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References from Landslide-oriented disaster resilience evaluation in mountainous cities: A case study in Chongqing, China. Local targets link to admitted publications; unresolved targets remain external evidence.
Emergency risk management for landslide dam breaks in 2018 on the Yangtze River, China
10.1016/j.rcns.2022.10.003 · 2022 · External reference
Deciphering decision-making mechanisms for the susceptibility of different slope geohazards: a case study on a SMOTE-RF-SHAP hybrid model
2024 · External reference
Comparison of GIS-based landslide susceptibility models using frequency ratio, logistic regression, and artificial neural network in a tertiary region of Ambon, Indonesia
10.1016/j.geomorph.2018.06.006 · 2018 · External reference
Landslide susceptibility modeling using Reduced Error Pruning Trees and different ensemble techniques: hybrid machine learning approaches
10.1016/j.catena.2018.12.018 · 2019 · External reference
Integrated natural disasters urban resilience evaluation: the case of China
10.1007/s11069-020-04478-8 · 2021 · External reference
Landslides-oriented urban disaster resilience assessment—A case study in ShenZhen, China
10.1016/j.scitotenv.2018.12.074 · 2019 · External reference
The concept of “Resilience”: history of formation and approaches to definition
2023 · External reference
Defining urban resilience: a review
10.1016/j.landurbplan.2015.11.011 · 2016 · External reference
Reviewing the use of resilience concepts in forest sciences
10.1007/s40725-020-00110-x · 2020 · External reference
10.1016/j.rcns.2022.03.002 · 2022 · Admitted local publication
A scientometric review of Urban Disaster Resilience Research
2021 · External reference
Multi-stage composition of urban resilience and the influence of pre-disaster urban functionality on urban resilience
10.1007/s11069-021-04590-3 · 2021 · External reference
Landslide risk, resilience and resistance: confronting community resilience with economic benefits in landslide-prone areas in Kerala
10.1504/ijem.2021.118769 · 2021 · External reference
The indispensable role of resilience in rational landslide risk management for social
2023 · External reference
An inclusive and adaptive framework for measuring social resilience to disasters
10.1016/j.ijdrr.2018.02.004 · 2018 · External reference
Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: a case study from the Tinau watershed, west Nepal
10.1016/j.cageo.2012.11.003 · 2013 · External reference
Machine learning methods for landslide susceptibility studies: a comparative overview of algorithm performance
10.1016/j.earscirev.2020.103225 · 2020 · External reference
Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling
10.1016/j.envsoft.2009.10.016 · 2010 · External reference
A random forest model of landslide susceptibility mapping based on hyperparameter optimization using Bayes algorithm
10.1016/j.geomorph.2020.107201 · 2020 · External reference
Comparison of landslide susceptibility maps using random forest and multivariate adaptive regression spline models in combination with catchment map units
10.1007/s12303-018-0038-8 · 2019 · External reference
Insights into spatial differential characteristics of landslide susceptibility from sub-region to whole-region cased by northeast Chongqing, China
10.1080/19475705.2023.2190858 · 2023 · External reference
An optimized random forest model and its generalization ability in landslide susceptibility mapping: application in two areas of three gorges reservoir, China
10.1007/s12583-020-1072-9 · 2020 · External reference
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Riverside landslide susceptibility overview: leveraging artificial neural networks and machine learning in accordance with the United Nations (UN) sustainable development goals
2023 · External reference
A review of statistically-based landslide susceptibility models
10.1016/j.earscirev.2018.03.001 · 2018 · External reference
Landslide susceptibility assessment at the Wuning area, China: a comparative between Multi-criteria decision making, bivariate statistical and machine learning methods
10.1007/s11069-018-3536-0 · 2019 · External reference
Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China
10.1016/j.scitotenv.2019.02.263 · 2019 · External reference
Assessment of landslide susceptibility mapping based on Bayesian hyperparameter optimization: a comparison between logistic regression and random forest
10.1016/j.enggeo.2020.105972 · 2021 · External reference
Novel GIS based machine learning algorithms for shallow landslide susceptibility mapping
10.3390/s18113777 · 2018 · External reference
Landslide susceptibility mapping using multiscale sampling strategy and convolutional neural network: a case study in Jiuzhaigou region
10.1016/j.catena.2020.104851 · 2020 · External reference
Impacts on watershed-scale runoff and sediment yield resulting from synergetic changes in climate and vegetation
10.1016/j.catena.2019.04.007 · 2019 · External reference
Optimization of landslide conditioning factors using very high-resolution airborne laser scanning (LiDAR) data at catchment scale
10.1016/j.rse.2014.05.013 · 2014 · External reference
Analyzing the effects of tectonic and lithology on the occurrence of landslide along Zagros ophiolitic suture: a case study of Sarv-Abad, Kurdistan, Iran
10.1007/s10064-019-01639-3 · 2020 · External reference
Comparative analysis for slope stability by using
2023 · External reference
Using provincial baseline indicators to model geographic variations of disaster resilience in Thailand
10.1007/s11069-015-1886-4 · 2015 · External reference
Building human resilience: the role of public health preparedness and response as an adaptation to climate change
10.1016/j.amepre.2008.08.022 · 2008 · External reference
What is social resilience? Lessons learned and ways forward
10.3112/erdkunde.2013.01.02 · 2013 · External reference
Disasters and communities: understanding social resilience
2007 · External reference
Like a fish out of water: reconsidering disaster recovery and the role of place and social capital in community disaster resilience
10.1007/s10464-011-9427-0 · 2011 · External reference
Towards resilient communities in developing countries through education of children for disaster preparedness
10.1504/ijem.2005.007355 · 2005 · External reference
Boundary crossing for urban community resilience: a social vulnerability and multi-hazard approach in Austin, Texas, USA
2021 · External reference
Study on the evaluation method and system of urban resilience in China
10.1007/s10669-023-09926-x · 2023 · External reference
Resilience assessment of urban communities
10.1061/ajrua6.0001004 · 2019 · External reference
Spatial prediction of landslide susceptibility using data mining-based kernel logistic regression, naive Bayes and RBFNetwork models for the Long County area (China)
10.1007/s10064-018-1256-z · 2019 · External reference
A spatially explicit deep learning neural network model for the prediction of landslide susceptibility
10.1016/j.catena.2019.104451 · 2020 · External reference
Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)
10.1080/19475705.2017.1407368 · 2018 · External reference
Machine learning methods for landslide susceptibility studies: a comparative overview of algorithm performance
10.1016/j.earscirev.2020.103225 · 2020 · External reference
Riverside landslide susceptibility overview: leveraging artificial neural networks and machine learning in accordance with the United Nations (UN) sustainable development goals
10.3390/w15152707 · 2023 · External reference
A novel hybrid integration model using support vector machines and random subspace for weather-triggered landslide susceptibility assessment in the Wuning area (China)
10.1007/s12665-017-6981-2 · 2017 · External reference
Rapid prediction of landslide dam stability considering the missing data using XGBoost algorithm
10.1007/s10346-022-01947-y · 2022 · External reference
Comparison of logistic regression and random forests techniques for shallow landslide susceptibility assessment in Giampilieri (NE Sicily, Italy)
10.1016/j.geomorph.2015.06.001 · 2015 · External reference
A novel performance assessment approach using photogrammetric techniques for landslide susceptibility mapping with logistic regression, ANN and random forest
10.3390/s19183940 · 2019 · External reference
GIS-based landslide susceptibility evaluation using a novel hybrid integration approach of bivariate statistical based random forest method
10.1016/j.catena.2018.01.012 · 2018 · External reference
10.1016/j.rcns.2024.03.001 · 2024 · Admitted local publication
Unraveling the evolution of landslide susceptibility: a systematic review of 30-years of strategic themes and trends
10.1080/10106049.2023.2256308 · 2023 · External reference
Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)
10.1080/19475705.2017.1407368 · 2018 · External reference
Comparison of logistic regression and random forests techniques for shallow landslide susceptibility assessment in Giampilieri (NE Sicily, Italy)
10.1016/j.geomorph.2015.06.001 · 2015 · External reference
Application of alternating decision tree with AdaBoost and bagging ensembles for landslide susceptibility mapping
10.1016/j.catena.2019.104396 · 2020 · External reference
Analytic Hierarchy Process and Expert Choice: benefits and limitations
10.1057/ori.2009.10 · 2009 · External reference
MCDM methods: practical difficulties and future directions for improvement
10.1051/ro/2022060 · 2022 · External reference
The ELECTRE multicriteria analysis approach based on Atanassov's intuitionistic fuzzy sets
10.1016/j.eswa.2011.04.010 · 2011 · External reference
Integration of convolutional neural network and conventional machine learning classifiers for landslide susceptibility mapping
10.1016/j.cageo.2020.104470 · 2020 · External reference
Using machine learning to build an early warning model for the risk of severe airflow limitation in patients with chronic obstructive pulmonary disease
2022 · External reference
Landslide susceptibility modeling applying machine learning methods: a case study from Longju in the Three Gorges Reservoir area, China
10.1016/j.cageo.2017.11.019 · 2018 · External reference
China's policy for the marine engineering equipment industry and potential challenges: an appraisal of the new developments under the 14th five-year plans
2022 · External reference
China's development plan for the utilization of foreign capita l during the 14th five-year period: prospects and analysis
10.14330/cwr.2022.8.2.05 · 2022 · External reference
Landslide Susceptibility mapping using random forest and extreme gradient boosting: a case study of Fengjie
2023 · External reference
Early appraisal of China's huge and complex health-care reforms
10.1016/s0140-6736(11)61880-1 · 2012 · External reference
Geography and development
10.1093/jeg/1.1.81 · 2001 · External reference
Resilience-vulnerability balance to urban flooding: a case study in a densely populated coastal city in China
10.1016/j.cities.2019.06.012 · 2019 · External reference
The adaptive capacity of institutions in the spatial planning, water, agriculture and nature sectors in the Netherlands
10.1007/s11027-014-9630-z · 2016 · External reference
The spatial-temporal evolution patterns of landslide-oriented resilience inmountainous city: a case study of Chongqing, China
10.1016/j.jenvman.2024.122963 · 2024 · External reference
