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ABSTRACT
Remote sensing data can play an important role in the production of Land use and Land cover maps and this can therefore be managed through a process called image. Image classification is a way of allocating land cover pixels while image identification is a way of detecting and identifying an object or feature in a digital image. This project aims to apply Geographic Information System (GIS) and remote sensing in the classification and identification of land use land cover types in Ugbowo. A supervised classification based method was used for this study, which involves selecting pixels in an image that are representatives of specific classes and then using the GIS software to use these training samples as reference r the classification of all other pixels in the image. Landsat 8 images from the United States Geological Survey (USGS) were used to generate data for the study area, while the data spans over a ten year period. The generated data was used to classify the features on the ground with the help of the Geographic Information System. The result shows that the land of the study area is majorly an urban area, with a lot of built up. The study also shows that with the passage of time, the number of built ups increased, which coincided with the decrease in the areas covered by vegetation. From the results of this study it can be concluded that Landsat 8 images along with GIS can be effectively used to classify and identify images on the ground such as soil, vegetation, built up environments etc and classify them into land use land cover types which can help in managing the environment.
