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<Article>
<Journal>
				<PublisherName>University of Tehran</PublisherName>
				<JournalTitle>Journal of Range and Watershed Managment</JournalTitle>
				<Issn>5044-2008</Issn>
				<Volume>70</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2017</Year>
					<Month>12</Month>
					<Day>22</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Modelling and Assessment of Landslide Susceptibility Zonation   (Case Study: Semirom Basin)</ArticleTitle>
<VernacularTitle>Modelling and Assessment of Landslide Susceptibility Zonation   (Case Study: Semirom Basin)</VernacularTitle>
			<FirstPage>921</FirstPage>
			<LastPage>939</LastPage>
			<ELocationID EIdType="pii">65326</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jrwm.2017.238368.1152</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>ALIREZA</FirstName>
					<LastName>Arabameri</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Kourosh</FirstName>
					<LastName>Shirani</LastName>
<Affiliation>esfahan</Affiliation>

</Author>
<Author>
					<FirstName>Khalil</FirstName>
					<LastName>Rezai</LastName>
<Affiliation>kharazmi university</Affiliation>

</Author>
<Author>
					<FirstName>Mojtaba</FirstName>
					<LastName>Yamani</LastName>
<Affiliation>tehran university</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2017</Year>
					<Month>07</Month>
					<Day>22</Day>
				</PubDate>
			</History>
		<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 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.</Abstract>
			<OtherAbstract Language="FA">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.</OtherAbstract>
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			<Object Type="keyword">
			<Param Name="value">landslide</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Regionalization</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">compound method</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Verification</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">ROC Curve</Param>
			</Object>
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<ArchiveCopySource DocType="pdf">https://jrwm.ut.ac.ir/article_65326_0178ca688ff2b4a4e6328ca150147695.pdf</ArchiveCopySource>
</Article>
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