Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/258178
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DC FieldValueLanguage
dc.coverage.spatialGeographical Information System
dc.date.accessioned2019-09-18T05:18:45Z-
dc.date.available2019-09-18T05:18:45Z-
dc.identifier.urihttp://hdl.handle.net/10603/258178-
dc.description.abstractNanded have rapid development in every aspect, so by using satellite images and newlineapplication of remote sensing and GIS for land use and land cover change detection were used. newlineFor the analysis, ETM+, LISS3 and Landsat 8 images acquired from official websites Bhuvan newlineand USGS. The main challenge in land use and land cover changes using the remote sensing data newlinewhich how to provide the accurate and geospatial information. The production of thematic map newlinefrom this classification by using an image classification is one of the most common way newlineapplication of remote sensing. This research briefly reviews the background, methods of newlineaccuracy assessment that commonly used and recommended in the research literature. newlineTraditionally pixel based classification was used by researchers but to get more accuracy we newlinehave implemented object based approach and machine learning algorithm. Here we have shown newlinecomparative analysis of pixel based and object based analysis where we obtained result and cross newlinevalidated with ground reality. Processes that involve in this research are selection data satellite, newlinedata correction, classification process, accuracy assessment. newline
dc.format.extent122p
dc.languageEnglish
dc.relation35b
dc.rightsuniversity
dc.titleAnalysis of Land Use Land Cover Change Detection Using GIS
dc.title.alternativen.a.
dc.creator.researcherShivpuje Prakash Ramling
dc.subject.keywordEngineering and Technology,Computer Science,Computer Science Information Systems
dc.description.noteBibliography
dc.contributor.guideDeshmukh N.K.
dc.publisher.placeNanded
dc.publisher.universitySwami Ramanand Teerth Marathwada University
dc.publisher.institutionDepartment of Computer Science
dc.date.registered31/03/2016
dc.date.completed19/10/2018
dc.date.awarded20/12/2018
dc.format.dimensions
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science

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01_title.pdfAttached File261.06 kBAdobe PDFView/Open
02_certificate.pdf345.89 kBAdobe PDFView/Open
03_abstract.pdf184.7 kBAdobe PDFView/Open
04_decleration.pdf263.89 kBAdobe PDFView/Open
05_acknowledgement.pdf185.77 kBAdobe PDFView/Open
06_contents.pdf281.48 kBAdobe PDFView/Open
07_list_of_tables.pdf190.96 kBAdobe PDFView/Open
08_list_of_figures.pdf194.23 kBAdobe PDFView/Open
09_abbriviations.pdf90.17 kBAdobe PDFView/Open
10_chapter 1.pdf406.61 kBAdobe PDFView/Open
11_chapter 2.pdf248.48 kBAdobe PDFView/Open
12_chapter 3.pdf1.88 MBAdobe PDFView/Open
13_chapter 4.pdf1.39 MBAdobe PDFView/Open
14_chapter 5.pdf295.93 kBAdobe PDFView/Open
15_chapter 6.pdf254.99 kBAdobe PDFView/Open
16_chapter 7.pdf491.56 kBAdobe PDFView/Open
17_conclusions.pdf166.24 kBAdobe PDFView/Open
18_summary.pdf82.57 kBAdobe PDFView/Open
19_bibliography.pdf154.51 kBAdobe PDFView/Open


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