Land Cover Mapping Using Image Recognition

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Kapila Moon, Rushikesh Yadav, Gandharva Tatkare, Saurabh Karambelkar


Data of the land covered is not only a useful factor to evaluate earth's land change but it is also an essential product for government regarding to decision making and research. The simplest way for an efficient land cover mapping is through remote sensing data. The unique characteristics of these urban targets were taken into account to create the Object- Based Image Analysis (OBIA) in consensus with the traditional pixel-based technique of image analysis, and thus was regarded as a reliable process to compartmentalize image of high resolution. The reason for classification in remote sensing is to ascertain and classify the elements on geography of the earth. It is seen in many real-world applications, such as land use/cover mapping, urban planning, agriculture and geology, etc. The aim of such categorization is to categorize the image (pixel or object) where its category is unknown, and attach it to one of the many categories on the basis of the categorization process and rules.

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