Dear Sambhaji Shinde,
There are lots of supervised classification methods such as maximum likelihood, minimum distance, and mahalanobis distance. Maximum likelihood is one of the most popular supervised classification method used with remote sensing image data. This method is based on the probability that a pixel belongs to a particular class. You can use idrisi software to classify your satellite image.
Image processing/ hard classifiers/maxlike (maximum likelihood)
Dear Sambhaji Shinde,
There are lots of supervised classification methods such as maximum likelihood, minimum distance, and mahalanobis distance. Maximum likelihood is one of the most popular supervised classification method used with remote sensing image data. This method is based on the probability that a pixel belongs to a particular class. You can use idrisi software to classify your satellite image.
Image processing/ hard classifiers/maxlike (maximum likelihood)
Dear Sambhaji Shinde,
As Mozhgan mentioned the supervised classification methods are many. The most popular parametric one is maximum likelihood. However, it depends on what type of data (images) you are going to use and your taring sample size etc, then you may choose the classifier that suits your study. Recently, researchers seek the use of machine learning methods such as random forest, support vector machines, neural network etc. Many open source and licensed tools/ packages like EnMap, ENVI, etc are available for machine learning methods.
There are several kind of supervised classification tehniques for land use land cover mapping. I can not suggest you any of these method since I do not know your main purpose to creat land use cover map. Since each method has several advantages as well as disadvantages such as accuracy, time, performance etc, we can not declare this or that method is the best and highly suggested.....Please give us more details then we could help you better....Maybe unsupervised classification might be more proper for you which based upon your purpose
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