradhan, B.[Biswajeet],
Kalantar, B.[Bahareh],
Sameen, M.I.[Maher Ibrahim],
Santosh, M.,
Alamri, A.[Abdullah],
Landslide Susceptibility Modeling: An Integrated Novel Method Based
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RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Li, J.F.[Jiang-Feng],
Stankovic, L.[Lina],
Pytharouli, S.[Stella],
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Automated Platform for Microseismic Signal Analysis: Denoising,
Detection, and Classification in Slope Stability Studies,
GeoRS(59), No. 9, September 2021, pp. 7996-8006.
IEEE DOI
2109
Landslides, Noise reduction, Signal processing algorithms,
Benchmark testing, Soil, Signal processing, Feature extraction,
graph Laplacian regularization (GLR) classification
BibRef
Giano, S.I.[Salvatore Ivo],
Pescatore, E.[Eva],
Siervo, V.[Vincenzo],
Morphometry and Debris-Flow Susceptibility Map in Mountain Drainage
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RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Gallo, I.G.[Ilenia G.],
Martínez-Corbella, M.[Mónica],
Sarro, R.[Roberto],
Iovine, G.[Giulio],
López-Vinielles, J.[Juan],
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Robustelli, G.[Gaetano],
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García-Davalillo, J.C.[Juan Carlos],
An Integration of UAV-Based Photogrammetry and 3D Modelling for
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RS(13), No. 17, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Luo, S.R.[Shu-Ran],
Feng, G.C.[Guang-Cai],
Xiong, Z.Q.[Zhi-Qiang],
Wang, H.Y.[Hai-Yan],
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An Improved Method for Automatic Identification and Assessment of
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DOI Link
2109
BibRef
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The Role of Satellite InSAR for Landslide Forecasting:
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RS(13), No. 18, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Gantimurova, S.[Svetlana],
Parshin, A.[Alexander],
Erofeev, V.[Vladimir],
GIS-Based Landslide Susceptibility Mapping of the Circum-Baikal
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RS(13), No. 18, 2021, pp. xx-yy.
DOI Link
2109
BibRef
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Qi, S.[Shi],
Song, D.Q.[Dan-Qing],
Pourghasemi, H.R.[Hamid Reza],
Ma, J.C.[Jia-Cheng],
Integrating Landslide Typology with Weighted Frequency Ratio Model
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RS(13), No. 18, 2021, pp. xx-yy.
DOI Link
2109
BibRef
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Landslide Susceptibility Assessment Based on Different Machine
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DOI Link
2109
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A Comparative Study of Frequency Ratio, Shannon's Entropy and
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DOI Link
2109
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PS-InSAR-Based Validated Landslide Susceptibility Mapping along
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RS(13), No. 20, 2021, pp. xx-yy.
DOI Link
2110
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Exploring Complementary Models Consisting of Machine Learning
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IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link
2110
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Multiclassification Method of Landslide Risk Assessment in
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2110
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2112
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Evaluation of Conditioning Factors of Slope Instability and
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2112
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2112
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Karst Collapse Risk Zonation and Evaluation in Wuhan, China Based on
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2112
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2201
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A Graph Convolutional Incorporating GRU Network for Landslide
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2202
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Landslide Susceptibility Mapping along a Rapidly Uplifting River
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The Impact of Climate Changes on Slope Stability and Landslide
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Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Specific Site Landslide Analysis .