scholarly journals COMBINING FUZZY LOGIC AND INFORMATION THEORY FOR PRODUCING A LANDSLIDE SUSCEPTIBILITY MODEL

2017 ◽  
Vol 50 (3) ◽  
pp. 1737
Author(s):  
P. Tsangaratos ◽  
I. Ilia
Keyword(s):  
Information Theory ◽  
Fuzzy Logic ◽  
Landslide Susceptibility ◽  
Shannon’S Entropy ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Landslide Susceptibility Map ◽  
Entropy Index ◽  
Shannon's Entropy ◽  
Susceptibility Model

The main objective of the present study was to develop a landslide susceptibility model by combining Fuzzy logic and Information Theory in order to estimate the spatial probability of landslide manifestation, in the mountains of central Tzoumerka, Greece. Specifically, Fuzzy logic was enabled for weighting the landslide related variables based on expert knowledge and in respect to landslide susceptibility, while the Shannon’s entropy index, an index from Information Theory, was calculated to weight the significance of each landslide related variable based on the available data. The final landslide susceptibility map was produced by applying the weighted sum method. Engineering lithological units, slope angle, slope aspect, distance from tectonic features, distance from river network and distance from road network were among the six landslide related variables that were included in the landslide database used in the training phase. The landslide inventory map was constructed by interpreting aerial photographs, satellite images and field surveys and was separated into two datasets, one for training and one for validating the model. The outcomes of the validation process illustrated that the developed methodology efficiently provided the most susceptible areas and was in good agreement with the actual landslide locations. The area under the curve was estimated to be for the training and validating datasets 0.7575 and 0.7828 respectively. The produced landslide susceptibility map could be regarded from local and national authorities as a valuable mean to evaluate strategies or to prevent and mitigate the impact of landslides. Keywords: slope stability, fuzzy weighting, Shannon’s entropy index, Tzoumerka, Greece.

scholarly journals Landslide susceptibility mapping by combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process in Dozain basin

2014 ◽  
Vol XL-2/W3 ◽  
pp. 267-272 ◽  
Author(s):  
E. Tazik ◽  
Z. Jahantab ◽  
M. Bakhtiari ◽  
A. Rezaei ◽  
S. Kazem Alavipanah
Keyword(s):  
Fuzzy Logic ◽  
Analytical Hierarchy Process ◽  
Landslide Susceptibility ◽  
Frequency Ratio ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Ahp Method ◽  
Landslide Susceptibility Map ◽  
Hierarchy Process ◽  
Process Method

Landslides are among the most important natural hazards that lead to modification of the environment. Therefore, studying of this phenomenon is so important in many areas. Because of the climate conditions, geologic, and geomorphologic characteristics of the region, the purpose of this study was landslide hazard assessment using Fuzzy Logic, frequency ratio and Analytical Hierarchy Process method in Dozein basin, Iran. At first, landslides occurred in Dozein basin were identified using aerial photos and field studies. The influenced landslide parameters that were used in this study including slope, aspect, elevation, lithology, precipitation, land cover, distance from fault, distance from road and distance from river were obtained from different sources and maps. Using these factors and the identified landslide, the fuzzy membership values were calculated by frequency ratio. Then to account for the importance of each of the factors in the landslide susceptibility, weights of each factor were determined based on questionnaire and AHP method. Finally, fuzzy map of each factor was multiplied to its weight that obtained using AHP method. At the end, for computing prediction accuracy, the produced map was verified by comparing to existing landslide locations. These results indicate that the <b>combining the three methods</b> Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process method are relatively good estimators of landslide susceptibility in the study area. According to landslide susceptibility map about 51% of the occurred landslide fall into the high and very high susceptibility zones of the landslide susceptibility map, but approximately 26 % of them indeed located in the low and very low susceptibility zones.

Production of Landslide Susceptibility Map using Bayesian Probability Model

2015 ◽  
Vol 4 (2) ◽  
pp. 16-33 ◽  
Author(s):  
Halil Akıncı ◽  
Ayşe Yavuz Özalp ◽  
Mehmet Özalp ◽  
Sebahat Temuçin Kılıçer ◽  
Cem Kılıçoğlu ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Planning ◽  
Landslide Susceptibility ◽  
Probability Model ◽  
Bayesian Probability ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Model Parameters ◽  
Operating Characteristics ◽  
Landslide Susceptibility Map

Artvin is one of the provinces in Turkey where landslides occur most frequently. There have been numerous landslides characterized as natural disaster recorded across the province. The areas sensitive to landslides across the province should be identified in order to ensure people's safety, to take the necessary measures for reducing any devastating effects of landslides and to make the right decisions in respect to land use planning. In this study, the landslide susceptibility map of the Central district of Artvin was produced by using Bayesian probability model. Parameters including lithology, altitude, slope, aspect, plan and profile curvatures, soil depth, topographic wetness index, land cover, and proximity to the road and stream were used in landslide susceptibility analysis. The landslide susceptibility map produced in this study was validated using the receiver operating characteristics (ROC) based on area under curve (AUC) analysis. In addition, control landslide locations were used to validate the results of the landslide susceptibility map and the validation analysis resulted in 94.30% accuracy, a reliable outcome for this map that can be useful for general land use planning in Artvin.

scholarly journals A new approach in the development and analysis of the landslide susceptibility map of the hillslopes of Bujumbura, Burundi

2021 ◽  
pp. 26-34
Author(s):  
Desire Kubwimana ◽  
Lahsen Ait Brahim ◽  
Abdellah Abdelouafi
Keyword(s):  
Landslide Susceptibility ◽  
Slope Angle ◽  
Landslide Inventory ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Landslide Susceptibility Map ◽  
Aerial Photos ◽  
Conditioning Factors ◽  
Mountainous Regions ◽  
Tropical Environments

As in other hilly and mountainous regions of the world, the hillslopes of Bujumbura are prone to landslides. In this area, landslides impact human lives and infrastructures. Despite the high landslide-induced damages, slope instabilities are less investigated. The aim of this research is to assess the landslide susceptibility using a probabilistic/statistical data modeling approach for predicting the initiation of future landslides. A spatial landslide inventory with their physical characteristics through interpretation of high-resolution optic imageries/aerial photos and intensive fieldwork are carried out. Base on in-depth field knowledge and green literature, let’s select potential landslide conditioning factors. A landslide inventory map with 568 landslides is produced. Out of the total of 568 landslide sites, 50 % of the data taken before the 2000s is used for training and the remaining 50 % (post-2000 events) were used for validation purposes. A landslide susceptibility map with an efficiency of 76 % to predict future slope failures is generated. The main landslides controlling factors in ascendant order are the density of drainage networks, the land use/cover, the lithology, the fault density, the slope angle, the curvature, the elevation, and the slope aspect. The causes of landslides support former regional studies which state that in the region, landslides are related to the geology with the high rapid weathering process in tropical environments, topography, and geodynamics. The susceptibility map will be a powerful decision-making tool for drawing up appropriate development plans in the hillslopes of Bujumbura with high demographic exposure. Such an approach will make it possible to mitigate the socio-economic impacts due to these land instabilities

scholarly journals Developing a Landslide Susceptibility Map Using the Analytic Hierarchical Process in Ta Van and Hau Thao Communes, Sapa, Vietnam

2021 ◽  
Vol 16 (4) ◽  
pp. 529-538
Author(s):  
Thi Thanh Thuy Le ◽  
The Viet Tran ◽  
Viet Hung Hoang ◽  
Van Truong Bui ◽  
Thi Kien Trinh Bui ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Landslide Susceptibility Mapping ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
High Susceptibility ◽  
Landslide Susceptibility Map ◽  
Landslide Occurrence ◽  
Mountainous Regions ◽  
Geological Conditions ◽  
Very High

Landslides are considered one of the most serious problems in the mountainous regions of the northern part of Vietnam due to the special topographic and geological conditions associated with the occurrence of tropical storms, steep slopes on hillsides, and human activities. This study initially identified areas susceptible to landslides in Ta Van Commune, Sapa District, Lao Cai Region using Analytical Hierarchy Analysis. Ten triggering and conditioning parameters were analyzed: elevation, slope, aspect, lithology, valley depth, relief amplitude, distance to roads, distance to faults, land use, and precipitation. The consistency index (CI) was 0.0995, indicating that no inconsistency in the decision-making process was detected during computation. The consistency ratio (CR) was computed for all factors and their classes were less than 0.1. The landslide susceptibility index (LSI) was computed and reclassified into five categories: very low, low, moderate, high, and very high. Approximately 9.9% of the whole area would be prone to landslide occurrence when the LSI value indicated at very high and high landslide susceptibility. The area under curve (AUC) of 0.75 illustrated that the used model provided good results for landslide susceptibility mapping in the study area. The results revealed that the predicted susceptibility levels were in good agreement with past landslides. The output also illustrated a gradual decrease in the density of landslide from the very high to the very low susceptible regions, which showed a considerable separation in the density values. Among the five classes, the highest landslide density of 0.01274 belonged to the very high susceptibility zone, followed by 0.00272 for the high susceptibility zone. The landslide susceptibility map presented in this paper would help local authorities adequately plan their landslide management process, especially in the very high and high susceptible zones.

scholarly journals Implementing Landslide Susceptibility Map at Watershed Scale of Lompobattang Mountain South Sulawesi, Indonesia

2018 ◽  
Vol 50 (2) ◽  
pp. 197
Author(s):  
Abdul Rachman Rasyid ◽  
Netra Prakash Bhandary ◽  
Ryuichi Yatabe
Keyword(s):  
Land Use ◽  
Landslide Susceptibility ◽  
Disaster Mitigation ◽  
Weight Of Evidence ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Watershed Scale ◽  
Landslide Susceptibility Map ◽  
Landslide Occurrence ◽  
Predictive Rate

This study attempts to predict future landslide occurrence at watershed scale and calculate the potency of landslide for each sub-watershed at Lompobatang Mountain. In order to produce landslide susceptibility map (LSM) using the statistical model on the watershed scale, we identified the landslide with landslide inventories that occurred in the past, and predict the prospective future landslide occurrence by correlating it with landslide causal factors. In this study, six parameters were used namely, distance from fault, slope, aspect, curvature, distance from river and land use. This research proposed the weight of evidence (WoE) model to produce a landslide susceptibility map. Success and predictive rate were also used to evaluate the accuracy by using Area under curve (AUC) of Receiver operating characteristic (ROC). The result is useful for land use planner and decision makers, in order to devise a strategy for disaster mitigation.

scholarly journals Evaluation of the Effect of Hydroseeded Vegetation for Slope Reinforcement

Land ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 995
Author(s):  
Okoli Jude Emeka ◽  
Haslinda Nahazanan ◽  
Bahareh Kalantar ◽  
Zailani Khuzaimah ◽  
Ojogbane Success Sani
Keyword(s):  
Landslide Susceptibility ◽  
Ground Cover ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Water Runoff ◽  
Operating Characteristics ◽  
Topographic Wetness Index ◽  
Landslide Susceptibility Map ◽  
Ahp Model ◽  
Slope Reinforcement

A landslide is a significant environmental hazard that results in an enormous loss of lives and properties. Studies have revealed that rainfall, soil characteristics, and human errors, such as deforestation, are the leading causes of landslides, reducing soil water infiltration and increasing the water runoff of a slope. This paper introduces vegetation establishment as a low-cost, practical measure for slope reinforcement through the ground cover and the root of the vegetation. This study reveals the level of complexity of the terrain with regards to the evaluation of high and low stability areas and has produced a landslide susceptibility map. For this purpose, 12 conditioning factors, namely slope, aspect, elevation, curvature, hill shade, stream power index (SPI), topographic wetness index (TWI), terrain roughness index (TRI), distances to roads, distance to lakes, distance to trees, and build-up, were used through the analytic hierarchy process (AHP) model to produce landslide susceptibility map. Receiver operating characteristics (ROC) was used for validation of the results. The area under the curve (AUC) values obtained from the ROC method for the AHP model was 0.865. Four seed samples, namely ryegrass, rye corn, signal grass, and couch, were hydroseeded to determine the vegetation root and ground cover’s effectiveness on stabilization and reinforcement on a high-risk susceptible 65° slope between August and December 2020. The observed monthly vegetation root of couch grass gave the most acceptable result. With a spreading and creeping vegetation ground cover characteristic, ryegrass showed the most acceptable monthly result for vegetation ground cover effectiveness. The findings suggest that the selection of couch species over other species is justified based on landslide control benefits.

scholarly journals Application Of Logistic Regression Method To Produce Landslide Susceptibility Map: A Case Study Of Tetouan Mazari, Morocco

2018 ◽  
Vol 149 ◽  
pp. 02082
Author(s):  
L. Ait Brahim ◽  
M. Elmoulat
Keyword(s):  
Logistic Regression ◽  
Land Use Planning ◽  
Landslide Susceptibility ◽  
Accurate Method ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Landslide Susceptibility Map ◽  
Logistic Regression Method ◽  
Validation Set

The main purpose of this study is to use logistic regression (RL) model to map landslide susceptibility in and around the area of Tetouan Mazari in the Northern Morocco. Parameters, such as lithology, slope gradient, slope aspect, faults, drainage lines, and hillshade, were considered. Landslide susceptibility map was produced using RL method and then compared and validated. Before the modeling and validation, the observed landslides were separated into two groups. The first group was for training, and the other group was for validation steps. The accuracy of the model was measured by fitting them to a validation set of observed landslides. For validation process, the half landslides remaining was used. The final map was classified into five classes: Very High (32%), High (40%), Medium (7%), Low (7%) and Nil (15%). According to these values logistic regression was determined to be one of the most accurate method to generate landslide susceptibility map. Last but not least, logistic regression model can be used to manage and mitigate hazards related to landslides and to aid in land-use planning for the city of Tetouan‥

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