Performance assessment of integrated model of data driven EBF model and knowledge driven AHP model in Landslide spatial modeling (Case study: Ferydoun Shahr watershed)

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

ARABAMERI A.R.; REZAEI KH.; YAMANI M.; SHIRANI K.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of Water and Soil Conservation Year:2019 | Volume:25 | Issue:5 Page(s): 47-67

Download Full-Text

Persian Verion

View:

558

Download:

Cites:

Information Journal Paper

Title

Performance assessment of integrated model of data driven EBF model and knowledge driven AHP model in Landslide spatial modeling (Case study: Ferydoun Shahr watershed)

Author(s)

ARABAMERI A.R. | REZAEI KH. | YAMANI M. | SHIRANI K. | Issue Writer Certificate

Keywords

Data driven methodsQ1

Ferydoun Shahr watershedQ1

Knowledge driven methodsQ1

ValidationQ1

Abstract

Background and Objectives: During the past decades, landslides have been a significant subject of research as a consequence of their devastated nature. Landslides are common geomorphic processes in mountain areas and are responsible for mass movements involving rock materials, regolith and/or soil debris. For manufacture roads, railways, water pipe line and electric line, the preparation of landslide distribution map is very much significant. Determining the occurrence of future landslides depend on the geological, geomorphological and hydrological processes that led to instability in the past and also at present. To assessment terrain susceptibility to landslides, a number of various techniques are used, ranging from qualitative assessments based on expert judgment, which are intrinsically subjective to quantitative assessments based on advanced statistical techniques or mathematical models. The purpose of this research is landslide susceptibility mapping in Fereydoun Shahr watershed using a combination of data-driven and knowledge-based methods. Materials and Methods: The steps of methodologies that were applied in the current study, including six steps. Step1. data sources that are used in the current study including data related to field surveys, historical reports, topographic maps of 1: 50, 000-scale, meteorological data, geological map of 1: 100, 000-scale, A digital elevation model (DEM) with the resolution of 30 m × 30 m was extracted from the ASTER GDEM data, The Landsat 8 OLI images with the resolution of 30 m × 30 m. Step2. Preparing the inventory map. In this study, a landslide inventory map with a total of 80 landslide events was provided by the extensive field survey, Interpretation of aerial photos of 1995 with a scale of 1: 40000 by stereoscopy as well as satellite images of Google Earth. Step3. Landslide-conditioning factors. Step4. Multicolinearity analysis of landslide conditioning factors. In the current study, 12 factors were used as conditioning factors. These include elevation, slope, plan curvature, stream length, distance from streams, topography wetness index, surface area ratio, distance from roads, lithology, distance from faults, rainfall and land use. Step5. Combination of EBF data driven and AHP knowledge driven models according to the relation between the landslides location and the different datasets. Step5. Validation of models using AUC and SCAI indicators. Results: The results of the multicollinearity test among the parameters using Tolerance and variance inflation factor indicators showed that among the 26 initial conditioning factors, 14 factors have multicollinearity, As a result, this factors were eliminated from the modeling process and modeling was performed using 12 parameters. Results of the spatial relationship between landslide and conditioning factors using the EBF (belief, disbelief, uncertainty and plausibility) model revealed that high potential of landslide occurrence was for the areas with high degrees of belief and low degrees of disbelief. Weighting of conditioning factors by AHP showed that parameters of lithology, elevation and distance to road, slope and rainfall are the most effective prediction factors in landslide occurrence. The consistency ratio shows 0. 034 value, which is reasonably good accuracy value, which reflect the high accuracy of ranking consistency between the factors. Conclusion: Due to some shortening of the AHP knowledge driven and EBF data driven models when applied individually in landslide susceptibility mapping, it can be overcome by using ensemble techniques. The AUC results showed that the success rate and prediction rate for ensemble model are 0. 872 (78. 3%), 0. 903, respectively. results of SCAI values of the ensemble model is desirable, in the high and very high susceptibility classes. The resultant landslide susceptibility map show that the high susceptibility areas are mainly distributed along the northwest to west direction in the study area. This map can provide very useful information for planners, decision makers and engineers in slope management and land use planning in landslide areas.

Cites

No record.

References

No record.

Cite

APA: Copy

ARABAMERI, A.R., REZAEI, KH., YAMANI, M., & SHIRANI, K.. (2019). Performance assessment of integrated model of data driven EBF model and knowledge driven AHP model in Landslide spatial modeling (Case study: Ferydoun Shahr watershed). JOURNAL OF WATER AND SOIL CONSERVATION (JOURNAL OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES), 25(5 ), 47-67. SID. https://sid.ir/paper/156273/en

Vancouver: Copy

ARABAMERI A.R., REZAEI KH., YAMANI M., SHIRANI K.. Performance assessment of integrated model of data driven EBF model and knowledge driven AHP model in Landslide spatial modeling (Case study: Ferydoun Shahr watershed). JOURNAL OF WATER AND SOIL CONSERVATION (JOURNAL OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES)[Internet]. 2019;25(5 ):47-67. Available from: https://sid.ir/paper/156273/en

IEEE: Copy

A.R. ARABAMERI, KH. REZAEI, M. YAMANI, and K. SHIRANI, “Performance assessment of integrated model of data driven EBF model and knowledge driven AHP model in Landslide spatial modeling (Case study: Ferydoun Shahr watershed),” JOURNAL OF WATER AND SOIL CONSERVATION (JOURNAL OF AGRICULTURAL SCIENCES AND NATURAL RESOURCES), vol. 25, no. 5 , pp. 47–67, 2019, [Online]. Available: https://sid.ir/paper/156273/en

Related Journal Papers