Muhammad, S., Aziz, G., Aneela, N., Muhammad, S.: Classification by Object recognition in satellite images by using data mining. Jabari, S., Zhang, Y.: Very high resolution satellite image classification using fuzzy rule-based systems. Pandya, A., Priya, R.S.: Classification of vegetation area from satellite images using image processing techniques. Sowmya, D., Deepa, P., Venugopal, K.: Remote sensing satellite image processing techniques for image classification: a comprehensive survey. Confusion matrix is used to estimate the overall classification accuracy. CNN will help to provide higher classification accuracy.

CNN is a deep neural networks which is most suitable when we deal with images. Convolutional neural network is used for feature extraction and classification of satellite images. So in our work, we focused with efficient automatic satellite image classification. Manual classification by using image interpretation technique requires more time and field experts. Used satellite images further classified into residential, industries, highways, crop lands, and unused images are classified further into forest, river, deserts, and beaches. Classification of satellite images into used and unused areas and also subclassing of each of the classes into four different classes has been carried out. In this work, we are creating a system to classify satellite images in order to extract information using image processing techniques.

Satellite image of address