Full Spectral Imaging Project

The goal of the Full Spectral Imaging Project is to develop a New System for Remote Sensing. The New System for Remote Sensing will provide high spectral and spatial resolution remotely sensed information, as well as a wealth of auxiliary information, to any user with an Internet connection, in near real-time, in a format that is easy to use.

Full Spectral Imaging Project is the concept of John Bolton, Earth Science Systems and Remote Sensing Instrument developer. Currently he is in the Earth Science Program Office at NASA's Goddard Space Flight Center.

Background:
Current optical remote sensing instrument technology allows the acquisition and digitization of all of the reflected energy (light) across the full-spectral range of interest. The current method for acquiring, transmitting, and processing this data is still based on the "multi-band" approach that has been used for the past thirty years. Full Spectral Imaging (FSI) intends to do remote sensing the way it would have been done in the first place if adequate technology would have been available.

The goal of the Full Spectral Imaging Project is to provide high quality, easy to use, remotely sensed data (information) to researchers. This project seeks to investigate the feasibility of using alternative methods for pre-processing, transmitting, and extracting information from full-spectral, remotely sensed data. The primary concept is that of transmitting remotely sensed data in which the data rate is proportional to the rate at which information is acquired by the instrument. One feature of the project will be to change from the current "bytes-per-band" approach to the "spectral feature" approach. This approach has the possibility to greatly simplify instrument characterization and to significantly reduce data transmission and storage requirements. Full Spectral Imaging (FSI) has the potential to remove most of the objections to, and fully exploit the capabilities of, "hyperspectral" technology. FSI utilizes all the advantages and technologies of hyperspectral imaging, reducing some of the problems and adding greater usefulness.

We expect that a basic application of the Full Spectral Imaging principle will reduce data transmission and storage requirements by an order of magnitude. Refinement of the principle and supplementing Full Spectral Imaging© with the principle of spectro-spatial compression© could produce another order of magnitude reduction. And finally, and probably most importantly, if the FSI system is implemented fully, it will be possible to make measurements that give researchers spectral reflectance at the target, rather then the current measurement of spectral radiance or spectral reflectance at the top of the atmosphere. This process is called Empirical Reflectance Retrieval.

The end-to-end remote sensing system (A New System for Remote Sensing) would be completed by employing the principle of Autonomous Remote Sensing. This principle would make use of Artificial Intelligence (AI) and Neural Networks and a collaborative computing and distributed data storage capability. Like any good AI system, its performance would improve with use.

Specifics:
Full Spectral Imaging (FSI) is not "hyperspectral", "superspectral', or "ultraspectral" imaging. It is an end-to-end system for doing remote sensing. It involves everything from the technology of the observing instruments to the processes for producing the data products.

Though many ideas will be investigated in this project, the key concept of Full Spectral Imaging is that it transmits all of the information acquired by the instrument rather than all of the data acquired by a traditional instrument. The information acquired is determined by the instrument performance characteristics that, presumably, have been determined by the science requirements. On the other hand, all the data acquired by a traditional instrument includes signal, noise, redundant, and occasionally, useless bits. If the instrument characteristics really are determined by the science requirements, then the quality of the data acquired by the instrument will be sufficient to remove current objections to not having all of the raw data transmitted to the ground.

The quantity of information available from typical imaging satellites is compromised by the volume of data that it must transmit. The FSI system will extract the information from the data before transmission.