Spatio-temporal analysis of river channel pattern in lower course of River Ravi using GIS and remote sensing
This study aims to detect changes that occurred in Ravi River channel over the period of last three decades (1990 to 2020). This paper spatially and temporally assesses the changes and geo-visualize variation of Ravi River using Landsat imageries. The maximum likelihood image classification techniqu...
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| Veröffentlicht in: | Applied geomatics 2023-09, Vol.15 (3), p.759-772 |
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| creator | Huda, Noor-ul Mahmood, Shakeel Sajjid, Rida Ahamad, Muhammad Irfan |
| description | This study aims to detect changes that occurred in Ravi River channel over the period of last three decades (1990 to 2020). This paper spatially and temporally assesses the changes and geo-visualize variation of Ravi River using Landsat imageries. The maximum likelihood image classification technique has been used to process and analyze the spatial data in geographic information system (GIS) environment. It was found from the results that vegetation cover has gradually decreased from 976 km
2
in 1990 to 905 km
2
in 2019, whereas the built-up land had increased from 82 to 188 km
2
in the same temporal extent. Generally, the channel is shifted from east to west and the growth of built-up land to towards river which has pushed the channel. Similarly, the extreme discharge also causes change in channel shifting. Minor floods have been occurred after 2010 but Ravi is not affected much as their discharge was not that much higher to put any abrupt or significant effect on Ravi River’s channel pattern. |
| doi_str_mv | 10.1007/s12518-023-00519-6 |
| format | Article |
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2
in 1990 to 905 km
2
in 2019, whereas the built-up land had increased from 82 to 188 km
2
in the same temporal extent. Generally, the channel is shifted from east to west and the growth of built-up land to towards river which has pushed the channel. Similarly, the extreme discharge also causes change in channel shifting. Minor floods have been occurred after 2010 but Ravi is not affected much as their discharge was not that much higher to put any abrupt or significant effect on Ravi River’s channel pattern.</description><identifier>ISSN: 1866-9298</identifier><identifier>EISSN: 1866-928X</identifier><identifier>DOI: 10.1007/s12518-023-00519-6</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Analysis ; Earth and Environmental Science ; Earth resources technology satellites ; Geographic information systems ; Geographical information systems ; Geographical Information Systems/Cartography ; Geography ; Geophysics/Geodesy ; Geospatial data ; Information systems ; Landsat ; Measurement Science and Instrumentation ; Original Paper ; Plant cover ; Remote sensing ; Remote Sensing/Photogrammetry ; Rivers ; Surveying ; Vegetation cover</subject><ispartof>Applied geomatics, 2023-09, Vol.15 (3), p.759-772</ispartof><rights>The Author(s), under exclusive licence to Società Italiana di Fotogrammetria e Topografia (SIFET) 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>COPYRIGHT 2023 Springer</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c392t-2658583fb42a6fbb27d838193aa526f45254f16270720ba814d100b5d687248d3</citedby><cites>FETCH-LOGICAL-c392t-2658583fb42a6fbb27d838193aa526f45254f16270720ba814d100b5d687248d3</cites><orcidid>0000-0001-6909-0735</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12518-023-00519-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12518-023-00519-6$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Huda, Noor-ul</creatorcontrib><creatorcontrib>Mahmood, Shakeel</creatorcontrib><creatorcontrib>Sajjid, Rida</creatorcontrib><creatorcontrib>Ahamad, Muhammad Irfan</creatorcontrib><title>Spatio-temporal analysis of river channel pattern in lower course of River Ravi using GIS and remote sensing</title><title>Applied geomatics</title><addtitle>Appl Geomat</addtitle><description>This study aims to detect changes that occurred in Ravi River channel over the period of last three decades (1990 to 2020). This paper spatially and temporally assesses the changes and geo-visualize variation of Ravi River using Landsat imageries. The maximum likelihood image classification technique has been used to process and analyze the spatial data in geographic information system (GIS) environment. It was found from the results that vegetation cover has gradually decreased from 976 km
2
in 1990 to 905 km
2
in 2019, whereas the built-up land had increased from 82 to 188 km
2
in the same temporal extent. Generally, the channel is shifted from east to west and the growth of built-up land to towards river which has pushed the channel. Similarly, the extreme discharge also causes change in channel shifting. Minor floods have been occurred after 2010 but Ravi is not affected much as their discharge was not that much higher to put any abrupt or significant effect on Ravi River’s channel pattern.</description><subject>Analysis</subject><subject>Earth and Environmental Science</subject><subject>Earth resources technology satellites</subject><subject>Geographic information systems</subject><subject>Geographical information systems</subject><subject>Geographical Information Systems/Cartography</subject><subject>Geography</subject><subject>Geophysics/Geodesy</subject><subject>Geospatial data</subject><subject>Information systems</subject><subject>Landsat</subject><subject>Measurement Science and Instrumentation</subject><subject>Original Paper</subject><subject>Plant cover</subject><subject>Remote sensing</subject><subject>Remote Sensing/Photogrammetry</subject><subject>Rivers</subject><subject>Surveying</subject><subject>Vegetation cover</subject><issn>1866-9298</issn><issn>1866-928X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kctKAzEUhgdRsFRfwFXAlYvRXCaXWZbipSAIrYK7kJlJamSa1CT18vZmHFHcmCwSku87nOQvihMEzxGE_CIiTJEoISYlhBTVJdsrJkgwVtZYPO7_7GtxWBzH-AyHwSGt8KToV1uVrC-T3mx9UD1QTvUf0UbgDQj2VQfQPinndA8ymHRwwDrQ-7fhwu9C1AO4_AKX6tWCXbRuDa4Xq1ypA0FvfNIgajccHxUHRvVRH3-v0-Lh6vJ-flPe3l0v5rPbsiU1TiVmVFBBTFNhxUzTYN4JIlBNlKKYmYpiWhnEMIccw0YJVHX5HxraMcFxJToyLU7HutvgX3Y6JvmcW80PixKL7PGacZ6p85Faq15L64xPQbV5dnpjW--0sfl8xlmFGaGEZOHsj5CZpN_TWu1ilIvV8i-LR7YNPsagjdwGu1HhQyIoh9TkmJrMqcmv1CTLEhmlmGG31uG373-sT5gumBo</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>Huda, Noor-ul</creator><creator>Mahmood, Shakeel</creator><creator>Sajjid, Rida</creator><creator>Ahamad, Muhammad Irfan</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>7TN</scope><scope>F1W</scope><scope>H96</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0001-6909-0735</orcidid></search><sort><creationdate>20230901</creationdate><title>Spatio-temporal analysis of river channel pattern in lower course of River Ravi using GIS and remote sensing</title><author>Huda, Noor-ul ; Mahmood, Shakeel ; Sajjid, Rida ; Ahamad, Muhammad Irfan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c392t-2658583fb42a6fbb27d838193aa526f45254f16270720ba814d100b5d687248d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Analysis</topic><topic>Earth and Environmental Science</topic><topic>Earth resources technology satellites</topic><topic>Geographic information systems</topic><topic>Geographical information systems</topic><topic>Geographical Information Systems/Cartography</topic><topic>Geography</topic><topic>Geophysics/Geodesy</topic><topic>Geospatial data</topic><topic>Information systems</topic><topic>Landsat</topic><topic>Measurement Science and Instrumentation</topic><topic>Original Paper</topic><topic>Plant cover</topic><topic>Remote sensing</topic><topic>Remote Sensing/Photogrammetry</topic><topic>Rivers</topic><topic>Surveying</topic><topic>Vegetation cover</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Huda, Noor-ul</creatorcontrib><creatorcontrib>Mahmood, Shakeel</creatorcontrib><creatorcontrib>Sajjid, Rida</creatorcontrib><creatorcontrib>Ahamad, Muhammad Irfan</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>Oceanic Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Applied geomatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Huda, Noor-ul</au><au>Mahmood, Shakeel</au><au>Sajjid, Rida</au><au>Ahamad, Muhammad Irfan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatio-temporal analysis of river channel pattern in lower course of River Ravi using GIS and remote sensing</atitle><jtitle>Applied geomatics</jtitle><stitle>Appl Geomat</stitle><date>2023-09-01</date><risdate>2023</risdate><volume>15</volume><issue>3</issue><spage>759</spage><epage>772</epage><pages>759-772</pages><issn>1866-9298</issn><eissn>1866-928X</eissn><abstract>This study aims to detect changes that occurred in Ravi River channel over the period of last three decades (1990 to 2020). This paper spatially and temporally assesses the changes and geo-visualize variation of Ravi River using Landsat imageries. The maximum likelihood image classification technique has been used to process and analyze the spatial data in geographic information system (GIS) environment. It was found from the results that vegetation cover has gradually decreased from 976 km
2
in 1990 to 905 km
2
in 2019, whereas the built-up land had increased from 82 to 188 km
2
in the same temporal extent. Generally, the channel is shifted from east to west and the growth of built-up land to towards river which has pushed the channel. Similarly, the extreme discharge also causes change in channel shifting. Minor floods have been occurred after 2010 but Ravi is not affected much as their discharge was not that much higher to put any abrupt or significant effect on Ravi River’s channel pattern.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s12518-023-00519-6</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-6909-0735</orcidid></addata></record> |
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| subjects | Analysis Earth and Environmental Science Earth resources technology satellites Geographic information systems Geographical information systems Geographical Information Systems/Cartography Geography Geophysics/Geodesy Geospatial data Information systems Landsat Measurement Science and Instrumentation Original Paper Plant cover Remote sensing Remote Sensing/Photogrammetry Rivers Surveying Vegetation cover |
| title | Spatio-temporal analysis of river channel pattern in lower course of River Ravi using GIS and remote sensing |
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