Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/153519
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dc.coverage.spatial
dc.date.accessioned2017-06-12T07:04:49Z-
dc.date.available2017-06-12T07:04:49Z-
dc.identifier.urihttp://hdl.handle.net/10603/153519-
dc.description.abstractThe increasing global population is exerting pressure on natural resources to fulfil the newlineincreased human needs and demands. An efficient utilisation and management of the natural newlineresources has become more important than ever to meet these enlarged demands. Crop newlineproducts are one of the most important natural resources available to us. In-season assessment newlineof crop area estimates helps planners and decision makers to efficiently manage the crop newlineproducts. There has been tremendous improvement in in-season assessment of crop acreage newlineestimation, during last couple of decades. Remote Sensing (RS) is an important tool that newlineprovide near real time data which can be used for crop area estimation. RS data with different newlinespecifications (spatial, temporal, spectral resolutions, active/passive etc.) are typically used newlinefor crop area estimation at different scales. Non-availability of frequent high spatial resolution newlineoptical RS data is an issue that affects an early estimation of crop area estimation over large newlineareas. Typically, high spatial resolution (low temporal frequency) RS data is used for single newlinecrop area estimation over small regions. Similarly, frequently available (low spatial newlineresolution) optical RS data is used for multiple crop area estimation over large regions. While newlineestimating small area crop acreages, frequently available low spatial resolution data are not newlineused; less frequently available high spatial resolution data are overlooked for large area crop newlineacreage estimation. Hence, an early estimation of small area crop acreage estimation is not newlinedone and crop acreage estimation over large area suffers due to crop field discrimination newlineambiguity. This situation may improve if we develop techniques of integrating the newlineinformation derived from high spatial resolution data as well as high temporal resolution data newlineat different scales. Currently there is no operational RS based system in India for an early newlineestimation of Rabi crop area which is an important information needed by agriculture newlinemanagement agencies at mu
dc.format.extent
dc.languageEnglish US
dc.relation
dc.rightsuniversity
dc.titleManagement and Analysis of Multi source Remote Sensing Data for Modelling Multi level Crop Acreage Estimates
dc.title.alternative
dc.creator.researcherDhani Ram Rajak
dc.subject.keywordAcreate
dc.subject.keywordcrop
dc.subject.keywordestimates
dc.subject.keywordresolution
dc.subject.keywordspatial
dc.description.note
dc.contributor.guideJain Rajesh, Parihar Jai Singh
dc.publisher.placeAhmedabad
dc.publisher.universityNirma University
dc.publisher.institutionInstitute of Management
dc.date.registered29/07/2010
dc.date.completed15/04/2017
dc.date.awarded20/04/2017
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Institute of Management

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01_title.pdfAttached File36.24 kBAdobe PDFView/Open
02_certificate.pdf333.6 kBAdobe PDFView/Open
03_abstract.pdf222.42 kBAdobe PDFView/Open
04_declaration.pdf247.58 kBAdobe PDFView/Open
05_acknowledgement.pdf1.08 MBAdobe PDFView/Open
06_content.pdf228.26 kBAdobe PDFView/Open
07_list_of_tables.pdf187.5 kBAdobe PDFView/Open
08_list_of_figures.pdf226.63 kBAdobe PDFView/Open
09_abbreviations.pdf230.06 kBAdobe PDFView/Open
10_chapter1.pdf862.19 kBAdobe PDFView/Open
11_chapter2.pdf429.81 kBAdobe PDFView/Open
12_chapter3.pdf1.44 MBAdobe PDFView/Open
13_chapter4.pdf857.5 kBAdobe PDFView/Open
14_chapter5.pdf1.47 MBAdobe PDFView/Open
15_chapter6.pdf1.28 MBAdobe PDFView/Open
16_chapter7.pdf273.26 kBAdobe PDFView/Open
17_summary_and_conclusions.pdf296.04 kBAdobe PDFView/Open
18_bibliography.pdf501.07 kBAdobe PDFView/Open


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