Landslide hazard zone mapping using Information Value model: the case of Gidole Landslide, Southern Ethiopia

2020 ◽  
Author(s):  
Filagot Mengistu Walle ◽  
Karuturi Venkata Suryabhagavan ◽  
Tarun Raghuvanshi ◽  
Elias Lewi
Keyword(s):  
Causative Factor ◽  
Landslide Hazard ◽  
Information Value ◽  
Southern Ethiopia ◽  
Causative Factors ◽  
Hazard Zone ◽  
Information Value Model ◽  
High Hazard ◽  
Value Model ◽  
Factor Maps

<p>Landslide hazard is becoming serious environmental constraints for the developmental activities in the highlands of Ethiopia. With the current infrastructure development, urbanization, rural development, and with the present landslide management system, it is predictable that the frequency and magnitude of landslide and losses due to such hazards would continue to increase. In the present study landslide hazard zone mapping were carried out in and around Gidole Town in Southern Ethiopia. The main objective of the study was to map landslide hazard zone using Information Value Bi-variant statistical model.  For landslide hazard zonation of the study area six causative factors namely; aspect, slope angle, elevation, Lithology, Normalized Deference Vegetation Index (NDVI) and land-use and land-cover were considered. The landslide inventory mapping for the present study area was carried out through field observations and Google Earth image interpretation. Later, Information value was calculated based on the influence of causative factors on past landslide. The distribution of landslide over each causative factor maps was obtained and analyzed. Weights for the class with in these causative factor maps was obtained using information value model. Distribution of landslide in the study area was largely governed by aspect of southwest facing, slope angel of 30-45<sup>o</sup>, elevation of 1815–2150m, NDVI of 0.27−0.37, Lithology of colluvial deposit and land-use and land-cover of agricultural land. The landslide hazard zonation map shows that 78.38km<sup>2</sup> (36.3%) area fall within very low hazard (VLH) zone, 72.85km<sup>2</sup> (34.2%) of the area fall within low hazard (LH) zone, 12.78 km<sup>2</sup> (6.6%), 32.72 km<sup>2</sup> (15.4%) and 15.89 km<sup>2</sup> (7.5%) of the area falls into very high hazard (VHH), high hazard (HH) and moderate hazard (MH), respectively. Further, validation of LHZ map with past landslide inventory data shows that 92.3% of the existing landslides fall in very high hazard (VHH) and high hazard (VHH) zone. Thus, it can safely be concluded that the hazard zones delineated in the present study validates with the past landslide data and the potential zone depicted can reasonably be applied for the safe planning of the area.</p><p><strong>Key words</strong>: Landslide, Gidole, Landslide hazard zone, Information Value model</p>

Landslide Hazard Zonation and Slope Instability Assessment using Optical and InSAR Data: A Case Study from Gidole Town and its Surrounding Areas, Southern Ethiopia

2019 ◽  
Vol 3 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Filagot Mengistu ◽  
K.V. Suryabhagavan ◽  
Tarun Kumar Raghuvanshi ◽  
Elias Lewi
Keyword(s):  
Information Value ◽  
Slope Instability ◽  
Southern Ethiopia ◽  
Hazard Zonation ◽  
The Past ◽  
Causative Factors ◽  
Information Value Model ◽  
High Hazard ◽  
Value Model ◽  
Very High

The present study was carried out in and around Gidole Town in Southern Ethiopia which is about 580km from Addis Ababa. The main objective of the study was to prepare a landslide hazard zonation (LHZ) map by using Bivariat statistical information value model and to assess the slope instability in the area by using InSAR approach. For LHZ six causative factors such as; slope, land-use/land-cover, slope-material, elevation, aspect, and Normalized Difference Vegetation Index (NDVI) were considered. For the sub-classes of these causative factors weights were obtained from the information value model. The results showed that very high hazard zones and high hazard zones covers 6.63% (14.12 km2) and 15.36% (32.72 km2) of the area, respectively. Whereas, moderate hazard, low hazard and very low hazard zones covers 7.47% (15.9 km2), 34.2% (72.85 km2) and 36.34% (77.4 km2) of the area, respectively. Further, validation of the LHZ map showed that 92.3% of the past landslides fall in very high hazard and high hazard zones. Thus, the hazard zones delineated in the present study has reasonably validated with the past landslide data and the potential zones depicted in the prepared LHZ map can be applied for the safe planning of the area. Further, the results of the PS-InSAR processing indicates that the average downward displacement in the study area is gradually increasing from 15.3mm/yr (2014) to −19.2 mm/yr (2018) and the rate of displacement in general increases with increase in the average monthly precipitation at all selected persistence scattered points.

scholarly journals Landslide Susceptibility Assessment based on Information Value Model in Amzaz Watershed in Northern Morocco

2021 ◽  
Vol 2 (2) ◽  
pp. 3-19
Author(s):  
Abdelhak EL-FENGOUR ◽  
Carlos Bateira ◽  
Hanifa EL MOTAKI ◽  
Horacio García
Keyword(s):  
Information Value ◽  
Susceptibility Assessment ◽  
Individual Factor ◽  
Landslide Susceptibility Assessment ◽  
Susceptibility Maps ◽  
Information Value Model ◽  
Independent Variable ◽  
Value Model ◽  
Factor Maps ◽  
Iv Model

This paper aims to identify potential areas of landslides in the Amzaz watershed in northern Morocco with its precarious environmental balance using the Information Value (IV) Model. Van Westen (1994) defines bivariate methods as a modified form of the quantitative map combination with the exception that weightings are assigned based upon the statistical relationship between past landslides and various factor maps, individual factor maps (independent variable). A set of factor maps were overlaid with a landslide map (dependent variable) to create cross-tabulations for each one and class. The landslide inventory is used to result in the susceptibility maps for better mitigation of the risks and losses related to this phenomenon. The results demonstrated that the percentage of rotational landslides varies between 8.79 and 30.08%, and between 9.79 and 23.36% for translational slides susceptibility in the Amzaz watershed.

scholarly journals Evidence Based Landslide Hazard Mapping in Purworejo using Information Value Model Approach

2019 ◽  
Vol 33 (1) ◽  
pp. 25-38 ◽  
Author(s):  
Sudaryatno Sudaryatno ◽  
Prima Widayani ◽  
Totok Wahyu Wibowo ◽  
Bagus Wiratmoko ◽  
Wahyu Nurbandi
Keyword(s):  
Landslide Hazard ◽  
Information Value ◽  
Mitigation Strategies ◽  
Slope Aspect ◽  
Hazard Mapping ◽  
Susceptibility Map ◽  
Evidence Based ◽  
Information Value Model ◽  
Landslide Hazard Mapping ◽  
Value Model

Purworejo District, which is located in Central Java, Indonesia, is prone to landslides. These are a natural hazard that often occur in mountainous areas, so landslide hazard analysis is needed to develop mitigation strategies. This paper elaborates on the use of an evidence-based statistical approach using the Information Value Model (IVM) to conduct landslide hazard mapping. The parameters of slope, aspect, elevation, rainfall, NDVI, distance from rivers, distance from the road network, and distance from faults were employed for the analysis, which was conducted based on a raster data environment, since the pixel is the most appropriate means to represent continuous data. Landslide evidence data were collected by combining secondary data and interpreting satellite imagery to identify old landslides. The IVM was successfully calculated by combining factors related to disposition to landslides and data on 19 landslide occurrences. The results helped produce a landslide susceptibility map for the northern and eastern parts of Purworejo District.

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.

A multi-temporal landslide inventory and hazard zonation using relative effect method along the Mughal road Shopian, India

2021 ◽  
Vol 14 (7) ◽  
pp. 42-51
Author(s):  
Bashir Subiaya ◽  
T. Ramkumar
Keyword(s):  
Causative Factor ◽  
Statistical Technique ◽  
Relative Effect ◽  
Landslide Hazard ◽  
Landslide Inventory ◽  
Hazard Mapping ◽  
Mountain Range ◽  
Jammu And Kashmir ◽  
Hazard Zone ◽  
Effect Method

Landslide inventory and thematic data are of utmost importance in the domain of landslide hazard mapping. The union territory of Jammu and Kashmir, India surrounded by the Himalayan and the Pir-Panjal mountain range is prone to landslides and has already caused havoc at many places. The present study aims to provide the landslide inventory of the Mughal Road, Shopian, which lies in the Pir Panjal range of Kashmir valley. Multidate satellite data of the years 2008 to 2020 are utilized to create an inventory of landslides in this area.The use of high-resolution satellite imagery made it possible to delineate the shallow as well as the deep landslides along the roadside where they occur frequently. To understand the landslide causes, a statistical technique, relative effect method has been implemented in this study. This method helped in mapping the hazard zone areas. The relative effect of each causative factor on landslides is determined by calculating the ratio of coverage and slide which were analyzed in GIS environment. The resulting landslide hazard zone map has been classified as very low, low, moderate, high and very high zones. Out of the total area, 12.62% is critical to landslides, 21.45% is highly prone and 24.84% is moderately prone while 21.94% is low and 19.13% is very low prone to landslides. The outcome of this susceptibility modeling will be beneficial for handling and monitoring the forthcoming landslides as well as the fortification of the general public and environmental hazards of the study area. It will also help the planners in the development around the study area.

scholarly journals Landslide Hazard Zonation and Evaluation Around Debre Markos Town, NW Ethiopia—A GIS-Based Statistical Approach

2021 ◽  
Author(s):  
Dawit Asmare Manderso
Keyword(s):  
Research Area ◽  
Landslide Hazard ◽  
Hazard Zonation ◽  
Landslide Hazard Zonation ◽  
Zonation Map ◽  
Hazard Zone ◽  
High Hazard ◽  
Debre Markos ◽  
Moderate Hazard ◽  
Very High

Abstract The main goal of this research was to perform a landslide hazard zonation and evaluation around Debre Markos town, North West Ethiopia, found about 300 km from the capital city Addis Ababa. To achieve the aim, a GIS-based probabilistic statistical technique was used to rate the governing factors, followed by geoprocessing in the GIS setting to produce the landslide hazard zonation map. In this research, eight internal causative and external triggering factors were selected: slope material (lithology and soil mass), elevation, aspect, slope, land use land cover, curvature, distance to fault, and distance to drainage. Data were collected from field mapping, secondary maps, and digital elevation models. Systematic and detailed fieldwork had been done for image interpretation and inventory mapping. Accordingly, the past landslides map of the research area was prepared. All influencing factors were statistically analyzed to determine their relationship to previous landslides. The results revealed that 17.15% (40.60 km2), 25.53% (60.45 km2), 28.04% (66.39 km2), 18.93% (44.83 km2), and 10.36% (24.54 km2) of the research area falls under no hazard, low hazard, moderate hazard, high hazard, and very high hazard respectively. The validation of the landslide hazard zonation map reveals that 1%, 2%, 3%, and 94% of past landslides fall in no hazard zone, low hazard, moderate hazard zone, and high hazard or very high hazard zones respectively. The validation of the landslide hazard zonation map thus, it has been adequately demonstrated that the adopted approach has produced acceptable results. The defined hazard zones can practically be utilized for land management and infrastructure construction in the study area.

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
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