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https://hdl.handle.net/1959.11/11977
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kumar, Lalit | en |
dc.contributor.author | Ghosh, Manoj Kumer | en |
dc.date.accessioned | 2013-01-31T19:47:00Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | Journal of Applied Remote Sensing, 6(1), p. 063608-1-063608-16 | en |
dc.identifier.issn | 1931-3195 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/11977 | - |
dc.description.abstract | Land cover change is a significant issue for environmental managers for sustainable management. Remote sensing techniques have been shown to have a high probability of recognizing land cover patterns and change detection due to periodic coverage, data integrity, and provision of data in a broad range of the electromagnetic spectrum. We evaluate the applicability of remote sensing techniques for land cover pattern recognition, as well as land cover change detection of the Hatiya Island, Bangladesh, and quantify land cover changes from 1977 to 1999. A supervised classification approach was used to classify Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM), and Multi spectral Scanner (MSS) images into eight major land cover categories. We detected major land cover changes over the 22-year study period. During this period, marshy land, mud, mud with small grass, and bare soil had decreased by 85%, 46%, 44%, and 24%, respectively, while agricultural land, medium forest, forest, and settlement had positive changes of 26%, 45%, 363%, and 59%, respectively. The primary drivers of such landscape change were erosion and accretion processes, human pressure, and the reforestation and land reclamation programs of the Bangladesh Government. | en |
dc.language | en | en |
dc.publisher | International Society for Optical Engineering (SPIE) | en |
dc.relation.ispartof | Journal of Applied Remote Sensing | en |
dc.title | Land cover change detection of Hatiya Island, Bangladesh, using remote sensing techniques | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1117/1.JRS.6.063608 | en |
dc.subject.keywords | Photogrammetry and Remote Sensing | en |
local.contributor.firstname | Lalit | en |
local.contributor.firstname | Manoj Kumer | en |
local.subject.for2008 | 090905 Photogrammetry and Remote Sensing | en |
local.subject.seo2008 | 960509 Ecosystem Assessment and Management of Mountain and High Country Environments | en |
local.profile.school | School of Environmental and Rural Science | en |
local.profile.email | lkumar@une.edu.au | en |
local.profile.email | mghosh2@une.edu.au | en |
local.output.category | C1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.identifier.epublicationsrecord | une-20130109-155050 | en |
local.publisher.place | United States of America | en |
local.identifier.runningnumber | 063608 | en |
local.format.startpage | 063608-1 | en |
local.format.endpage | 063608-16 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 6 | en |
local.identifier.issue | 1 | en |
local.contributor.lastname | Kumar | en |
local.contributor.lastname | Ghosh | en |
dc.identifier.staff | une-id:lkumar | en |
dc.identifier.staff | une-id:mghosh2 | en |
local.profile.orcid | 0000-0002-9205-756X | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:12180 | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | Land cover change detection of Hatiya Island, Bangladesh, using remote sensing techniques | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.search.author | Kumar, Lalit | en |
local.search.author | Ghosh, Manoj Kumer | en |
local.uneassociation | Unknown | en |
local.year.published | 2012 | en |
local.subject.for2020 | 401304 Photogrammetry and remote sensing | en |
local.subject.seo2020 | 180201 Assessment and management of coastal and estuarine ecosystems | en |
Appears in Collections: | Journal Article School of Environmental and Rural Science |
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