Titlebook: Statistical Approaches for Landslide Susceptibility Assessment and Prediction; Sujit Mandal,Subrata Mondal Book 2019 Springer Internationa

Truman

書目名稱Statistical Approaches for Landslide Susceptibility Assessment and Prediction影響因子(影響力)




書目名稱Statistical Approaches for Landslide Susceptibility Assessment and Prediction影響因子(影響力)學(xué)科排名




書目名稱Statistical Approaches for Landslide Susceptibility Assessment and Prediction網(wǎng)絡(luò)公開度




書目名稱Statistical Approaches for Landslide Susceptibility Assessment and Prediction網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Statistical Approaches for Landslide Susceptibility Assessment and Prediction被引頻次




書目名稱Statistical Approaches for Landslide Susceptibility Assessment and Prediction被引頻次學(xué)科排名




書目名稱Statistical Approaches for Landslide Susceptibility Assessment and Prediction年度引用




書目名稱Statistical Approaches for Landslide Susceptibility Assessment and Prediction年度引用學(xué)科排名




書目名稱Statistical Approaches for Landslide Susceptibility Assessment and Prediction讀者反饋




書目名稱Statistical Approaches for Landslide Susceptibility Assessment and Prediction讀者反饋學(xué)科排名

TEN

Geomorphic, Geo-tectonic, and Hydrologic Attributes and Landslide Probability, cover (LULC) were prepared in ARC GIS environment.?To assess the probability of each class of the landslide causative factors, frequency ratio (FR) value was estimated considering both landslide affected pixels and landslide non-affected pixels. The derived frequency ratio established the relations

遺產(chǎn)

Frequency Ratio (FR) Model and Modified Information Value (MIV) Model in Landslide Susceptibility AGoogle earth image, and some authorized?maps were processed in accordance with ArcMap 10.1 and Erdas imagine 9.2. To obtain the relative significance of each class/category of landslide conditioning factors, frequency ratio (FR) value and modified?information value (MIV) were estimated and according

DEBT

CEDE

Artificial Neural Network (ANN) Model and Landslide Susceptibility,to estimate factor’s weight and the landslide hazard indices were derived with the help of trained back-propagation weights. Then, the landslide susceptibility zonation map of Darjeeling Himalaya was made using GIS tool and classified into five, i.e. very low, low, moderate, high, and very low lands

鋼筆記下懲罰

撫慰

Knowledge-Driven Statistical Approach for Landslide Susceptibility Assessment Using GIS and Fuzzy Lcy ratio and cosine amplitude membership value. The accuracy study based on ROC curve revealed that the FR membership value based . and landslide susceptibility map having the accuracy result of 80.9% and cosine amplitude membership value based landslide susceptibility having the validation result o

陳舊

Comparison Between Statistical Models: A Review and Evaluation,50–2010) and some other information?were processed with the help of GIS. To integrate all the data layers and to prepare landslide susceptibility map, several models such as frequency ratio (FR) model, modified information value (MIV) model, logistic regression (LR) model, artificial neural network

準(zhǔn)則

盡管