Change detection is a major application of satellite remote sensing. The idea is to analyze change in spectral patterns over a particular geographic area at different points of time. The information might be gathered by different satellite platforms (multi-sensor), in various wavebands (multi- spectral) and on several acquisition dates (multi-temporal). For forestry field applications, change detection might provide useful information for forest resources management, inventory, evaluation, planning, and monitoring. This study incorporated a multi-temporal approach for detecting forest change due to clearcut, partial cut, and release operation treatments in a Maine study area. Most forest change detection studies include only two dates of imagery. However, in this investigation, three date satellite images from 1983, 1988 and 1991 were examined simultaneously in a single step analysis approach. Two change detection methods, the Normalized Difference Vegetation Index (NDVI) and the Principal Components Analysis (PCA) were evaluated and a new method, Principal Factor Analysis (PFA) was introduced. A maximum likelihood classification algorithm was used to categorize change/no change events and the results were compared to a forest stand exam and history database. The Khat statistic was chosen as the criteria to evaluate the accuracy of each classification method while pairwise significance tests were constructed to compare results between methods. The Standardized variant of Principal Factor Analysis (SPFA) produced the best results followed by Principal Components Analysis and Normalized Difference Vegetation index.

This paper addresses the composition of multispectra images for target detection and recognition. It will provide the reader with tools with which multispectra images may be decomposed and new superimages may be composed to emphasize desired features of targets of interest. The proposed methodology consists of blur and noise estimation and reduction processes in association with registration, decomposition and resolution improvements. Examples from real data are being presented.

Here we consider the possibility of applying vector median filtering for joint processing of multichannel radar images. The goal is to correct distortions due errors in superimposing of channels. The proposed approach is a two-stage one. It takes into account the difference between statistical characteristics of images formed by side-look aperture radar (SLAR) and synthetic aperture radar (SAR) and uses the correlation properties of the signal processed by vector filter. Image enhancement is achieved as many false edges are eliminated and contrast of true edges is increased. Filter properties are analyzed both with simulated test images and real radar data.

Optical image movement about an image receiver of a space-born remote sensing system causes degradation of spatial resolving power of the system. The report is dedicated to the problem of minimization of that degradation by means of image movement compensation with an image stabilization subsystem. Unknown parameters of the image movement are expressed through measured or calculated parameters of the satellite movement, and the structure of an electro-mechanic compensator connected to the CCD-matrix of the image receiver is elaborated. Stabilization errors caused by the input data errors, by spatial and temporal discretization, and by the operational errors are classified and analyzed. Based on that analysis, a method of minimization of the main component of the total stabilization error is suggested.

In this paper, a novel concept of a platform-based multi- spectral collector, based on wavelength division multiplexing (WDM), is presented for terrestrial applications.

The design and fabrication of the infrared spectral imaging radiometer (ISIR) is presented. The ISIR was designed in 1994 to provide calibrated images in four thermal wavelength bands without cryogenic cooling by utilizing the new, uncooled microbolometer detector technology. The complete system was fabricated at Space Instruments, Inc. (SI) in 1995 and 1996 and delivered to NASA Goddard Space Flight Center (GSFC) for flight on the space shuttle in 1997. Photographs of the flight hardware are shown. The ISIR operates in a pushbroom fashion and utilizes real time, digital time delay and integration (TDI) to improve the signal to noise ratio. From a nominal shuttle altitude of 140 nmi, the nadir pixel subtends 240 by 240 meters on the ground. The size of the radiometer is minimized by the elimination of mechanical scan mechanisms and a space radiator. The ISIR instrument utilizes a through-the- optics calibration system to periodically obtain a two-point calibration for each pixel in the detector array. A blackbody with both heating and cooling capability is used to obtain accurate calibration data for both terrestrial and cloudtop measurements. The timeline logic, TDI integration, mechanism control, calibration, and data formatting are performed in the onboard digital processor which utilizes two microprocessors and seven programmable logic devices. The output data is recorded on two, 8 mm tape recorders.

NASA Langley Research Center (LaRC) is sponsoring the development of a revolutionary new concept for remote sensing from space. This concept is based on new technology and differs radically from previous paradigms, which call for building instruments that bolt to spacecraft. Langley's concept is called a 'sensorcraft.' The term sensorcraft simply designates a spaceflight remote sensing system that does not distinguish between the instrument, which performs a remote measurement, and the spacecraft bus, which provides the operational resources needed by the instrument in orbit. It integrates the resource requirements of both to minimize size, power consumption and cost. The gas and aerosol monitoring sensorcraft (GAMS) is a technology development project that seeks to revolutionize the remote sensing technique of solar occultation. An inherent limitation of solar occultation is the spatial and temporal coverage from a single spacecraft. For any given orbit there are at most two opportunities to take data, one at sunrise and one at sunset. A single satellite takes months to obtain a sufficient number of events to achieve global coverage. One solution to quicker global coverage is to launch several copies of the satellite. Unfortunately, by today's standards, this is very costly in hardware, launch costs, and in mission operations. This paper describes the effort to produce a small, inexpensive satellite that requires minimal ground support effort. Such a satellite would be cost effective to mass-produce, be a good 'payload of opportunity,' and allow for a constellation approach yielding global coverage in a matter of days. The GAMS project will produce an autonomous sensorcraft with mass of 60 kg, requiring less than 50 W average power and costing less than $2 M. GAMS will also perform extensive onboard processing which not only helps to reduce size and weight, but will minimize mission operations requirements. A validation flight is targeted for Shuttle deployment in late 1999. This paper discusses the mission concept and the key technologies GAMS will employ to achieve a tenfold decrease in science mission costs.

The project of a microsatellite intended for remote exploration of the atmosphere, ground and sea surface is considered. The realization of hardware part of payload of the satellite is based on the idea to use the turnable acousto- optical filter in ultra-violet and visible ranges of frequency enabling to ensure the programmed varying of one with (Delta) (lambda) less than 1 nm in area 0.2 divided by 0.9 mkm and using the counter of photons with high spatial resolution as a recording sensitive sensor. The given approach permits us to ensure the design realization of the small-size space platform, not requiring three axis precise orientation and stabilization of picture on sensor, which simultaneously is performing the role of star-tracker for detection of the satellite attitude motion.

We report on a design for a geosynchronous UV observatory optimized for imaging and spectrography of planets and comets. This solar system telescope (SST), based on a commercial developed spacecraft, was proposed to NASA as a Discovery mission. It can also serve as a low-cost orbiting observatory for other disciplines in space astronomy. The SST consists of a 140-cm-aperture telescope with an instrumentation section comprising four spectrographs and a wide-field UV imager. We use silicon carbide mirrors and a telescope structure provided by the Vavilov State Optical Institute in St. Petersburg, Russia. The spacecraft is derived from Lockheed Martin's commercial remote sensing satellite (CRSS), which provides attitude control, power, communications, and command and data handling, with minimal modifications. Using this approach, we were able to design an observatory with capabilities comparable to the Hubble Space Telescope at approximately 1/20th the cost.

We present a design for taking advantage of the Boeing inertial upper Stage (IUS) to provide a means of launching small satellites as passengers on a Titan IV-IUS launch of a 1775 kg communications satellite. An overview of a design to use the extra propulsive capability of the IUS to place small satellites into orbit is discussed. It is our proposal to have small satellites travel with the IUS into geostationary orbit and then release the satellites after the main satellite has been released. Alternatively, several small satellite buses could be stacked together on a dedicated mission to launch a series of small or microsatellites into any desired orbit including interplanetary missions. This design project was part of a joint space engineering class offered by Boeing, University of Central Florida and Florida Institute of Technology.

Presented is a preliminary design for a small ultraviolet- visible (uv-vis) sensitive space telescope. Included will be optical, sensor, and spacecraft subsystem design considerations. With recent advances in charge coupled device (CCD) technology it is now possible to build a space telescope system with wavelength sensitivity from 200 to 1000 nm. A main objective of this design is to keep costs to a minimum and use commercial off the shelf (COTS) components wherever possible. Such a low-cost system could provide a platform for studying such untested techniques as small space-based optical interferometry. The observatory could be open to a guest observer program with proposal for observing time accepted from anyone with a scientifically useful plan. Amateurs and professional astronomers alike. The World Wide Web (WWW) could be used to provide data and images to registered subscribers.

With both the increased importance of multispectral remote sensing from space-based platforms and the growth of observation data collected, new and innovative ways of collecting, processing, and storing data are becoming equally important. New collection systems are growing faster and larger which drives the need for quicker processing and greater storage capacities. To meet these needs Harris has designed and built the solid state compressive recorder (SSCR). The SSCR contains nineteen 32-bit rad-hard processors, a full duplex non-blocking cross-bar switch, and more than 2 GBytes of bulk memory. This system can perform onboard image processing and data reduction on multispectral, hyperspectral, or ultraspectral images and store the data in a format which suits the need of the end user. For optical remote sensing applications, the Harris SSCR exceeds the capability of any current fielded onboard processing system.

In October 1993, the students at Arizona State University (ASU) were challenged by Orbital Sciences Corporation to develop a 4.5-kg (10-lb) satellite (ASUSat1) to be launched as a piggyback payload on a Pegasus rocket. The challenge included the requirements for the satellite to perform meaningful science and to fit inside the Pegasus avionics section (0.033 m diam. X 0.027 m). Moreover, the students were faced with the cost constraints associated with university projects. This unusual set of requirements resulted in a design and development process, which is fundamentally different from that of traditional space projects. The spacecraft capabilities and scientific mission evolved in an extremely rigid environment where cost, size and weight limits were set before the design process even started. In the ASUSat1 project, severe constraints were determined first, and then a meaningful scientific mission was chosen to fit those constraints. This design philosophy can be applied to future satellite systems. In addition, the ASUSat1 program demonstrates that universities can provide an open-minded source for the innovative nano-spacecraft technologies required for the next generation of low-cost missions, as well as an economical testbed to evaluate those technologies. At the same time, the program provides hands-on training for the space scientists and engineers of the future.

The exploitation of remote sensing data across multiple applications is greatly facilitated by a platform for delivering the information that can be readily tailored for the requirements of specific problems, while providing a standard infrastructure for storage, metadata management, dissemination, and integration with desktop tools and other multimedia data relevant to a problem. We have developed such a platform for data generated by remote sensing instruments, including the TRW imaging spectrometer (TRWIS) family. Based on TRW's InfoWeb^TM digital multimedia archive architecture, it provides an object-relational, Intranet environment for finding and manipulating hyperspectral data and derived products. In this paper, we discuss the platform architecture and strategies for data management and integration. We present lessons learned in applying this technology that are illustrative for the development of remote sensing delivery systems.

Remote sensing is providing voluminous data and value added information products. Electronic sensors, communication electronics, computer software, hardware, and network communications technology have matured to the point where a distributed infrastructure for remotely sensed information is a reality. The amount of remotely sensed data and information is making distributed infrastructure almost a necessity. This infrastructure provides data collection, archiving, cataloging, browsing, processing, and viewing for applications from scientific research to economic, legal, and national security decision making. The remote sensing field is entering a new exciting stage of commercial growth and expansion into the mainstream of government and business decision making. This paper overviews this new distributed infrastructure and then focuses on describing a software system for on-line catalog access and distribution of remotely sensed information.

The study of the space plasma environment is the goal of the experiments named: PLASMEX, ORCAS, MAGNEX and PHOTO. They constitute the payload of the first small Brazilian satellite for scientific applications (SACI-1). The SACI-1 is a low earth polar orbit satellite which shall be launched as China- Brazil Earth Resource Satellite (CBERS) piggyback, by the Chinese launcher Long March IV, in the beginning of 1998. All the space plasma data measured by the SACI-1 payload will be received and archived in the SACI-1 Ground Station by a software system which uses the relational data modeling to build the system database. Focusing on the space plasma data base, this article describes the Ground Station software facilities such as: quick-looks of the SACI-1 remote sensing data and the data access in raw form from the investigators, via Internet.

By their very nature, hyperspectral imagers collect much more data per pixel than more traditional imaging systems. With bandwidth limitations on the communications channels and storage space, intelligent system design, band selection, and/or data compression will be very important. In two recent government-funded studies (completed in Dec. 1996), Kodak developed two preliminary compression options for hyperspectral imaging. As part of these studies, the band-to- band data correlation structures for both AVIRIS and HYDICE hyperspectral imaging systems were evaluated. Some surprising results were noted that have important implications to system designers.

It is common practice in digital imaging to apply a spatial modulation transfer function compensation (MTFC) function as a convolution filter to accomplish image sharpening. MTFC in the spatial domain is applied to back out blurring introduced by the various MTF degraders in the image chain. Analogously, in hyperspectral imaging, there is generally a blurring in the spectral dimension due to overlapping spectral bands. This blurring effect can cause narrow-band absorption features to become less apparent when a material is imaged. In a recent study at Kodak, we showed that a hyperspectral signature can be 'sharpened' in the spectral dimension by developing a set of convolution kernels that effectively reduce the overlap among the spectral responsivity of the detectors (i.e., using an appropriate convolution kernel that effectively narrows the spectral responsivity of a detector). Our initial simulations have shown that the main limitation of this technique is its performance in noisy conditions.

The process of extracting information from hyperspectral imagery datasets provided by newer sensor systems can be enhanced through a combination of unique spectral processing algorithms. The first technique we describe is a unique method for extracting the relevant bands within a hyperspectral dataset; this set of optimized bands will provide the greatest potential for discriminating specified materials of interest. The second process, subpixel spectral identification, uses the results from the subset of hyperspectral bands to further refine and distinguish between specific materials of interest, improving classification accuracy and diminishing false alarms. Comparison results produced using the full hyperspectral bandset, a six-band selection chosen based on thematic-mapper band centers, and the optimized bandset are presented for a test scene using HYDICE hyperspectral imagery.

The Florida Bay region is experiencing an economically and environmentally debilitating algal bloom. Remotely sensed data collected by the SPOT satellites provides fine spatial resolution data, necessary for this environment, currently available covering the spectral signature of chlorophyll. The study used SPOT multispectral data to test the utility of the green band (.5 - .6 microns) in algae detection while providing a change detection analysis of the Florida Bay for the years 1987, 1991, 1994 and 1996.

The GOME instrument, on board the ERS-2 satellite, has been designed in order to collect radiation over the entire wavelength region from 240 to 790 nm, in which several atmospheric species and also aerosols and clouds can be observed. A prototypal processor for the aerosol optical thickness retrieval and aerosol classification starting from GOME data has been developed. This processor has been devised as a tool to be used for the development of an operational GOME data processing chain. The implemented retrieval algorithm is based on a spectral reflectance fitting procedure of the measured radiances by GOME instrument. The maximum likelihood principle has been used in order to define the objective function. The ranking is made choosing the minimum among the least squares residuals computed for different aerosol classes. For each pixel the output of processor gives the aerosol optical thickness, the aerosol classification, a relative retrieval residual and a flag that indicates if the pixel is cloudy. The results of some different GOME real data sets are shown.