Risk Assessment of water inrush under an unconsolidated, confined aquifer: the application of GIS and information value model in the Qidong Coal Mine, China

2021 ◽  
Author(s):  
Zhihong Peng ◽  
Luwang Chen ◽  
Xiaowei Hou ◽  
Qinghua Ou ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Coal Mine ◽  
Water Inrush ◽  
Information Value ◽  
Confined Aquifer ◽  
Information Value Model ◽  
Value Model ◽  
Application Of Gis

The Landslide Susceptibility Assessment using Bi-variate Statistical Information Value Model of Chenab River Valley, Jammu and Kashmir (India)

2021 ◽  
Vol 14 (11) ◽  
pp. 44-56
Author(s):  
Abhijit S. Patil ◽  
Bidyut K. Bhadra ◽  
Sachin S. Panhalkar ◽  
Sudhir K. Powar
Keyword(s):  
Landslide Susceptibility ◽  
Statistical Information ◽  
River Valley ◽  
Information Value ◽  
Landslide Inventory ◽  
Susceptibility Map ◽  
Acceptable Result ◽  
Information Value Model ◽  
Value Model ◽  
Chenab River

Almost every year, the Himalayan region suffers from a landslide disaster that is directly associated with the prosperity and development of the area. The study of landslide disasters helps planners, decision-makers and local communities for the development of anthropogenic structures in order to enhance the safety of society. Therefore, the prime aim of this research is to produce the landslide susceptibility map for the Chenab river valley using the bi-variate statistical information value model to detect and demarcate the areas of potential landslide incidence. The object-based image analysis method identified about 84 potential sites of landslides as landslide inventory. The statistical information value model is derived from the landslide inventory and multiple causative factors. The outcome showed that 23% area of the Chenab river valley falls into the class of a very high landslide susceptibility zone. The ROC curve method is used to validate the model which denoted the acceptable result for the landslide susceptibility zonation with 0.826 AUC value for the Chenab river valley.

An Empirical Development of Knowledge and Information Value Model

2009 ◽  
Vol 40 (1) ◽  
pp. 113-132
Author(s):  
Seung-Hoon Yoo ◽  
Jae-Yong Heo ◽  
Yoon-Gih Ahn
Keyword(s):  
Information Value ◽  
Information Value Model ◽  
Value Model

Realization of the Multi-Factor Combined Information Value Model in the Spatial Prediction of Landslides

2013 ◽  
Vol 734-737 ◽  
pp. 3163-3170
Author(s):  
Yu Feng Chen ◽  
Xue Lian Cao
Keyword(s):  
Influence Factors ◽  
Great Influence ◽  
Drainage System ◽  
Spatial Prediction ◽  
Information Value ◽  
Slope Aspect ◽  
Strongly Correlated ◽  
Information Value Model ◽  
Value Model ◽  
The Ideal

Information value model simplify the total information of evaluation unit down to sum of each factor, what may influence the prediction accuracy when factors are strongly correlated . Thus, its better to select the original modelthe multi-factor combined information value model, which directly calculate the information of factors-combination. However, the calculation is hard to realize due to the large number of combinations. In this paper, we propose a method that can quickly calculate the information. Taking Badong area for example, selecting slope, aspect, lithology, distance to drainage system and distance to road as influence factors, constructed the ideal information value model and the multi-factor combined information value model respectively. We found that the former model accuracy is 71.1%, with the latter is 80.3%. The result proved that the correlation between factors may have great influence, and showed the multi-factor combined information value model is better in a way.

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