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Content based Image Retrieval systems (CBIR) have become a reliable tool for many image database applications. Today, the need for reliable, automated satellite image classification and browsing systems is more than ever before. Everyday there is a massive amount of remotely sensed data being collected and sent by terrestrial satellites for analysis. The use of automated tools for this analysis has become imperative due to the large volumes required to be processed on a daily basis. Our goal is to develop a prototype of Content based Image Retrieval Systems for Satellite Images, wherein the user enters query in form of a sample image and the relevant similar images based on image content are displayed as an output. The Work presents a novel approach of satellite image search and retrieval system based on colour and texture. Texture information is obtained using co-occurrence matrix of the gray scaled images. The properties like correlation and homogeneity are good parameters to measure the textural property; these are evaluated at proper offset and angle. Colour is inevitable feature that dominates the human perception most. The Hue Saturation and Value (HSV) colour space is quite similar to the way in which humans perceive colour. Making this as the foundation, the work presented here uses the combination of the HSV colour and texture feature. Results have shown that the retrieval based on combination of texture and colour based features match better with the human perception.