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- W3204149237 abstract "Classifications of Land Use and Land Cover (LULC) have proved as one of the useful tools for resource managers to understand the environmental changes that occur over time [1]. The objective of the work is to compare the pixel-based supervised classification[2] with & without Principal Component Analysis (PCA)[3] and object-based supervised classification[4]. In this study, the data captured from Landsat 8 satellite by Operational Land Imager (OLI) sensor was used for LULC classification. For comparison, six LULC classes were used, that are: agriculture land, urban land, waterbody, dense forest, bare land, and uncultivated land. The maximum likelihood classification (MLC)[5] algorithm was employed to attain a supervised pixel and object-based classification. The study investigated the difference between the object-based and pixel-based classification in LULC classification." @default.
- W3204149237 created "2021-10-11" @default.
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- W3204149237 date "2021-10-01" @default.
- W3204149237 modified "2023-09-23" @default.
- W3204149237 title "An investigation on the difference between pixel based and object based classification for Land Use/Land Cover from Landsat 8 imagery" @default.
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