相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。A novel combination approach for karst collapse susceptibility assessment using the analytic hierarchy process, catastrophe, and entropy model
Aihua Wei et al.
NATURAL HAZARDS (2021)
Monitoring, analyzing and predicting urban surface subsidence: A case study of Wuhan City, China
Qing Ding et al.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION (2021)
Present-day land subsidence rates, surface faulting hazard and risk in Mexico City with 2014-2020 Sentinel-1 IW InSAR
Francesca Cigna et al.
REMOTE SENSING OF ENVIRONMENT (2021)
A decade-long silent ground subsidence hazard culminating in a metropolitan disaster in Maceio, Brazil
Magdalena Vassileva et al.
SCIENTIFIC REPORTS (2021)
A Comparative Study of Frequency Ratio, Shannon's Entropy and Analytic Hierarchy Process (AHP) Models for Landslide Susceptibility Assessment
Sandeep Panchal et al.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION (2021)
Karst geology and mitigation measures for hazards during metro system construction in Wuhan, China
Xiuling Wang et al.
NATURAL HAZARDS (2020)
Ground Deformation of Wuhan, China, Revealed by Multi-Temporal InSAR Analysis
Yakun Han et al.
REMOTE SENSING (2020)
Evolution of sinkholes over Wink, Texas, observed by high-resolution optical, and SAR imagery
Jin-Woo Kim et al.
REMOTE SENSING OF ENVIRONMENT (2019)
Extracting sinkhole features from time-series of TerraSAR-X/TanDEM-X data
Sanaz Vajedian et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2019)
Sinkhole susceptibility mapping in Marion County, Florida: Evaluation and comparison between analytical hierarchy process and logistic regression based approaches
Praveen Subedi et al.
SCIENTIFIC REPORTS (2019)
InSAR Reveals Land Deformation at Guangzhou and Foshan, China between 2011 and 2017 with COSMO-SkyMed Data
Alex Hay-Man Ng et al.
REMOTE SENSING (2018)
Detection of Building and Infrastructure Instabilities by Automatic Spatiotemporal Analysis of Satellite SAR Interferometry Measurements
Mao Zhu et al.
REMOTE SENSING (2018)
A comparison of statistical and deterministic methods for shallow landslide susceptibility zoning in clayey soils
Mariantonietta Ciurleo et al.
ENGINEERING GEOLOGY (2017)
Wuhan Surface Subsidence Analysis in 2015-2016 Based on Sentinel-1A Data by SBAS-InSAR
Lv Zhou et al.
REMOTE SENSING (2017)
Sinkhole monitoring and early warning: An experimental and successful GB-InSAR application
Emanuele Intrieri et al.
GEOMORPHOLOGY (2015)
A review on natural and human-induced geohazards and impacts in karst
F. Gutierrez et al.
EARTH-SCIENCE REVIEWS (2014)
Karst collapse susceptibility mapping considering peak ground acceleration in a rapidly growing urban area
Kyriaki Papadopoulou-Vrynioti et al.
ENGINEERING GEOLOGY (2013)
Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea
Soyoung Park et al.
ENVIRONMENTAL EARTH SCIENCES (2013)
Instance sampling in credit scoring: An empirical study of sample size and balancing
Sven F. Crone et al.
INTERNATIONAL JOURNAL OF FORECASTING (2012)
Integrating geomorphological mapping, trenching, InSAR and GPR for the identification and characterization of sinkholes: A review and application in the mantled evaporite karst of the Ebro Valley (NE Spain)
Francisco Gutierrez et al.
GEOMORPHOLOGY (2011)
A seismological study of shallow weak micro-earthquakes in the urban area of Hamburg city, Germany, and its possible relation to salt dissolution
Torsten Dahm et al.
NATURAL HAZARDS (2011)
Space geodetic imaging of rapid ground subsidence in Mexico City
Enrique Cabral-Cano et al.
GEOLOGICAL SOCIETY OF AMERICA BULLETIN (2008)
Prediction of landslide susceptibility using rare events logistic regression: A case-study in the Flemish Ardennes (Belgium)
M. Van den Eeckhaut et al.
GEOMORPHOLOGY (2006)
The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan
L Ayalew et al.
GEOMORPHOLOGY (2005)
Decision-making with the AHP: Why is the principal eigenvector necessary
TL Saaty
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2003)
分享论文
