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Potentials and Characteristics of Landsat Imagery in Relation to Land Use /Cover in Okitipupa Metropolis, Ondo State, Nigeria

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dc.contributor.author Tobore, A. O.
dc.contributor.author Oyerinde, G.
dc.contributor.author Senjobi, B.A.
dc.contributor.author Ogundiyi, T.O.
dc.date.accessioned 2022-12-16T09:11:49Z
dc.date.available 2022-12-16T09:11:49Z
dc.date.issued 2019
dc.identifier.uri http://197.159.135.214/jspui/handle/123456789/610
dc.description Research Article en_US
dc.description.abstract Landsat satellite imagery plays a crucial role in providing information on land use/cover modifications on local, regional, and global scales, especially where aerial photographs are missing. Monitoring land -use changes from past to present tends to be time-consuming especially when dealing with groundtruth information. Determining the past and current land-use change on Earth's surface using Landsat imagery tends to be effective and efficient when high-resolution imagery is unavailable. This study employed the use of Landsat satellite imagery to assess the past and present land use/cover using supervised classification and Normalized Difference Vegetation Index (NDVI). The result of the supervised classification land use/cover showed that forest cover and woodland undergo rapid loss, while farmland, wetland, built-up, and waterbodies tend to experience gradual loss. The NDVI demonstrated that farmland and forest cover was the most affected land use/cover. Hence, land use/cover of the study area is affected by human activities, such as intensive farming, population size, and deforestation. en_US
dc.language.iso en en_US
dc.publisher Journal of Agricultural Science and Environment en_US
dc.subject LandSAT Imagery en_US
dc.subject land use/cover en_US
dc.subject Normalized Difference Vegetation Index en_US
dc.subject Supervised Classification en_US
dc.title Potentials and Characteristics of Landsat Imagery in Relation to Land Use /Cover in Okitipupa Metropolis, Ondo State, Nigeria en_US
dc.type Article en_US


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