Some fundamentals and methods for hyperspectral image data analysis

Multispectral image data has been a key data type for land observational remote sensing from aircraft and spacecraft since the 1960's(1). Sensor technology was a primary limiting factor for many years for this method, as sensors such as Landsat could only collect data in four to seven spectral bands at once. In the last few years, advances in sensor technology have made possible the collection of such image data in as many as several hundred spectral bands at once. In this paper, some results obtained in the study of data analysis methods for such high dimensional data will be overviewed. They show that such data have substantially increased potential for deriving more detailed and more accurate information, but to achieve it, the primary limiting factor has become the precision with which a user can specify the analysis classes of interest. Some methods and procedures for mitigating this limitation in practical circumstances will be described.