Zahra Barati; Ebrahim Omidvar; Ataollah Shirzadi
Abstract
Landslide susceptibility mapping is considered as the first important step in landslide risk assessment. The main purpose of this study is to compare the performance of a machine learning algorithm (a logistic model tree), and a statistical model (a logistic regression), for landslide susceptibility ...
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Landslide susceptibility mapping is considered as the first important step in landslide risk assessment. The main purpose of this study is to compare the performance of a machine learning algorithm (a logistic model tree), and a statistical model (a logistic regression), for landslide susceptibility modeling in the Sarkhoon watershed, Chaharmahal and Bakhtiari province. For this purpose, at first, a landslide inventory map including a total of 98 landslide locations was constructed using historical landslides, and extensive field surveys. In addition, a total of 100 non-landslide locations were also identified to construct a database. The landslide and non-landslide locations were randomly selected and divided into two groups with a 70/30 ratio for modelling and validation processes. Twenty conditioning factors were selected based on literature review and geo-environmental properties in the study area. Subsequently, the logistic model tree (LMT) and the logistic regression (LR) models were applied to identify the influence of conditioning factors on landslide occurrence. Finally, the performance of the models in landslide susceptibility mapping was investigated using the area under the receiver operating characteristics curve (AUC). The results concluded that the LR model (AUC = 0.797) outperformed and outclassed the LMT (AUC = 0.740) model in the study area. Although both models were reliable tools for spatial prediction of landslide susceptibility; however, the LR model was more accurate that it can be proposed as an alternative tool for better management of areas prone to landslide in the study area.
Asghar Kouhpeima; Sadat Feiznia
Abstract
Landslide causes many social and economic losses in many parts of the world every year. These losses can be greatly reduced by using appropriate management measures such as mapping landslide susceptibility mapping in the basin. The aim of this study is landslide susceptibility mapping using Mahalanobis ...
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Landslide causes many social and economic losses in many parts of the world every year. These losses can be greatly reduced by using appropriate management measures such as mapping landslide susceptibility mapping in the basin. The aim of this study is landslide susceptibility mapping using Mahalanobis distance in the Latyan catchment. First, a total of 208 cases of landslides identificated and geo-referenced using geographic information systems based on an interpretation of aerial photographs and extensive field surveys and provided a landslide inventory map. The map of 12 factors, including rainfall, land use, distance to fault, distance from river, distance from road, lithology, altitude, slope, aspect, plan curvature, Peak Ground Acceleration and topographic wetness index as the most important factors in landslides was prepared. Then the correlating each factor and the landslide was examined. Finally landslide susceptibility zoning map was provided based on the Mahalanobis distance in Latyan catchment. To evaluate the results, the ROC and chi-square tests were used. The results show more than 80 % of the catchment located in range of high and very high susceptibility classes and need to suitable management operations. AUC index (area under the curve ROC) for this model is achieved to 0.896 or 89.6% which represent capability and high accuracy. Chi-square test results also reflect the proper separation of landslide susceptibility classes by model.
ALIREZA Arabameri; kourosh shirani; khalil rezai; mojtaba yamani
Abstract
landslides situation recognized using interpreting the aerial photos and extensive field measurements. Among total number of 200 identified landslides, %70 (140 landslides) of them have been utilized for model executing and %30 (60 landslides) of them for verification randomly. This research criteria ...
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landslides situation recognized using interpreting the aerial photos and extensive field measurements. Among total number of 200 identified landslides, %70 (140 landslides) of them have been utilized for model executing and %30 (60 landslides) of them for verification randomly. This research criteria including geomorphological parameters, hydrological parameters , geological parameters and environmental parameters . The Shannon’s entropy model have been used for defining the criteria weight and Area density model for defining classes weight, then the regionalization map obtained by combining the criteria and classes weight in ArcGIS 10.2 software environment and classified to 5 classes very little, little , moderate, high and very high according to natural fractures. The Roc curve have been used for model verification. The clerical accuracy results indicated that the compound model have the high accuracy 0.877 (87.7%) for identifying the regions susceptible to landslide. According to the results, slope length, slope and topography wetness index have had the most effect in occurring the landslide. Among total area of region (168547 hectar), 27.39% (46165.02 hectar) have been placed in high and very high sensitive. The prepared regionalization map can be useful for planning land use and building the infrastructure installations such as road.
Ommolbanin Kazemi Gordgi; Hasan Ahmadi; Mohammad Jafari
Abstract
The ultimate aim of any research on the mass movement processes is to prepare zonation map and classify area into different degrees of hazard in order to mitigating related damages. This study was undertaken using F-AHP & GIS within Nekaroud watershed in Mazandaran province. Pairwise comparisons ...
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The ultimate aim of any research on the mass movement processes is to prepare zonation map and classify area into different degrees of hazard in order to mitigating related damages. This study was undertaken using F-AHP & GIS within Nekaroud watershed in Mazandaran province. Pairwise comparisons showed that sub-criteria’s Slope (>30%), elevation (> 1700 m), distance from fault (0-200 meter), distance from river, residual land-use and precipitation (>600 mm) have high weight than others in their group which lead to increasing occurrence of landslides. In the study area much amount of lime stone was found which is effective in reducing landslide. Major parts of central areas of watershed are prone to the most dangerous and high frequency landslides, other parts of watershed classified into medium and a little part is in low danger class.
Payam Ebrahimi; mehdi Eslah; Maryam Azarakhshi
Abstract
One kind of the mass wasting which takes much toll and leaves much damage in the world and many locations in Iran is landslide. Landslide susceptibility mapping allows recognizing susceptible areas to be considered in environmental programs. Present research is aimed at Landslide susceptibility mapping ...
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One kind of the mass wasting which takes much toll and leaves much damage in the world and many locations in Iran is landslide. Landslide susceptibility mapping allows recognizing susceptible areas to be considered in environmental programs. Present research is aimed at Landslide susceptibility mapping in Hafshejan watershed in Chaharmahal-o-Bakhtiari province using Spatial Multi Criteria Evaluation (SMCE) method via geographic information system (GIS) and ILWIS software and AHP technic. Therefore, regarding the sites where landslides occurred, comparative studies, and the findings of other scholars, eight informational layers were identified for this research. Then, the tree of factors and restrictions was designed in ILWIS software. All layers were standardized and were evaluated and weighted applying AHP model. Last but not least, upshot model and landslide hazard zonation map were prepared and presented for the relevant study area. It was found out that from among effective factors, distance from road, distance from fault and distance from stream of 0.4047, 0.2239 and 0.1302 weight respectively are the most important factors triggering landslide in study area. According to the presented model, about 1.32 percent of watershed area (1013900 square meters) is extremely high risk and 9 percent (6909800 square meters) is high risk. The results of accuracy evaluation of the presented model are indicative of ascendantal trend of landslide index from very low hazard zone to very high hazard zone and they are indicative of sufficient precision of this model.
Alireza Motevali; Ali Talebi; Mehrdad Safaei; Mohammadreza Ekhtesasi
Abstract
Landslide is one of the most important geological phenomena in northern slopes of Iran (Alborz) which causes considerable damages gradually. In the last few years, due to unfavorable changes in land uses and increasing degradation of pastures, forests and farmlands as well as implementation of inappropriate ...
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Landslide is one of the most important geological phenomena in northern slopes of Iran (Alborz) which causes considerable damages gradually. In the last few years, due to unfavorable changes in land uses and increasing degradation of pastures, forests and farmlands as well as implementation of inappropriate development projects in areas prone to landslides, geology formation prone to landsliding, rainfall rate and steep slopes, the occurance of this destructive phenomenon has constantly increased. In this research, landslides which occurred around Sari-Kiasar road were investigated using physically based models i.e. SINMAP and SHALSTAB and the stability map of the region was determined applying these models. First, the physical and mechanical properties of soils in 13 points were measured and evaluated by 56 landslide points. The results of field studies, laboratory samples, running models and data analysis showed that these models (SINMAP and SHALSTAB) have success rate equal to 87.3 % and 69.5%, respectively for predicting the slope instability in ChaharDonge region. This means that the SINMAP model has more efficiency than SHALSTAB model for slope stability analysis.
Elham Meshkati; Hassan Ahmadi; Aliakbar Nazari Samani; M.H Davoodi
Abstract
Landslide occurs inevitably and naturally in many slopes due to sensitive formations, moisture, andother factors. Taleghan watershed is prone to landslide due to the presence of huge Miocene marlmasses. After construction of Taleghan reservoir dam, moisture and ecological condition of theregion changed. ...
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Landslide occurs inevitably and naturally in many slopes due to sensitive formations, moisture, andother factors. Taleghan watershed is prone to landslide due to the presence of huge Miocene marlmasses. After construction of Taleghan reservoir dam, moisture and ecological condition of theregion changed. In this paper, factors impacting upon landslide hazard (slope, aspect, hypsometry,geology, land use, distance to road, distance to lake) were studied and their role and importance onthis phenomenon were verified in a large (maximum distance of 1500 meter from lake) and a small(maximum distance of 450 meter from lake) spatial scale. Thus, GIS maps of the above mentionedparameters were provided using satellite and aerial images and field activities. All maps werecrossed with a resolution of 100m*100m. It was found out that the distance to the lake didn’tinfluence upon landslide in a large spatial scale but it falls effective as the distance to the lakereduces. In fact lake has a local effect and mostly influences at maximum 200 meter distance.
Hamid Reza Moradi
Abstract
ABSTRACT Aim Of this research is landslide hazard zoning in Syahdare watershed using logistic regression. Therefore, outset landslide points recognized using air photography and extensive field studies. Then distribution of landslide map was makes. Then each effective element on landslide occurred for ...
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ABSTRACT Aim Of this research is landslide hazard zoning in Syahdare watershed using logistic regression. Therefore, outset landslide points recognized using air photography and extensive field studies. Then distribution of landslide map was makes. Then each effective element on landslide occurred for example slope, aspect, elevation, litho logy, land use, distance of road, distance of drainage, distance of fault and precipitation map makes in GIS environment. These data were saved in raster and vector format in GIS soft ware and they used for analysis with logistic regression. Logistic analysis obtained by Arc GIS 9.2 soft ware and SPSS. Results showed the most important elements in Land slide occurred in this area are slope, elevation, precipitation, distance of drainage and distance of fault respectively. Most of the land slides have occurred in the classes of 10 to 15 degree slope, elevation of 2350-2500 meters, precipitation (473-523 mm) are located. 50% Landslide is located at a distance of 30 meters of the stream. In this region the most landslides are occurrence in the 300 meter to fault distance. While the from 500 meter distance to the fault reduced number and susceptibility to landslides. The evaluation of accuracy model and the results obtained with three methods for the presence of all variables, 98.2 percent, 0.692 and 0.519 respectively. So showed that logistic regression had high accuracy in making landslide susceptibility map in study area.
Ebrahim Omidvar; Ataollah Kavian
Abstract
Landslides are the major natural hazard, causing significant damage to properties, lives and engineering projects in all mountainous areas in the world. In order to estimate the role of the landslides in erosion processes and evaluation of their risks, it is necessary to quantify landslides. This quantifying ...
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Landslides are the major natural hazard, causing significant damage to properties, lives and engineering projects in all mountainous areas in the world. In order to estimate the role of the landslides in erosion processes and evaluation of their risks, it is necessary to quantify landslides. This quantifying can be performed by applying the probability distributions that show the landslide size against the probability density. This study was investigated the behavior of landslide areas and volumes on Frequency distributions in Mazandaran province. Also total number, area and volume of landslides that have occurred over time were estimated using the approach suggested by Malamud et al. Result of cumulative frequency distribution of landslide area and volume revealed the significant proportion of large landslides in determining the total landslide area and volume. According to Malamud et al. approach total number of landslides were estimated to be 9823±2323. These landslides have been obliterated over the time by soil erosion, vegetation growth or by human activities and total of their affected area and volume by these landslides were 31.5±7.1 km2 and 0.232±0.052 km3, respectively. The obtained results also presented an area of 2×10-3 km2 as a critical threshold area for transition between resistances against slope failure.
Koroosh Shirani; Mohammadreza Haji Hashemi Jazi; Seyyed Ali Niknejad; Soleiman Rakhsha
Abstract
In western and southern watersheds of Isfahan province, combinations of natural and human factors have caused numerous landslides related damages. One of the main strategies for restricting the damage caused by the landslide is to avoid these regions. For this purpose, it is necessary to prepare precise ...
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In western and southern watersheds of Isfahan province, combinations of natural and human factors have caused numerous landslides related damages. One of the main strategies for restricting the damage caused by the landslide is to avoid these regions. For this purpose, it is necessary to prepare precise landslide hazard zonation map for such areas. For this purpose, by aerial photos, satellite images, geological maps and field studies , landslide inventory map was prepared in of the upstream watersheds of Karoon Basin called Marber River Basin with an area of 800 square kilometers. Then, nine factors including lithology, slope, land use, rainfall, vegetation cover, aspect, and lineaments elements such as road, fault and drainages were studied as 54 parameters. To enhance accuracy, speed and ease of analysis, all spatial and descriptive data were interred into GIS and 27466 homogeneous units were obtained by overlapping of the mentioned map layers. Analytical Hierarchy Process (AHP) and Multivariate Regression (MR) were used for multi criteria decision analysis and the results showed that both methods have the same accuracy in the separation of zones (lines) with the specific index of landslide risk.. But AHP approach of regression data, based on total quality index as an indicator of the accuracy of the learning has higher acceptability. This is related to this fact that the method has considered all 54 effective parameters due to the inherent performance of natural phenomena and events involved with the landslide. Based on multivariate regression method, only 30 of 54 variables were significant at 95% and 99% levels and r coefficient of regression equation was 57% which is quite acceptable
Hamidreza Moradi; Alireza Sepahvand; Parviz Abdolmaleki
Abstract
More than 30% of Iran's land is formed from mountainous areas. So each year, landslides cause damages to structures, residential areas and forests, creating sedimentation, muddy floods and finally deposit the sediments in reservoir dams. Therefore, for preventing of this damages and expressing the sensitivity ...
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More than 30% of Iran's land is formed from mountainous areas. So each year, landslides cause damages to structures, residential areas and forests, creating sedimentation, muddy floods and finally deposit the sediments in reservoir dams. Therefore, for preventing of this damages and expressing the sensitivity rate of hillslopes, landslide hazard zonation is considered in prone areas. The purpose of this study is to determine the optimal structure of artificial neural network with different numbers of input factors for the landslide hazard zonation in the Haraz Watershed. First, the number of optimal epochs was determined to prevent network overlearning with trial and error method. Then, 14 neurons were determined in the hidden layer. Finally, the number of neurons was changed from 1 to 9 in the input layer. According to the obtained results, with increasing the number of neurons in the input layer, efficiency of Artificial Neural Network improved for landslide susceptibility mapping. In this research, nine neurons in the input layer, 14 neurons in the hidden layer and one neuron in the output layer were selected as the optimal structure. Root Mean Square Error and Descriptive Coefficient (R2) were equal to 0.051 and 0.962, respectively and the accuracy of landslide hazard zonation map was equal to 92.3%. Meanwhile, the results showed that about 35.14, 26.73, 14.59, 9.88, and 13.63 percent of all studied areas are located in stable, low, moderate, high and extremely hazardous areas, respectively.
