A Comparison of Fuzzy Analytic Hierarchy Process, Artificial Neural Network and Area Density in Quantitative Evaluation and Landslide Susceptibility Mapping within GIS Framework (Case Study: Simereh Homiyan 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.

Bakhtiyari Mohsen; komeh zinat; Memarian Hadi

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

Journal Paper

Paper Information

Journal: GEOGRAPHY AND ENVIRONMENTAL HAZARDS Year:2018 | Volume:7 | Issue:27 Page(s): 19-40

Download Full-Text

Persian Verion

View:

417

Download:

Cites:

Information Journal Paper

Title

A Comparison of Fuzzy Analytic Hierarchy Process, Artificial Neural Network and Area Density in Quantitative Evaluation and Landslide Susceptibility Mapping within GIS Framework (Case Study: Simereh Homiyan Watershed(

Author(s)

Bakhtiyari Mohsen | komeh zinat | Memarian Hadi | Issue Writer Certificate

Keywords

Landslide ZonationQ2

Artificial Neural NetworkQ2

Density AreaQ2

FAHPQ2

Abstract

Introduction Landslide is one of the major geomorphologic processes affecting the landscape's evolution in mountainous areas, which can lead to the catastrophic events (Hattanji & Moriwaki, 2009). Landslide Hazard Zonation (LHZ) is defined as dividing land into several regions and the classification of these areas, based on the actual or probable degree of susceptibility to landslides or other displacements of slopes (Varnes, 1984). For this purpose, the use of new technologies such as Geographic Information System and computational intelligence algorithms can be useful in preparing accurate maps of Landslide Zonation. In this study, three methods including Fuzzy Analytic Hierarchy Process (FAHP), Artificial Neural Network (ANN) and Area Density were employed as the representatives of two groups of decision making frameworks, i. e. non-deterministic computational and statistical methods in quantitative assessment. The efficiency of these approaches were examined, as well. This study was conducted in a part of Simereh Homiyan watershed with a large number of registered landslides to present an appropriate model for determining a geologic based efficient approach in Landslide Zonation. . Materials and Methods 2. 1. Study Area The study area is located in the west of Lorestan province with a geographical longitude of 47˚ 22' to 47˚ 52' and a geographical latitude of 33˚ 34' to 34˚ 9'. The study region with an area of 128, 000 hectares has an average altitude of 1620 meters above sea level (Baharand and Surri, 2015). 2. 1. 1. Information Layers In order to determine the effective criteria for landslide susceptibility mapping, we should use the factors that are able to solve the problem, and take into account the local and general situation of the region and existing constraints. The information layers used in this study, based on a consultation with watershed managers and geology experts were topographic layers, vegetation, relative humidity, depth of soil fracture, proximity to river, fault and road, and geological sensitivity layer. 2. 1. 2. Layer standardization Measurement of criteria in the form of information layers takes place with a wide range of scales. Therefore, the values in the various layers must be converted into the units that are comparable and proportionate. Verification In order to evaluate the accuracy of the results, the data of the landslides recorded in the study area were used based on simple random sampling in the areas with mass movements. Generally, 50% of the landslide records were used to train the employed techniques and the remaining were utilized in validation analysis. Results and Discussion Due to the number of layers provided for this study, the corresponding calculations were performed for each method. In sum, according to the type of training and experimental data used, the accuracy of the three methods used can be considered convincing; however, at the same time, the validity of the ANN and area density is significantly better than that of the FAHP. It could be due to the poor performance of the FAHP in pair comparisons. In other words, the opinions of the experts that should be involved in, impose some uncertainties in FAHP process. The highest accuracy for the ANN can be resulted from the proper functioning of this approach, which has been able to produce appropriate outputs by using appropriate training data and finding the internal relations of the target values and inputs. Conclusion Based on the results, the northern regions of the study area are prone to occurrence of landslide. On the other hand, the values of the verification parameters confirm the higher accuracy of the results of both neural network and surface area densities, respectively, with the overall accuracy of 0. 73 and 0. 71. Based on the comparison of the results, the FAHP method with a total accuracy of 0. 58 shows better performance. In general, the neural network method based on the validation statistics used include general accuracy, user authenticity and manufacturer's accuracy which are respectively with values of 0. 73, 0. 8, and 0. 59 and have the highest accuracy.

Cites

No record.

References

No record.

Cite

APA: Copy

Bakhtiyari, Mohsen, komeh, zinat, & Memarian, Hadi. (2018). A Comparison of Fuzzy Analytic Hierarchy Process, Artificial Neural Network and Area Density in Quantitative Evaluation and Landslide Susceptibility Mapping within GIS Framework (Case Study: Simereh Homiyan Watershed(. GEOGRAPHY AND ENVIRONMENTAL HAZARDS, 7(27 ), 19-40. SID. https://sid.ir/paper/226677/en

Vancouver: Copy

Bakhtiyari Mohsen, komeh zinat, Memarian Hadi. A Comparison of Fuzzy Analytic Hierarchy Process, Artificial Neural Network and Area Density in Quantitative Evaluation and Landslide Susceptibility Mapping within GIS Framework (Case Study: Simereh Homiyan Watershed(. GEOGRAPHY AND ENVIRONMENTAL HAZARDS[Internet]. 2018;7(27 ):19-40. Available from: https://sid.ir/paper/226677/en

IEEE: Copy

Mohsen Bakhtiyari, zinat komeh, and Hadi Memarian, “A Comparison of Fuzzy Analytic Hierarchy Process, Artificial Neural Network and Area Density in Quantitative Evaluation and Landslide Susceptibility Mapping within GIS Framework (Case Study: Simereh Homiyan Watershed(,” GEOGRAPHY AND ENVIRONMENTAL HAZARDS, vol. 7, no. 27 , pp. 19–40, 2018, [Online]. Available: https://sid.ir/paper/226677/en

Related Journal Papers