PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, Iran

In northern parts of Iran such as the Alborz Mountain belt, frequent landslides occur due to a combination of climate and geologic conditions with high tectonic activities. This results in millions of dollars of financial damages annually excluding casualties and unrecoverable resources. This paper...

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Main Authors: Jadda, Mehrnoosh, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri
Format: Article
Language:English
Published: Springer 2011
Online Access:http://psasir.upm.edu.my/id/eprint/22947/1/PFR%20model%20and%20GiT%20for%20landslide%20susceptibility%20mapping%20a%20case%20study%20from%20Central%20Alborz%2C%20Iran.pdf
http://psasir.upm.edu.my/id/eprint/22947/
http://link.springer.com/article/10.1007%2Fs11069-010-9620-8
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Institution: Universiti Putra Malaysia
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spelling my.upm.eprints.229472015-12-01T01:02:04Z http://psasir.upm.edu.my/id/eprint/22947/ PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, Iran Jadda, Mehrnoosh Mohd Shafri, Helmi Zulhaidi Mansor, Shattri In northern parts of Iran such as the Alborz Mountain belt, frequent landslides occur due to a combination of climate and geologic conditions with high tectonic activities. This results in millions of dollars of financial damages annually excluding casualties and unrecoverable resources. This paper evaluates the landslide susceptible areas in Central Alborz using the probabilistic frequency ratio (PFR) model and Geo-information Technology (GiT). The landslide location map in this study has been generated based on image elements interpreted from IRS satellite data and field observations. The display, manipulation and analysis have been carried out to evaluate layers such as geology, geomorphology, soil, slope, aspect, land use, distance from faults, lineaments, roads and drainages. The validation group of actual landslides and relative operation curve method has been used to increase the accuracy of the final landslide susceptibility map. The area under the curve evaluates how well the method predicts landslides. The results showed a satisfactory agreement of 91% between prepared susceptibility map and existing data on landslide locations. Springer 2011 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/22947/1/PFR%20model%20and%20GiT%20for%20landslide%20susceptibility%20mapping%20a%20case%20study%20from%20Central%20Alborz%2C%20Iran.pdf Jadda, Mehrnoosh and Mohd Shafri, Helmi Zulhaidi and Mansor, Shattri (2011) PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, Iran. Natural Hazards, 57 (2). pp. 395-412. ISSN 0921-030X; ESSN: 1573-0840 http://link.springer.com/article/10.1007%2Fs11069-010-9620-8 10.1007/s11069-010-9620-8
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description In northern parts of Iran such as the Alborz Mountain belt, frequent landslides occur due to a combination of climate and geologic conditions with high tectonic activities. This results in millions of dollars of financial damages annually excluding casualties and unrecoverable resources. This paper evaluates the landslide susceptible areas in Central Alborz using the probabilistic frequency ratio (PFR) model and Geo-information Technology (GiT). The landslide location map in this study has been generated based on image elements interpreted from IRS satellite data and field observations. The display, manipulation and analysis have been carried out to evaluate layers such as geology, geomorphology, soil, slope, aspect, land use, distance from faults, lineaments, roads and drainages. The validation group of actual landslides and relative operation curve method has been used to increase the accuracy of the final landslide susceptibility map. The area under the curve evaluates how well the method predicts landslides. The results showed a satisfactory agreement of 91% between prepared susceptibility map and existing data on landslide locations.
format Article
author Jadda, Mehrnoosh
Mohd Shafri, Helmi Zulhaidi
Mansor, Shattri
spellingShingle Jadda, Mehrnoosh
Mohd Shafri, Helmi Zulhaidi
Mansor, Shattri
PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, Iran
author_facet Jadda, Mehrnoosh
Mohd Shafri, Helmi Zulhaidi
Mansor, Shattri
author_sort Jadda, Mehrnoosh
title PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, Iran
title_short PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, Iran
title_full PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, Iran
title_fullStr PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, Iran
title_full_unstemmed PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, Iran
title_sort pfr model and git for landslide susceptibility mapping: a case study from central alborz, iran
publisher Springer
publishDate 2011
url http://psasir.upm.edu.my/id/eprint/22947/1/PFR%20model%20and%20GiT%20for%20landslide%20susceptibility%20mapping%20a%20case%20study%20from%20Central%20Alborz%2C%20Iran.pdf
http://psasir.upm.edu.my/id/eprint/22947/
http://link.springer.com/article/10.1007%2Fs11069-010-9620-8
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