Interval and fuzzy methods in remote sensing and satellite image processing

Remote sensing conducted from satellites can be very useful for the purpose of extracting geophysical, environmental, and other earth-related information. A central problem in remote sensing is the enormous amount of data that is typically available for processing. In many cases, traditional data processing methods, that work well for data sets of smaller size, often require too much computational time and storage when applied to satellite images. In order to combat the data explosion problem encountered in remote sensing applications, interval and fuzzy methods may be employed. This paper presents several applications that have been addressed using these approaches.