A prologue to natural computing in remote sensing

Nature was always one of the sources of motivation for artist, painters, musician's, scientist and many more. New growth in science and technology has given several optimization approaches that inspire the creation of greater efficient algorithms for Digital Satellite Image Classification. Different conventional classification techniques were used for satellite image classification however the outcomes got from those calculations were very little proficient to use for any genuine application. Different forms of remote sensing images and varying classification techniques are examined in this paper. Natural Computing Intelligence explores the area based on Physics, Chemistry, Geo-Sciences, Human mind and some other intelligent techniques. From these intelligent computational techniques, this paper includes some of the nature-inspired algorithms for satellite image classification of the Alwar region, Rajasthan, India. The fundamental objective of the paper is to retrieve various natural terrain features with a group of classifiers or a hybrid model for the accomplishment of better accuracy. Various parameters like Kappa Coefficient, User Accuracy, Producer Accuracy, and Overall Accuracy are used to decide the effectiveness of classification.