Change detection of the land cover for three decades using remote sensing data and geographic information system
The changes in the land cover using geographical information systems and remote sensing techniques for the period (1990 - 2019) for part of the Baghdad governorate in central Iraq are detected and monitored. In this research, four satellite scenes with different sensors were used the TM, ETM+, and O...
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description | The changes in the land cover using geographical information systems and remote sensing techniques for the period (1990 - 2019) for part of the Baghdad governorate in central Iraq are detected and monitored. In this research, four satellite scenes with different sensors were used the TM, ETM+, and OLI, which were obtained by Landsat-5, Landsat-7 and Landsat-8 satellites, respectively. Maximum likelihood method supervised classification is adopted as the main classifier to distinguish different land cover types in the study region. The results showed that there are ten different classes in the values of their reflectance. This study proved that any landcover of the earth’s surface can be studied and determined by its spectral characteristics. The change for each class of the land cover for the study area was determined within the study period. The results of the study confirmed the possibility of identifying the types of land cover and finding the percentage of changes that occur in it and detecting it with high efficiency using the remote sensing technique. |
doi_str_mv | 10.1063/5.0033261 |
format | Conference Proceeding |
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In this research, four satellite scenes with different sensors were used the TM, ETM+, and OLI, which were obtained by Landsat-5, Landsat-7 and Landsat-8 satellites, respectively. Maximum likelihood method supervised classification is adopted as the main classifier to distinguish different land cover types in the study region. The results showed that there are ten different classes in the values of their reflectance. This study proved that any landcover of the earth’s surface can be studied and determined by its spectral characteristics. The change for each class of the land cover for the study area was determined within the study period. The results of the study confirmed the possibility of identifying the types of land cover and finding the percentage of changes that occur in it and detecting it with high efficiency using the remote sensing technique.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/5.0033261</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Change detection ; Earth surface ; Geographic information systems ; Information systems ; Land cover ; Landsat satellites ; Maximum likelihood method ; Remote sensing</subject><ispartof>AIP conference proceedings, 2020, Vol.2307 (1)</ispartof><rights>Author(s)</rights><rights>2020 Author(s). 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In this research, four satellite scenes with different sensors were used the TM, ETM+, and OLI, which were obtained by Landsat-5, Landsat-7 and Landsat-8 satellites, respectively. Maximum likelihood method supervised classification is adopted as the main classifier to distinguish different land cover types in the study region. The results showed that there are ten different classes in the values of their reflectance. This study proved that any landcover of the earth’s surface can be studied and determined by its spectral characteristics. The change for each class of the land cover for the study area was determined within the study period. The results of the study confirmed the possibility of identifying the types of land cover and finding the percentage of changes that occur in it and detecting it with high efficiency using the remote sensing technique.</description><subject>Change detection</subject><subject>Earth surface</subject><subject>Geographic information systems</subject><subject>Information systems</subject><subject>Land cover</subject><subject>Landsat satellites</subject><subject>Maximum likelihood method</subject><subject>Remote sensing</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2020</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNotUEtLxDAQDqLgunrwHwS8CV0nSZO0R1l8wYIXBW8lTabdLtumJllh_73dx2mY4XvNR8g9gwUDJZ7kAkAIrtgFmTEpWaYVU5dkBlDmGc_FzzW5iXEDwEutixkZl2sztEgdJrSp8wP1DU1rpFszOGr9Hwba-DCdAh5Q1jiMdBe7oaUBe5-QRhyOqzPJ0AOrRd8GM647S7thIvfmKBz3MWF_S64as414d55z8v368rV8z1afbx_L51U2cilSVjRKyqLGwtaTae2m5zQ6ZqwsHFdQN0WJnGlVawVlLbSDBpwqbF6CgEZLMScPJ90x-N8dxlRt_C4Mk2XFcw0MpCzzCfV4QkXbpWPMagxdb8K-YlAdGq1kdW5U_AMG_Glk</recordid><startdate>20201215</startdate><enddate>20201215</enddate><creator>Mohammed, Muna Aref</creator><creator>Hatem, Amal Jabbar</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20201215</creationdate><title>Change detection of the land cover for three decades using remote sensing data and geographic information system</title><author>Mohammed, Muna Aref ; Hatem, Amal Jabbar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p253t-8f6558be8cbdecbd1067ed1ac58d260bf89e2176b7609b37d0f0d68c49030f753</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Change detection</topic><topic>Earth surface</topic><topic>Geographic information systems</topic><topic>Information systems</topic><topic>Land cover</topic><topic>Landsat satellites</topic><topic>Maximum likelihood method</topic><topic>Remote sensing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mohammed, Muna Aref</creatorcontrib><creatorcontrib>Hatem, Amal Jabbar</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mohammed, Muna Aref</au><au>Hatem, Amal Jabbar</au><au>Salame, Chafic-Touma</au><au>Jabur, Akram R</au><au>Haider, Adawiya J</au><au>Shaban, Auday</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Change detection of the land cover for three decades using remote sensing data and geographic information system</atitle><btitle>AIP conference proceedings</btitle><date>2020-12-15</date><risdate>2020</risdate><volume>2307</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>The changes in the land cover using geographical information systems and remote sensing techniques for the period (1990 - 2019) for part of the Baghdad governorate in central Iraq are detected and monitored. In this research, four satellite scenes with different sensors were used the TM, ETM+, and OLI, which were obtained by Landsat-5, Landsat-7 and Landsat-8 satellites, respectively. Maximum likelihood method supervised classification is adopted as the main classifier to distinguish different land cover types in the study region. The results showed that there are ten different classes in the values of their reflectance. This study proved that any landcover of the earth’s surface can be studied and determined by its spectral characteristics. The change for each class of the land cover for the study area was determined within the study period. The results of the study confirmed the possibility of identifying the types of land cover and finding the percentage of changes that occur in it and detecting it with high efficiency using the remote sensing technique.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0033261</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Change detection Earth surface Geographic information systems Information systems Land cover Landsat satellites Maximum likelihood method Remote sensing |
title | Change detection of the land cover for three decades using remote sensing data and geographic information system |
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