Classification of Damaged Crops using Remote Sensing and Geographic Information System

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dc.contributor.advisorSingh, J.P.
dc.contributor.authorRandhawa, Prabhjot Kaur
dc.date.accessioned2017-12-21T04:43:33Z
dc.date.available2017-12-21T04:43:33Z
dc.date.issued2017
dc.description.abstractCrop damage is a serious problem which perilously affect the agriculture production and the livelihood of farmers and nation as a whole. In the present study, two villages namely; Bagga kalan, Nurpur Bet and Sarmastpur, Bal from each Ludhiana and Jalandhar district respectively, were selected for classifying and quantifying the crop area under damage using remote sensing (RS) and GIS technique. WV-2 and LISS-3 data were used for digitizing cadastral map under each village and classifying the villages under various classes. Confusion matrix were tabulated under each village for computing accuracy assessment for ground truthing and classified values. There were no losses in all the villages of Ludhiana and Jalandhar district. Therefore damaged was induced into each of the village. The study revealed that the affected area under damage were found to be 26.48 ha, 30.01 ha, 10.10 ha and 45.84 ha for villages Bagga kalan, Nurpur Bet, Sarmastpur and Bal respectively. A case was carried out to identify damaged wheat crop on satellite imagery. Lohgarh village of Sirsa district, Haryana was chosen in which damage wheat crop was found to be 127.62 ha due to inundation.en_US
dc.identifier.urihttp://krishikosh.egranth.ac.in/handle/1/5810037956
dc.keywordsDamage, Crop, Remote sensing, GIS, Cadastral, Confusion Matrixen_US
dc.language.isoenen_US
dc.pages57en_US
dc.publisherPunjab Agricultural University, Ludhianaen_US
dc.research.problemClassification of Damaged Crops using Remote Sensing and Geographic Information Systemen_US
dc.subSoil and Water Engineeringen_US
dc.subjectnullen_US
dc.themeClassification of Damaged Crops using Remote Sensing and Geographic Information Systemen_US
dc.these.typeM.Techen_US
dc.titleClassification of Damaged Crops using Remote Sensing and Geographic Information Systemen_US
dc.typeThesisen_US
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