Magliulo, P.[Paolo],
di Lisio, A.[Antonio],
Russo, F.[Filippo],
Comparison of GIS-based methodologies for the landslide susceptibility
assessment,
GeoInfo(13), No. 3, September 2009, pp. xx-yy.
Springer DOI
0905
BibRef
Pradhan, B.[Biswajeet],
Lee, S.[Saro],
Buchroithner, M.F.[Manfred F.],
Remote Sensing and GIS-based Landslide Susceptibility Analysis and its
Cross-validation in Three Test Areas Using a Frequency Ratio Model,
PFG(2010), No. 1, 2010, pp. 17-32.
WWW Link.
1211
BibRef
Rauste, Y.,
Lateh, H.B.,
Jefriza,,
Mohd, M.W.I.W.[M. W. I. Wan],
Lonnqvist, A.,
Hame, T.,
TerraSAR-X Data in Cut Slope Soil Stability Monitoring in Malaysia,
GeoRS(50), No. 9, September 2012, pp. 3354-3363.
IEEE DOI
1209
BibRef
Qiao, G.[Gang],
Lu, P.[Ping],
Scaioni, M.[Marco],
Xu, S.Y.[Shu-Ying],
Tong, X.H.[Xiao-Hua],
Feng, T.T.[Tian-Tian],
Wu, H.B.[Hang-Bin],
Chen, W.[Wen],
Tian, Y.X.[Yi-Xiang],
Wang, W.[Weian],
Li, R.X.[Rong-Xing],
Landslide Investigation with Remote Sensing and Sensor Network: From
Susceptibility Mapping and Scaled-down Simulation towards in situ
Sensor Network Design,
RS(5), No. 9, 2013, pp. 4319-4346.
DOI Link
1310
BibRef
Chalkias, C.[Christos],
Ferentinou, M.[Maria],
Polykretis, C.[Christos],
GIS Supported Landslide Susceptibility Modeling at Regional Scale:
An Expert-Based Fuzzy Weighting Method,
IJGI(3), No. 2, 2014, pp. 523-539.
DOI Link
1405
BibRef
Yin, L.Z.[Ling-Zhi],
Zhu, J.[Jun],
Li, Y.[Yi],
Zeng, C.[Chao],
Zhu, Q.[Qing],
Qi, H.[Hua],
Liu, M.W.[Ming-Wei],
Li, W.[Weilian],
Cao, Z.Y.[Zhen-Yu],
Yang, W.J.[Wei-Jun],
Zhang, P.C.[Peng-Cheng],
A Virtual Geographic Environment for Debris Flow Risk Analysis in
Residential Areas,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link
1712
BibRef
Ba, Q.Q.[Qian-Qian],
Chen, Y.M.[Yu-Min],
Deng, S.[Susu],
Wu, Q.J.[Qian-Jiao],
Yang, J.X.[Jia-Xin],
Zhang, J.Y.[Jing-Yi],
An Improved Information Value Model Based on Gray Clustering for
Landslide Susceptibility Mapping,
IJGI(6), No. 1, 2017, pp. xx-yy.
DOI Link
1702
BibRef
Deng, X.L.[Xiao-Long],
Li, L.H.[Li-Hui],
Tan, Y.F.[Yu-Fang],
Validation of Spatial Prediction Models for Landslide Susceptibility
Mapping by Considering Structural Similarity,
IJGI(6), No. 4, 2017, pp. xx-yy.
DOI Link
1705
BibRef
Park, H.J.[Hyuck-Jin],
Jang, J.Y.[Jung-Yoon],
Lee, J.H.[Jung-Hyun],
Physically Based Susceptibility Assessment of Rainfall-Induced
Shallow Landslides Using a Fuzzy Point Estimate Method,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link
1706
BibRef
Shrestha, S.[Suchita],
Kang, T.S.[Tae-Seob],
Suwal, M.K.[Madan Krishna],
An Ensemble Model for Co-Seismic Landslide Susceptibility Using GIS
and Random Forest Method,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link
1712
BibRef
Merghadi, A.[Abdelaziz],
Abderrahmane, B.[Boumezbeur],
Bui, D.T.[Dieu Tien],
Landslide Susceptibility Assessment at Mila Basin (Algeria): A
Comparative Assessment of Prediction Capability of Advanced Machine
Learning Methods,
IJGI(7), No. 7, 2018, pp. xx-yy.
DOI Link
1808
BibRef
Kadavi, P.R.[Prima Riza],
Lee, C.W.[Chang-Wook],
Lee, S.[Saro],
Application of Ensemble-Based Machine Learning Models to Landslide
Susceptibility Mapping,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link
1809
BibRef
Liu, C.C.[Cheng-Chien],
Luo, W.[Wei],
Chung, H.W.[Hsiao-Wei],
Yin, H.Y.[Hsiao-Yuan],
Yan, K.W.[Ke-Wei],
Influences of the Shadow Inventory on a Landslide Susceptibility
Model,
IJGI(7), No. 9, 2018, pp. xx-yy.
DOI Link
1810
BibRef
Capitani, M.[Marco],
Ribolini, A.[Adriano],
Bini, M.[Monica],
Susceptibility to Translational Slide-Type Landslides: Applicability
of the Main Scarp Upper Edge as a Dependent Variable Representation
by Reduced Chi-Square Analysis,
IJGI(7), No. 9, 2018, pp. xx-yy.
DOI Link
1810
BibRef
Si, A.[Alu],
Zhang, J.[Jiquan],
Tong, S.[Siqin],
Lai, Q.[Quan],
Wang, R.[Rui],
Li, N.[Na],
Bao, Y.B.[Yong-Bin],
Regional Landslide Identification Based on Susceptibility Analysis
and Change Detection,
IJGI(7), No. 10, 2018, pp. xx-yy.
DOI Link
1811
BibRef
Kang, K.[Kai],
Ponomarev, A.[Andrey],
Zerkal, O.[Oleg],
Huang, S.[Shiyuan],
Lin, Q.[Qigen],
Shallow Landslide Susceptibility Mapping in Sochi Ski-Jump Area Using
GIS and Numerical Modelling,
IJGI(8), No. 3, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Arabameri, A.[Alireza],
Pradhan, B.[Biswajeet],
Rezaei, K.[Khalil],
Lee, C.W.[Chang-Wook],
Assessment of Landslide Susceptibility Using Statistical- and
Artificial Intelligence-Based FR-RF Integrated Model and
Multiresolution DEMs,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link
1905
BibRef
Zhang, Y.[Yichi],
Yue, P.[Pan],
Zhang, G.[Guike],
Guan, T.[Tao],
Lv, M.M.[Ming-Ming],
Zhong, D.[Denghua],
Augmented Reality Mapping of Rock Mass Discontinuities and Rockfall
Susceptibility Based on Unmanned Aerial Vehicle Photogrammetry,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link
1906
BibRef
Li, H.F.[Hui-Fang],
Chen, Y.M.[Yu-Min],
Deng, S.[Susu],
Chen, M.[Meijie],
Fang, T.[Tao],
Tan, H.Y.[Huang-Yuan],
Eigenvector Spatial Filtering-Based Logistic Regression for Landslide
Susceptibility Assessment,
IJGI(8), No. 8, 2019, pp. xx-yy.
DOI Link
1909
BibRef
Lai, J.S.[Jhe-Syuan],
Chiang, S.H.[Shou-Hao],
Tsai, F.[Fuan],
Exploring Influence of Sampling Strategies on Event-Based Landslide
Susceptibility Modeling,
IJGI(8), No. 9, 2019, pp. xx-yy.
DOI Link
1909
BibRef
Mutlu, B.[Begum],
Nefeslioglu, H.A.[Hakan A.],
Sezer, E.A.[Ebru A.],
Akcayol, M.A.[M. Ali],
Gokceoglu, C.[Candan],
An Experimental Research on the Use of Recurrent Neural Networks in
Landslide Susceptibility Mapping,
IJGI(8), No. 12, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Saleem, N.[Nayyer],
Huq, M.E.[Md. Enamul],
Twumasi, N.Y.D.[Nana Yaw Danquah],
Javed, A.[Akib],
Sajjad, A.[Asif],
Parameters Derived from and/or Used with Digital Elevation Models
(DEMs) for Landslide Susceptibility Mapping and Landslide Risk
Assessment: A Review,
IJGI(8), No. 12, 2019, pp. xx-yy.
DOI Link
1912
BibRef
del Soldato, M.[Matteo],
Solari, L.[Lorenzo],
Poggi, F.[Francesco],
Raspini, F.[Federico],
Tomás, R.[Roberto],
Fanti, R.[Riccardo],
Casagli, N.[Nicola],
Landslide-Induced Damage Probability Estimation Coupling InSAR and
Field Survey Data by Fragility Curves,
RS(11), No. 12, 2019, pp. xx-yy.
DOI Link
1907
BibRef
Fan, R.[Runyu],
Wang, L.Z.[Li-Zhe],
Yan, J.N.[Ji-Ning],
Song, W.J.[Wei-Jing],
Zhu, Y.Q.[Ying-Qian],
Chen, X.D.[Xiao-Dao],
Deep Learning-Based Named Entity Recognition and Knowledge Graph
Construction for Geological Hazards,
IJGI(9), No. 1, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Chang, Z.[Zhilu],
Du, Z.[Zhen],
Zhang, F.[Fan],
Huang, F.[Faming],
Chen, J.[Jiawu],
Li, W.B.[Wen-Bin],
Guo, Z.Z.[Zi-Zheng],
Landslide Susceptibility Prediction Based on Remote Sensing Images
and GIS: Comparisons of Supervised and Unsupervised Machine Learning
Models,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link
2002
BibRef
Huang, F.[Faming],
Chen, J.[Jiawu],
Du, Z.[Zhen],
Yao, C.[Chi],
Huang, J.S.[Jin-Song],
Jiang, Q.H.[Qing-Hui],
Chang, Z.[Zhilu],
Li, S.[Shu],
Landslide Susceptibility Prediction Considering Regional Soil Erosion
Based on Machine-Learning Models,
IJGI(9), No. 6, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Arabameri, A.[Alireza],
Saha, S.I.[Sun-Il],
Roy, J.[Jagabandhu],
Chen, W.[Wei],
Blaschke, T.[Thomas],
Bui, D.T.[Dieu Tien],
Landslide Susceptibility Evaluation and Management Using Different
Machine Learning Methods in The Gallicash River Watershed, Iran,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link
2002
BibRef
Maxwell, A.E.[Aaron E.],
Sharma, M.[Maneesh],
Kite, J.S.[James S.],
Donaldson, K.A.[Kurt A.],
Thompson, J.A.[James A.],
Bell, M.L.[Matthew L.],
Maynard, S.M.[Shannon M.],
Slope Failure Prediction Using Random Forest Machine Learning and
LiDAR in an Eroded Folded Mountain Belt,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link
2002
BibRef
Shirvani, Z.[Zeinab],
A Holistic Analysis for Landslide Susceptibility Mapping Applying
Geographic Object-Based Random Forest: A Comparison between Protected
and Non-Protected Forests,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link
2002
BibRef
Qin, Y.X.[Yu-Xiao],
Hoppe, E.[Edward],
Perissin, D.[Daniele],
Slope Hazard Monitoring Using High-Resolution Satellite Remote
Sensing: Lessons Learned from a Case Study,
IJGI(9), No. 2, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Chen, L.Q.[Li-Quan],
Zhao, C.Y.[Chao-Ying],
Kang, Y.[Ya],
Chen, H.Y.[Heng-Yi],
Yang, C.S.[Cheng-Sheng],
Li, B.[Bin],
Liu, Y.Y.[Yuan-Yuan],
Xing, A.[Aiguo],
Pre-Event Deformation and Failure Mechanism Analysis of the Pusa
Landslide, China with Multi-Sensor SAR Imagery,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Wang, G.R.[Gui-Rong],
Chen, X.[Xi],
Chen, W.[Wei],
Spatial Prediction of Landslide Susceptibility Based on GIS and
Discriminant Functions,
IJGI(9), No. 3, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Qi, L.[Lin],
Tan, W.X.[Wei-Xian],
Huang, P.P.[Ping-Ping],
Xu, W.[Wei],
Qi, Y.[Yaolong],
Zhang, M.[Mingzhi],
Landslide Prediction Method Based on a Ground-Based Micro-Deformation
Monitoring Radar,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Zhang, M.M.[Ming-Mei],
Xue, Y.A.[Yong-An],
Ge, Y.H.[Yong-Hui],
Zhao, J.L.[Jin-Ling],
Watershed Segmentation Algorithm Based on Luv Color Space Region
Merging for Extracting Slope Hazard Boundaries,
IJGI(9), No. 4, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Senanayake, S.[Sumudu],
Pradhan, B.[Biswajeet],
Huete, A.[Alfredo],
Brennan, J.[Jane],
Assessing Soil Erosion Hazards Using Land-Use Change and Landslide
Frequency Ratio Method: A Case Study of Sabaragamuwa Province, Sri
Lanka,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Luti, T.[Tania],
Segoni, S.[Samuele],
Catani, F.[Filippo],
Munafò, M.[Michele],
Casagli, N.[Nicola],
Integration of Remotely Sensed Soil Sealing Data in Landslide
Susceptibility Mapping,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Felice, P.D.[Paolino Di],
Ranking of Assets with Respect to Their Exposure to the Landslide
Hazard: A GIS Proposal,
IJGI(9), No. 5, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Kalantar, B.[Bahareh],
Ueda, N.[Naonori],
Saeidi, V.[Vahideh],
Ahmadi, K.[Kourosh],
Halin, A.A.[Alfian Abdul],
Shabani, F.[Farzin],
Landslide Susceptibility Mapping: Machine and Ensemble Learning Based
on Remote Sensing Big Data,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link
2006
See also Forest Fire Susceptibility Prediction Based on Machine Learning Models with Resampling Algorithms on Remote Sensing Data.
BibRef
Canavesi, V.[Vanessa],
Segoni, S.[Samuele],
Rosi, A.[Ascanio],
Ting, X.[Xiao],
Nery, T.[Tulius],
Catani, F.[Filippo],
Casagli, N.[Nicola],
Different Approaches to Use Morphometric Attributes in Landslide
Susceptibility Mapping Based on Meso-Scale Spatial Units:
A Case Study in Rio de Janeiro (Brazil),
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Melis, M.T.[Maria Teresa],
Pelo, S.D.[Stefania Da],
Erbì, I.[Ivan],
Loche, M.[Marco],
Deiana, G.[Giacomo],
Demurtas, V.[Valentino],
Meloni, M.A.[Mattia Alessio],
Dessì, F.[Francesco],
Funedda, A.[Antonio],
Scaioni, M.[Marco],
Scaringi, G.[Gianvito],
Thermal Remote Sensing from UAVs: A Review on Methods in Coastal
Cliffs Prone to Landslides,
RS(12), No. 12, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Moharrami, M.[Meisam],
Naboureh, A.[Amin],
Nachappa, T.G.[Thimmaiah Gudiyangada],
Ghorbanzadeh, O.[Omid],
Guan, X.D.[Xu-Dong],
Blaschke, T.[Thomas],
National-Scale Landslide Susceptibility Mapping in Austria Using
Fuzzy Best-Worst Multi-Criteria Decision-Making,
IJGI(9), No. 6, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Daniela, R.[Ruberti],
Ermanno, M.[Marino],
Antonio, P.[Pignalosa],
Pasquale, R.[Romano],
Marco, V.[Vigliotti],
Assessment of Tuff Sea Cliff Stability Integrating Geological Surveys
and Remote Sensing. Case History from Ventotene Island (Southern
Italy),
RS(12), No. 12, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Lei, X.X.[Xin-Xiang],
Chen, W.[Wei],
Pham, B.T.[Binh Thai],
Performance Evaluation of GIS-Based Artificial Intelligence
Approaches for Landslide Susceptibility Modeling and Spatial Patterns
Analysis,
IJGI(9), No. 7, 2020, pp. xx-yy.
DOI Link
2007
BibRef
Litoseliti, A.[Aspasia],
Koukouvelas, I.K.[Ioannis K.],
Nikolakopoulos, K.G.[Konstantinos G.],
Zygouri, V.[Vasiliki],
An Event-Based Inventory Approach in Landslide Hazard Assessment: The
Case of the Skolis Mountain, Northwest Peloponnese, Greece,
IJGI(9), No. 7, 2020, pp. xx-yy.
DOI Link
2007
BibRef
Zhao, X.[Xia],
Chen, W.[Wei],
Optimization of Computational Intelligence Models for Landslide
Susceptibility Evaluation,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link
2007
BibRef
Rabby, Y.W.[Yasin Wahid],
Ishtiaque, A.[Asif],
Rahman, M.S.[Md. Shahinoor],
Evaluating the Effects of Digital Elevation Models in Landslide
Susceptibility Mapping in Rangamati District, Bangladesh,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Qing, F.[Feng],
Zhao, Y.[Yan],
Meng, X.M.[Xing-Min],
Su, X.J.[Xiao-Jun],
Qi, T.J.[Tian-Jun],
Yue, D.X.[Dong-Xia],
Application of Machine Learning to Debris Flow Susceptibility Mapping
along the China-Pakistan Karakoram Highway,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Psomiadis, E.[Emmanouil],
Charizopoulos, N.[Nikos],
Efthimiou, N.[Nikolaos],
Soulis, K.X.[Konstantinos X.],
Charalampopoulos, I.[Ioannis],
Earth Observation and GIS-Based Analysis for Landslide Susceptibility
and Risk Assessment,
IJGI(9), No. 9, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Akinci, H.[Halil],
Kilicoglu, C.[Cem],
Dogan, S.[Sedat],
Random Forest-Based Landslide Susceptibility Mapping in Coastal
Regions of Artvin, Turkey,
IJGI(9), No. 9, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Žabota, B.[Barbara],
Kobal, M.[Milan],
A New Methodology for Mapping Past Rockfall Events: From Mobile
Crowdsourcing to Rockfall Simulation Validation,
IJGI(9), No. 9, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Adnan, M.S.G.[Mohammed Sarfaraz Gani],
Rahman, M.S.[Md Salman],
Ahmed, N.[Nahian],
Ahmed, B.[Bayes],
Rabbi, M.F.[Md. Fazleh],
Rahman, R.M.[Rashedur M.],
Improving Spatial Agreement in Machine Learning-Based Landslide
Susceptibility Mapping,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link
2010
BibRef
Arabameri, A.[Alireza],
Karimi-Sangchini, E.[Ebrahim],
Pal, S.C.[Subodh Chandra],
Saha, A.[Asish],
Chowdhuri, I.[Indrajit],
Lee, S.[Saro],
Bui, D.T.[Dieu Tien],
Novel Credal Decision Tree-Based Ensemble Approaches for Predicting
the Landslide Susceptibility,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link
2010
BibRef
Kadirhodjaev, A.[Azam],
Rezaie, F.[Fatemeh],
Lee, M.J.[Moung-Jin],
Lee, S.[Saro],
Landslide Susceptibility Assessment Using an Optimized Group Method
of Data Handling Model,
IJGI(9), No. 10, 2020, pp. xx-yy.
DOI Link
2010
BibRef
Pradhan, A.M.S.[Ananta Man Singh],
Kim, Y.T.[Yun-Tae],
Rainfall-Induced Shallow Landslide Susceptibility Mapping at Two
Adjacent Catchments Using Advanced Machine Learning Algorithms,
IJGI(9), No. 10, 2020, pp. xx-yy.
DOI Link
2010
BibRef
Ghorbanzadeh, O.[Omid],
Didehban, K.[Khalil],
Rasouli, H.[Hamid],
Kamran, K.V.[Khalil Valizadeh],
Feizizadeh, B.[Bakhtiar],
Blaschke, T.[Thomas],
An Application of Sentinel-1, Sentinel-2, and GNSS Data for Landslide
Susceptibility Mapping,
IJGI(9), No. 10, 2020, pp. xx-yy.
DOI Link
2010
BibRef
Zhang, Y.[Yang],
Wu, W.C.[Wei-Cheng],
Qin, Y.Z.[Yao-Zu],
Lin, Z.Y.[Zi-Yu],
Zhang, G.L.[Gui-Liang],
Chen, R.X.[Ren-Xiang],
Song, Y.[Yong],
Lang, T.[Tao],
Zhou, X.T.[Xiao-Ting],
Huangfu, W.C.[Wen-Chao],
Ou, P.H.[Peng-Hui],
Xie, L.F.[Li-Feng],
Huang, X.L.[Xiao-Lan],
Peng, S.L.[Shan-Ling],
Shao, C.J.[Chong-Jian],
Mapping Landslide Hazard Risk Using Random Forest Algorithm in Guixi,
Jiangxi, China,
IJGI(9), No. 11, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Chen, W.[Wei],
Chen, Y.Z.[Yun-Zhi],
Tsangaratos, P.[Paraskevas],
Ilia, I.[Ioanna],
Wang, X.J.[Xiao-Jing],
Combining Evolutionary Algorithms and Machine Learning Models in
Landslide Susceptibility Assessments,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Tseng, C.W.[Chun-Wei],
Song, C.E.[Cheng-En],
Wang, S.F.[Su-Fen],
Chen, Y.C.[Yi-Chin],
Tu, J.Y.[Jien-Yi],
Yang, C.J.[Ci-Jian],
Chuang, C.W.[Chih-Wei],
Application of High-Resolution Radar Rain Data to the Predictive
Analysis of Landslide Susceptibility under Climate Change in the
Laonong Watershed, Taiwan,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Perrotti, M.[Michele],
Godone, D.[Danilo],
Allasia, P.[Paolo],
Baldo, M.[Marco],
Fazio, N.L.[Nunzio Luciano],
Lollino, P.[Piernicola],
Investigating the Susceptibility to Failure of a Rock Cliff by
Integrating Structure-from-Motion Analysis and 3D Geomechanical
Modelling,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Kovanic, L.[Ludovít],
Blistan, P.[Peter],
Urban, R.[Rudolf],
Štroner, M.[Martin],
Blištanová, M.[Monika],
Bartoš, K.[Karol],
Pukanská, K.[Katarína],
Analysis of the Suitability of High-Resolution DEM Obtained Using ALS
and UAS (SfM) for the Identification of Changes and Monitoring the
Development of Selected Geohazards in the Alpine Environment:
A Case Study in High Tatras, Slovakia,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Li, W.B.[Wen-Bin],
Fan, X.M.[Xuan-Mei],
Huang, F.[Faming],
Chen, W.[Wei],
Hong, H.Y.[Hao-Yuan],
Huang, J.S.[Jin-Song],
Guo, Z.Z.[Zi-Zheng],
Uncertainties Analysis of Collapse Susceptibility Prediction Based on
Remote Sensing and GIS: Influences of Different Data-Based Models and
Connections between Collapses and Environmental Factors,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Chen, W.[Wei],
Sun, Z.[Zenghui],
Zhao, X.[Xia],
Lei, X.[Xinxiang],
Shirzadi, A.[Ataollah],
Shahabi, H.[Himan],
Performance Evaluation and Comparison of Bivariate Statistical-Based
Artificial Intelligence Algorithms for Spatial Prediction of
Landslides,
IJGI(9), No. 12, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Lyimo, N.N.[Neema Nicodemus],
Shao, Z.[Zhenfeng],
Ally, A.M.[Ally Mgelwa],
Twumasi, N.Y.D.[Nana Yaw Danquah],
Altan, O.[Orhan],
Sanga, C.A.[Camilius A.],
A Fuzzy Logic-Based Approach for Modelling Uncertainty in Open
Geospatial Data on Landfill Suitability Analysis,
IJGI(9), No. 12, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Fang, Z.[Zhice],
Wang, Y.[Yi],
Duan, G.[Gonghao],
Peng, L.[Ling],
Landslide Susceptibility Mapping Using Rotation Forest Ensemble
Technique with Different Decision Trees in the Three Gorges Reservoir
Area, China,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Skrzypczak, I.[Izabela],
Kokoszka, W.[Wanda],
Zientek, D.[Dawid],
Tang, Y.J.[Yong-Jing],
Kogut, J.[Janusz],
Landslide Hazard Assessment Map as an Element Supporting Spatial
Planning: The Flysch Carpathians Region Study,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Jones, L.[Lee],
Hobbs, P.[Peter],
The Application of Terrestrial LiDAR for Geohazard Mapping,
Monitoring and Modelling in the British Geological Survey,
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
Landslide Susceptibility Models,
RS(13), No. 3, 2021, pp. xx-yy.
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
GeoDetector and Machine Learning Cluster: A Case of Xiaojin County,
China,
IJGI(10), No. 2, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Wang, X.L.[Xue-Liang],
Liu, H.[Haiyang],
Sun, J.[Juanjuan],
A New Approach for Identification of Potential Rockfall Source Areas
Controlled by Rock Mass Strength at a Regional Scale,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Khan, M.W.[Muhammad Waqas],
Dunning, S.[Stuart],
Bainbridge, R.[Rupert],
Martin, J.[James],
Diaz-Moreno, A.[Alejandro],
Torun, H.[Hamdi],
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],
Erbì, 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
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
Landslide Prediction,
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.[Yuting],
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.[Shiyu],
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.[Xinyi],
Fu, B.[Bihong],
Du, J.[Jie],
Shi, P.[Pilong],
Chen, Q.[Qingyu],
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.[Shuran],
Feng, G.C.[Guang-Cai],
Xiong, Z.Q.[Zhi-Qiang],
Wang, H.Y.[Hai-Yan],
Zhao, Y.[Yinggang],
Li, K.[Kaifeng],
Deng, K.[Kailiang],
Wang, Y.[Yuexin],
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:
Limitations and Openings,
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
Railway in Russia Using UAV Data,
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.[Chunfang],
Tian, Y.P.[Yi-Ping],
Ma, X.G.[Xiao-Gang],
Weng, Z.P.[Zheng-Ping],
Zhang, Z.[Zhiting],
Xu, K.[Kai],
Landslide Susceptibility Assessment Based on Different Machine
Learning Methods in Zhaoping County of Eastern Guangxi,
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
Analytic Hierarchy Process (AHP) Models for Landslide Susceptibility
Assessment,
IJGI(10), No. 9, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Hussain, M.A.[Muhammad Afaq],
Chen, Z.[Zhanlong],
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],
Wang, C.M.[Chang-Ming],
Liang, Z.[Zhu],
Gao, R.Y.[Rui-Yuan],
Li, B.L.[Bai-Long],
Exploring Complementary Models Consisting of Machine Learning
Algorithms for Landslide Susceptibility Mapping,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Xu, S.H.[Sheng-Hua],
Zhang, M.[Meng],
Ma, Y.[Yu],
Liu, J.P.[Ji-Ping],
Wang, Y.[Yong],
Ma, X.R.[Xin-Rui],
Chen, J.[Jie],
Multiclassification Method of Landslide Risk Assessment in
Consideration of Disaster Levels: A Case Study of Xianyang City,
Shaanxi Province,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Coco, L.[Laura],
Macrini, D.[Debora],
Piacentini, T.[Tommaso],
Buccolini, M.[Marcello],
Landslide Susceptibility Mapping by Comparing GIS-Based Bivariate
Methods: A Focus on the Geomorphological Implication of the
Statistical Results,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Ramos-Bernal, R.N.[Rocío N.],
Vázquez-Jiménez, R.[René],
Cantú-Ramírez, C.A.[Claudia A.],
Alarcón-Paredes, A.[Antonio],
Alonso-Silverio, G.A.[Gustavo A.],
Bruzón, A.G.[Adrián G.],
Arrogante-Funes, F.[Fátima],
Martín-González, F.[Fidel],
Novillo, C.J.[Carlos J.],
Arrogante-Funes, P.[Patricia],
Evaluation of Conditioning Factors of Slope Instability and
Continuous Change Maps in the Generation of Landslide Inventory Maps
Using Machine Learning (ML) Algorithms,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Pradhan, B.[Biswajeet],
Sameen, M.I.[Maher Ibrahim],
Al-Najjar, H.A.H.[Husam A. H.],
Sheng, D.[Daichao],
Alamri, A.M.[Abdullah M.],
Park, H.J.[Hyuck-Jin],
A Meta-Learning Approach of Optimisation for Spatial Prediction of
Landslides,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Rong, G.Z.[Guang-Zhi],
Li, K.[Kaiwei],
Su, Y.L.[Yu-Lin],
Tong, Z.J.[Zhi-Jun],
Liu, X.P.[Xing-Peng],
Zhang, J.[Jiquan],
Zhang, Y.C.[Yi-Chen],
Li, T.T.[Tian-Tao],
Comparison of Tree-Structured Parzen Estimator Optimization in Three
Typical Neural Network Models for Landslide Susceptibility Assessment,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Weidner, L.[Luke],
Walton, G.[Gabriel],
Monitoring the Effects of Slope Hazard Mitigation and Weather on
Rockfall along a Colorado Highway Using Terrestrial Laser Scanning,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Kavzoglu, T.[Taskin],
Teke, A.[Alihan],
Yilmaz, E.O.[Elif Ozlem],
Shared Blocks-Based Ensemble Deep Learning for Shallow Landslide
Susceptibility Mapping,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Liu, S.[Shuhao],
Yin, K.[Kunlong],
Zhou, C.[Chao],
Gui, L.[Lei],
Liang, X.[Xin],
Lin, W.[Wei],
Zhao, B.[Binbin],
Susceptibility Assessment for Landslide Initiated along Power
Transmission Lines,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Liu, R.[Ru],
Peng, J.B.[Jian-Bing],
Leng, Y.Q.[Yan-Qiu],
Lee, S.[Saro],
Panahi, M.[Mahdi],
Chen, W.[Wei],
Zhao, X.[Xia],
Hybrids of Support Vector Regression with Grey Wolf Optimizer and
Firefly Algorithm for Spatial Prediction of Landslide Susceptibility,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Loiotine, L.[Lidia],
Andriani, G.F.[Gioacchino Francesco],
Jaboyedoff, M.[Michel],
Parise, M.[Mario],
Derron, M.H.[Marc-Henri],
Comparison of Remote Sensing Techniques for Geostructural Analysis
and Cliff Monitoring in Coastal Areas of High Tourist Attraction: The
Case Study of Polignano a Mare (Southern Italy),
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Hu, J.Y.[Ji-Yuan],
Motagh, M.[Mahdi],
Wang, J.Y.[Jia-Yao],
Qin, F.[Fen],
Zhang, J.C.[Jian-Chen],
Wu, W.H.[Wen-Hao],
Han, Y.[Yakun],
Karst Collapse Risk Zonation and Evaluation in Wuhan, China Based on
Analytic Hierarchy Process, Logistic Regression, and InSAR Angular
Distortion Approaches,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Maxwell, A.E.[Aaron E.],
Sharma, M.[Maneesh],
Donaldson, K.A.[Kurt A.],
Explainable Boosting Machines for Slope Failure Spatial Predictive
Modeling,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Zhang, X.[Xuan],
Zhu, C.[Chun],
He, M.[Manchao],
Dong, M.L.[Meng-Long],
Zhang, G.[Guangcheng],
Zhang, F.[Faming],
Failure Mechanism and Long Short-Term Memory Neural Network Model for
Landslide Risk Prediction,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Zhao, P.X.[Peng-Xiang],
Masoumi, Z.[Zohreh],
Kalantari, M.[Maryam],
Aflaki, M.[Mahtab],
Mansourian, A.[Ali],
A GIS-Based Landslide Susceptibility Mapping and Variable Importance
Analysis Using Artificial Intelligent Training-Based Methods,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Karakas, G.,
Kocaman, S.,
Gokceoglu, C.,
Aerial Photogrammetry and Machine Learning Based Regional Landslide
Susceptibility Assessment for An Earthquake Prone Area In Turkey,
ISPRS21(B3-2021: 713-720).
DOI Link
2201
BibRef
Kim, S.S.,
Kim, D.Y.,
Nho, H.,
Risk Assessment of Steep Slope Using Drone Mapping and Terrestrial
LIDAR in Korea,
Gi4DM20(81-86).
DOI Link
2012
BibRef
Pesántez, P.C.,
Landslide Study Using Terrestrial Laser Scanner (LIDAR) Analysis,
ISPRS20(B3:1251-1256).
DOI Link
2012
BibRef
Yordanov, V.,
Brovelli, M.A.,
Comparing Model Performance Metrics for Landslide Susceptibility
Mapping,
ISPRS20(B3:1277-1284).
DOI Link
2012
BibRef
Karakas, G.,
Can, R.,
Kocaman, S.,
Nefeslioglu, H.A.,
Gokceoglu, C.,
Landslide Susceptibility Mapping with Random Forest Model for Ordu,
Turkey,
ISPRS20(B3:1229-1236).
DOI Link
2012
BibRef
Shin, D.Y.,
Sim, J.S.,
Lee, K.S.,
Application of The Steep Slope Risk Assessment Using Three Dimensional
Information Data,
Gi4DM19(381-386).
DOI Link
1912
BibRef
Redweik, P.,
Matildes, R.,
Marques, F.,
Geospatial Model for Large Scale Sea Cliff Rockfall Susceptibility
Mapping,
Gi4DM19(341-347).
DOI Link
1912
BibRef
Abujayyab, S.K.M.,
Karas, I.R.,
Low Data Requirements Framework for Landslide Susceptibility Prediction
Using 3d Alos Palsar Images and Neural Networks,
GGT19(47-54).
DOI Link
1912
BibRef
Javier, D.N.,
Kumar, L.,
Frequency Ratio Landslide Susceptibility Estimation in a Tropical
Mountain Region,
Gi4DM19(173-179).
DOI Link
1912
BibRef
Hasan, R.C.,
Rosle, Q.A.,
Asmadi, M.A.,
Mohamed Kamal, N.A.,
Extraction of Element At Risk for Landslides Using Remote Sensing
Method,
GeoDisast18(181-188).
DOI Link
1901
BibRef
Bibi, T.,
Gul, Y.,
Abdul Rahman, A.,
Riaz, M.,
Landslide Susceptibility Assessment Through Fuzzy Logic Inference
System (FLIS),
GGT16(355-360).
DOI Link
1612
BibRef
Chang, K.T.,
Dou, J.,
Chang, Y.,
Kuo, C.P.,
Xu, K.M.,
Liu, J.K.,
Spatial Resolution Effects Of Digital Terrain Models On Landslide
Susceptibility Analysis,
ISPRS16(B8: 33-36).
DOI Link
1610
BibRef
Lai, J.S.,
Tsai, F.,
Chiang, S.H.,
Integrating Geo-spatial Data For Regional Landslide Susceptibility
Modeling In Consideration Of Run-out Signature,
ISPRS16(B8: 89-93).
DOI Link
1610
BibRef
Mora, O.E.,
Lenzano, M.G.,
Toth, C.K.,
Grejner-Brzezinska, D.A.,
Analyzing the Effects of Spatial Resolution for Small Landslide
Susceptibility and Hazard Mapping,
LandImaging14(293-300).
DOI Link
1411
BibRef
Valenzuela, V.V.[Victor Vermehren],
Lins, R.D.[Rafael Dueire],
de Oliveira, H.M.[Hélio Magalhães],
Application of Enhanced-2D-CWT in Topographic Images for Mapping
Landslide Risk Areas,
ICIAR13(380-388).
Springer DOI
1307
BibRef
Blesius, L.,
Weirich, F.,
The use of high-resolution satellite imagery for deriving geotechnical
parameters applied to landslide susceptibility,
HighRes09(xx-yy).
PDF File.
0906
BibRef
Hasan, K.[Khaled],
Aanstoos, J.V.[James V.],
Mahrooghy, M.[Majid],
Stressed vegetation identification by SAR time series as an indicator
of slope instability in Mississippi River levee segments,
AIPR13(1-4)
IEEE DOI
1408
cracks
BibRef
Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Specific Site Landslide Analysis .