Please use this identifier to cite or link to this item: http://digitalrepository.fccollege.edu.pk/handle/123456789/1156
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dc.contributor.authorAhmad, Farooq-
dc.contributor.authorShafique, Kashif-
dc.date.accessioned2021-03-30T08:24:20Z-
dc.date.available2021-03-30T08:24:20Z-
dc.date.issued2013-
dc.identifier.citationGlobal Journal of HUMAN SOCIAL SCIENCES Geography, Geo-Sciences & Environmental Volume 13 Issue 1 Version 1.0 Year 2013 , Online ISSN: 2249-460x & Print ISSN: 0975-587Xen_US
dc.identifier.issnOnline ISSN: 2249-460x & Print ISSN: 0975-587X-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/1156-
dc.descriptionhttps://www.researchgate.net/publication/262588099_Detection_of_change_in_vegetation_cover_using_multi-spectral_and_multi-temporal_information_for_District_Sargodha_Pakistanen_US
dc.description.abstractDetection of change is the measure of the distinct data framework and thematic change information that can direct to more tangible insights into underlying process involving land cover and landuse changes. Monitoring the locations and distributions of land cover changes is important for establishing links between policy decisions, regulatory actions and subsequent landuse activities. Change detection is the process that helps in determining the changes associated with landuse and land cover properties with reference to geo-registered multi-temporal remote sensing information. It assists in identifying change between two or more dates that is uncharacterized of normal variation. After image to image registrations, the normalized difference vegetation index (NDVI), the transformed normalized differ-rence vegetation index (TNDVI), the enhanced vegetation index (EVI) and the soil-adjusted vegetation index (SAVI) values were derived from Landsat ETM+ dataset and an image differencing algorithm was applied to detect changes. This paper presents an application of the use of multi temporal Landsat ETM+ images and multi-spectral MODIS (Terra) EVI/NDVI time-series vegetation phenology metrics for the District Sargodha.en_US
dc.language.isoenen_US
dc.publisherGlobal Journalsen_US
dc.relation.ispartofseriesGlobal Journal of HUMAN SOCIAL SCIENCES Geography, Geo-Sciences & Environmental Volume 13 Issue 1 Version 1.0 Year 2013;-
dc.subjectNDVI,en_US
dc.subjectPakistanen_US
dc.subject: Change detection,en_US
dc.subjectEVI,en_US
dc.subjectLandsat,en_US
dc.subjectmulti-temporal,en_US
dc.subjectmulti-spectral,en_US
dc.titledetection of change in vegetation cover using multispectral and multi-temporal information for district sargodhaen_US
dc.typeArticleen_US
Appears in Collections:Geography Department

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