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The Application of Terrestrial LiDAR for Geohazard Mapping,
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RS(13), No. 3, 2021, pp. xx-yy.
DOI Link
2102
BibRef
Barbosa, N.[Natalie],
Andreani, L.[Louis],
Gloaguen, R.[Richard],
Ratschbacher, L.[Lothar],
Window-Based Morphometric Indices as Predictive Variables for
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DOI Link
2102
BibRef
Xie, W.[Wei],
Li, X.S.[Xiao-Shuang],
Jian, W.B.[Wen-Bin],
Yang, Y.[Yang],
Liu, H.W.[Hong-Wei],
Robledo, L.F.[Luis F.],
Nie, W.[Wen],
A Novel Hybrid Method for Landslide Susceptibility Mapping-Based
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2103
BibRef
Wang, X.L.[Xue-Liang],
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A New Approach for Identification of Potential Rockfall Source Areas
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DOI Link
2103
BibRef
Khan, M.W.[Muhammad Waqas],
Dunning, S.[Stuart],
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Martin, J.[James],
Diaz-Moreno, A.[Alejandro],
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Jin, N.[Nanlin],
Woodward, J.[John],
Lim, M.[Michael],
Low-Cost Automatic Slope Monitoring Using Vector Tracking Analyses on
Live-Streamed Time-Lapse Imagery,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Liu, Y.[Yimo],
Zhang, W.C.[Wan-Chang],
Zhang, Z.J.[Zhi-Jie],
Xu, Q.[Qiang],
Li, W.[Weile],
Risk Factor Detection and Landslide Susceptibility Mapping Using
Geo-Detector and Random Forest Models: The 2018 Hokkaido Eastern
Iburi Earthquake,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
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
Himalayan Region: Recent Developments, Gaps, and Future Directions,
IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Nefeslioglu, H.A.[Hakan A.],
Tavus, B.[Beste],
Er, M.[Melahat],
Ertugrul, G.[Gamze],
Ozdemir, A.[Aybuke],
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
Loche, M.[Marco],
Scaringi, G.[Gianvito],
Blahut, J.[Jan],
Melis, M.T.[Maria Teresa],
Funedda, A.[Antonio],
da Pelo, S.[Stefania],
Erbě, I.[Ivan],
Deiana, G.[Giacomo],
Meloni, M.A.[Mattia Alessio],
Cocco, F.[Fabrizio],
An Infrared Thermography Approach to Evaluate the Strength of a Rock
Cliff,
RS(13), No. 7, 2021, pp. xx-yy.
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
Highway (Cuenca-Ecuador),
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],
Liu, H.L.[Hai-Liang],
Liu, X.Y.[Xiao-Yang],
Khan, K.U.J.[Kaleem Ullah Jan],
A Hybrid Model Consisting of Supervised and Unsupervised Learning for
Landslide Susceptibility Mapping,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Wang, Y.B.[Yun-Biao],
Xu, S.B.[Shi-Biao],
Xiao, J.[Jun],
Wang, F.P.[Fei-Peng],
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
Point Clouds,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link
2203
BibRef
Tseng, C.M.[Chih-Ming],
Chen, Y.R.[Yie-Ruey],
Chang, C.M.[Chwen-Ming],
Chue, Y.S.[Yung-Sheng],
Hsieh, S.C.[Shun-Chieh],
Assessment of Rainfall-Induced Landslide Distribution Based on Land
Disturbance in Southern Taiwan,
IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link
2104
BibRef
He, L.F.[Ling-Feng],
Coggan, J.[John],
Francioni, M.[Mirko],
Eyre, M.[Matthew],
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,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Luo, S.Y.[Shi-Yu],
Sarabandi, K.[Kamal],
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
Arma?, I.[Iuliana],
Gheorghe, M.[Mihaela],
Silva?, G.C.[George Catalin],
Shallow Landslides Physically Based Susceptibility Assessment
Improvement Using InSAR. Case Study: Carpathian and Subcarpathian
Prahova Valley, Romania,
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
Landslides in the Eastern Tibetan Plateau,
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
Mapping Using Random Forest and GeoDetector,
RS(13), No. 13, 2021, pp. xx-yy.
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
on Machine Learning Feature Transformation,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Li, J.F.[Jiang-Feng],
Stankovic, L.[Lina],
Pytharouli, S.[Stella],
Stankovic, V.[Vladimir],
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
Basins of the Vallo di Diano, Southern Italy,
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],
Hérnandez, M.[Mario],
Robustelli, G.[Gaetano],
Mateos, R.M.[Rosa María],
García-Davalillo, J.C.[Juan Carlos],
An Integration of UAV-Based Photogrammetry and 3D Modelling for
Rockfall Hazard Assessment: The Cárcavos Case in 2018 (Spain),
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],
Zhao, Y.G.[Ying-Gang],
Li, K.F.[Kai-Feng],
Deng, K.L.[Kai-Liang],
Wang, Y.X.[Yue-Xin],
An Improved Method for Automatic Identification and Assessment of
Potential Geohazards Based on MT-InSAR Measurements,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Moretto, S.[Serena],
Bozzano, F.[Francesca],
Mazzanti, P.[Paolo],
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
Shu, H.P.[He-Ping],
Guo, Z.Z.[Zi-Zheng],
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
for Landslide Susceptibility Mapping:
A Case Study from Lanzhou City of Northwestern China,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Kong, C.F.[Chun-Fang],
Tian, Y.P.[Yi-Ping],
Ma, X.G.[Xiao-Gang],
Weng, Z.P.[Zheng-Ping],
Zhang, Z.T.[Zhi-Ting],
Xu, K.[Kai],
Landslide Susceptibility Assessment Based on Different Machine
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RS(13), No. 18, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Panchal, S.[Sandeep],
Shrivastava, A.K.[Amit K.],
A Comparative Study of Frequency Ratio, Shannon's Entropy and
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IJGI(10), No. 9, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Hussain, M.A.[Muhammad Afaq],
Chen, Z.L.[Zhan-Long],
Wang, R.[Run],
Shoaib, M.[Muhammad],
PS-InSAR-Based Validated Landslide Susceptibility Mapping along
Karakorum Highway, Pakistan,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Hu, H.[Han],
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Liang, Z.[Zhu],
Gao, R.Y.[Rui-Yuan],
Li, B.L.[Bai-Long],
Exploring Complementary Models Consisting of Machine Learning
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IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Xu, S.H.[Sheng-Hua],
Zhang, M.[Meng],
Ma, Y.[Yu],
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Wang, Y.[Yong],
Ma, X.R.[Xin-Rui],
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Multiclassification Method of Landslide Risk Assessment in
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IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link
2110
BibRef
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Landslide Susceptibility Mapping by Comparing GIS-Based Bivariate
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RS(13), No. 21, 2021, pp. xx-yy.
DOI Link
2112
BibRef
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Evaluation of Conditioning Factors of Slope Instability and
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RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
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Pradhan, B.[Biswajeet],
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A Meta-Learning Approach of Optimisation for Spatial Prediction of
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2112
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Rong, G.Z.[Guang-Zhi],
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Comparison of Tree-Structured Parzen Estimator Optimization in Three
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DOI Link
2112
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Weidner, L.[Luke],
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Monitoring the Effects of Slope Hazard Mitigation and Weather on
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DOI Link
2112
BibRef
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Shared Blocks-Based Ensemble Deep Learning for Shallow Landslide
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RS(13), No. 23, 2021, pp. xx-yy.
DOI Link
2112
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Susceptibility Assessment for Landslide Initiated along Power
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2112
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Hybrids of Support Vector Regression with Grey Wolf Optimizer and
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RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
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Loiotine, L.[Lidia],
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Derron, M.H.[Marc-Henri],
Comparison of Remote Sensing Techniques for Geostructural Analysis
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RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
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Hu, J.Y.[Ji-Yuan],
Motagh, M.[Mahdi],
Wang, J.Y.[Jia-Yao],
Qin, F.[Fen],
Zhang, J.C.[Jian-Chen],
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Han, Y.K.[Ya-Kun],
Karst Collapse Risk Zonation and Evaluation in Wuhan, China Based on
Analytic Hierarchy Process, Logistic Regression, and InSAR Angular
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RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
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Maxwell, A.E.[Aaron E.],
Sharma, M.[Maneesh],
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DOI Link
2112
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Zhang, X.[Xuan],
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Failure Mechanism and Long Short-Term Memory Neural Network Model for
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RS(14), No. 1, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Zhao, P.X.[Peng-Xiang],
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DOI Link
2201
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Comparative Study of Convolutional Neural Network and Conventional
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RS(14), No. 2, 2022, pp. xx-yy.
DOI Link
2201
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A Graph Convolutional Incorporating GRU Network for Landslide
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2202
BibRef
Lizama, E.[Elizabet],
Morales, B.[Bastian],
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Understanding Landslide Susceptibility in Northern Chilean Patagonia:
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RS(14), No. 4, 2022, pp. xx-yy.
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2202
BibRef
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Impact of Land Use/Land Cover Change on Landslide Susceptibility in
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DOI Link
2202
BibRef
Jiang, H.[Hu],
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Susceptibility Assessment of Debris Flows Coupled with
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RS(14), No. 6, 2022, pp. xx-yy.
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2204
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Hazard Assessment of Rocky Slopes: An Integrated Photogrammetry-GIS
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RS(14), No. 6, 2022, pp. xx-yy.
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2204
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Landslide Susceptibility Mapping along a Rapidly Uplifting River
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RS(14), No. 7, 2022, pp. xx-yy.
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2205
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The Impact of Climate Changes on Slope Stability and Landslide
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RS(14), No. 8, 2022, pp. xx-yy.
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2205
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Discussion on InSAR Identification Effectivity of Potential
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Predicting Landslides Susceptible Zones in the Lesser Himalayas by
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Liu, W.C.[Wang-Cai],
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Landslide Risk Assessment Using a Combined Approach Based on InSAR
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Landslide Susceptibility Assessment Model Construction Using Typical
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Landslide Susceptibility Mapping Based on the Germinal Center
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Evaluation and Prediction of Landslide Susceptibility in Yichang
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A Novel Intelligent Method Based on the Gaussian Heatmap Sampling
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Vulnerability Analysis of Geographical Railway Network under
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Landslide Risk Assessment in Eastern Kentucky, USA: Developing a
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See also Spatio-Temporal Knowledge Graph Based Forest Fire Prediction with Multi Source Heterogeneous Data.
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Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Specific Site Landslide Analysis .