Electro-optical and hyper-spectral remote sensing

Abstract

Remote sensing satellites have become increasingly sophisticated in terms of increased spatial, radiometric, and temporal resolution. Over the past few decades sensing devices have become more sophisticated with not only higher spatial resolution but have also now become more capable at capturing data in much more precisely defined bandwidths or frequency ranges. This provides the ability to identify particular vegetation, forestry, wildlife and fish, minerals - even camouflage - with greater precision. sky is processed. This chapter explains the transition that is rapidly occurring in terms of the transition from multispectral imaging to the much more precise and data intensive hyperspectral sensing - also called imaging spectroscopy. Much more capable electro-optical arrays (usually using charge coupled devices (CCDs) allow the capturing of hyperspectral data much more efficiently. In the past with multispectral sensing data was collected in perhaps five or perhaps as many as ten broad frequency bands. Now data can be collected in much more precise and narrower frequency bands in the infrared, near infrared, visible spectrum, and even ultraviolet bands. This chapter discusses the transition from multispectral to hyperspectral sensing that is now in full swing. It notes that the first uses of hyperspectral sensing were for military and defense-related purposes but now hyperspectral sensing - using the latest electro-optical arrays - is becoming central to civil earth observation programs. This transition has not only meant a change in the imaging process and the types of sensor devices included on remote sensing satellites, but it has also signaled the shift in data processing formats with data being processed as "data cubes." In this format spatial data is provided along the (X,Y axis) while the various frequency bands are displayed on the vertical or Z axis. This evolution of sensor capabilities has, however, led to new needs on the ground in terms of interpreting the data. The new interpretative needs - because much more data is captured - involve requirements for new and faster processing techniques on the ground. Or it has led to the need for "preprocessing of data" (i.e., discarding noncritical or nonmeaningful data) before being down loaded from the satellite. The point is that the more capable sensors that collect a larger amount of data serves to alter the way the torrent of data downloaded from the sky is processed. This chapter explains the transition that is rapidly occurring in terms of the transition from multispectral imaging to the much more precise and data intensive hyperspectral sensing - also called imaging spectroscopy. Much more capable electro-optical arrays (usually using charge coupled devices (CCDs) allow the capturing of hyperspectral data much more efficiently. In the past with multispectral sensing data was collected in perhaps five or perhaps as many as ten broad frequency bands. Now data can be collected in much more precise and narrower frequency bands in the infrared, near infrared, visible spectrum, and even ultraviolet bands. This chapter discusses the transition from multispectral to hyperspectral sensing that is now in full swing. It notes that the first uses of hyperspectral sensing were for military and defense-related purposes but now hyperspectral sensing - using the latest electro-optical arrays - is becoming central to civil earth observation programs. This transition has not only meant a change in the imaging process and the types of sensor devices included on remote sensing satellites, but it has also signaled the shift in data processing formats with data being processed as 'data cubes. In this format spatial data is provided along the (X,Y axis) while the various frequency bands are displayed on the vertical or Z axis.