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<Article>
<Journal>
				<PublisherName>National Geographical Organization</PublisherName>
				<JournalTitle>Scientific- Research Quarterly of Geographical Data (SEPEHR)</JournalTitle>
				<Issn>2588-3860</Issn>
				<Volume>21</Volume>
				<Issue>83</Issue>
				<PubDate PubStatus="epublish">
					<Year>2012</Year>
					<Month>10</Month>
					<Day>22</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Preparation of Infiltration Levels Mapping as an Environmental Indicator</ArticleTitle>
<VernacularTitle>Preparation of Infiltration Levels Mapping as an Environmental Indicator</VernacularTitle>
			<FirstPage>65</FirstPage>
			<LastPage>69</LastPage>
			<ELocationID EIdType="pii">26241</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Azadeh</FirstName>
					<LastName>Zaeri Amirani</LastName>
<Affiliation>Isfahan University</Affiliation>

</Author>
<Author>
					<FirstName>Alireza</FirstName>
					<LastName>Sofyanian</LastName>
<Affiliation>Isfahan University</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2012</Year>
					<Month>03</Month>
					<Day>31</Day>
				</PubDate>
			</History>
		<Abstract>Accessing correct and timely information about urban land use and coverage is especially important for urban planning and management, achieving sustainable development in urban areas and optimal application of land.Impenetrable surfaces are a part of urban coverage with an effective role in changing landform and the quality of urban environment. Regarding the importance of such surfaces, different methods of mapping impenetrable surfaces and investigating its changes with satellite imagery exist. These methods can be classified into five general groups: subpixel classification, neural network, classification with VIS model, regression tree model, and spectral composition analysis. Generally, each of these methods have their own advantages and disadvantages, but they are mostly used to detect and classify impenetrable surfaces. The present article investigate impenetrable surfaces and their importance, along with different methods of mapping these surfaces.</Abstract>
			<OtherAbstract Language="FA">Accessing correct and timely information about urban land use and coverage is especially important for urban planning and management, achieving sustainable development in urban areas and optimal application of land.Impenetrable surfaces are a part of urban coverage with an effective role in changing landform and the quality of urban environment. Regarding the importance of such surfaces, different methods of mapping impenetrable surfaces and investigating its changes with satellite imagery exist. These methods can be classified into five general groups: subpixel classification, neural network, classification with VIS model, regression tree model, and spectral composition analysis. Generally, each of these methods have their own advantages and disadvantages, but they are mostly used to detect and classify impenetrable surfaces. The present article investigate impenetrable surfaces and their importance, along with different methods of mapping these surfaces.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Remote Sensing</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">impenetrable surfaces</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Classification</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">detecting changes</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://www.sepehr.org/article_26241_b62fc92a2561538525c89be63f36bf7b.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
