The potential for a significant improvement in the spatial resolution of the Visible Infrared Imager Radiometer Suite (VIIRS) is discussed. VIIRS continuously samples a 3000 km-wide swath from its low-earth orbit in support of NASA/NOAA’s weather, climate and environmental science missions. In order to provide superior spatial resolution across the swath compared with previous sensors, VIIRS samples the earth at very high angular resolutions and then aggregates up to three samples per pixel in order to reduce the raw data rate presented to the spacecraft for downlink. As additional downlink capacity becomes available, science data users may consider if utilization of the native rectangular resolution provided by the VIIRS detectors can improve any of the JPSS Environmental Data Records. The impacts to this potential improvement would be largely limited to increasing capacity for data handling and processing. The VIIRS sensor would still meet its sensitivity requirements in spite of this elimination of detector averaging.
The development of the National Polar-orbiting Operational Environmental Satellite (NPOESS) Visible Infrared Imager Radiometer Suite (VIIRS) design demonstrated the value of an end-to-end simulation of remote sensing systems. To arrive at a truly optimized system, Raytheon developed and refined a system simulation capability that can be applied to a number of other programs. This capability supports both instrument and algorithm design trades. The VIIRS effort included spectral modeling of various surface types, radiative transfer modeling of the atmosphere (sometimes incorporating observed atmospheric profiles), instrument spectral, spatial, and radiometric response, and a chain of environmental product retrieval algorithms. In this paper, we present a system simulation tool that has evolved from the VIIRS capability into a more general software package that runs both quickly and accurately. This tool can be used to simulate the behavior of any system that includes a scanning visible/infrared imager or radiometer and associated product retrieval algorithms. The tool has been validated against actual Moderate-resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) outputs (both instrument-level and product-level) to illustrate the realism of the instrument modeling and environmental algorithm implementation. The package has also been reapplied to the VIIRS system design to deliver a snapshot of what can be expected when the VIIRS prototype is launched aboard the NPOESS Preparatory Project (NPP) in 2006. As an example, we present the system level characteristics of the red and near infrared (NIR) reflectances, as well as the Normalized Difference Vegetation Index (NDVI) product that can be derived from these reflectances.
Video quality metrics can be used to optimize design of advanced geosynchronous remote sensors by providing a basis for comparing information content of video at different data rates for given video sequences and compression methods and to optimize operation of future remote sensing systems by testing and monitoring quality of data collected by these systems. This paper examines and compares video quality metrics in three broad categories: distortion-based metrics that provide objective performance measures, perception-based metrics that attempt to quantify differences in images that are visible to the human visual system and utility-based metrics that address video quality for specific applications. Candidate figures of merit for describing effects of data compression on quality of video sequences or animation derived from geosynchronous imagers are presented along with recommendations for future work.
In the next decade, the volume of data produced by satellite-based remote sensing instruments will increase dramatically. The success of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments validates the decisions of government agencies to seek higher spectral and spatial resolution in the next generation of polar-orbiting and geosynchronous imagers, but transmitting the resulting high amounts of data to the Earth within constraints of available bandwidth will require new approaches to onboard data compression. In particular, the limitations of bandwidth will force greater use of lossy data compression, particularly in spectral channels with high spatial resolution, such as the reflective channels proposed for the Geostationary Operational Environmental Satellite (GOES) Advanced Baseline Imager (ABI), which will fly on GOES-R in 2012. In this study, we present analyses of the trade between two candidate lossy data compression algorithms, JPEG and JPEG-2000, for the encoding of reflective channel data from the ABI. These analyses include application to two types of real data: MODIS imagery and MODIS Airborne Simulator (MAS) imagery. The MODIS images are processed directly; the 50-m resolution MAS images are first run through a basic simulation of ABI spatial and radiometric response. In both cases, spectral channels corresponding to those that will be lossily compressed on ABI are available to support the performance trades between JPEG and JPEG-2000. The performance results are expressed in terms of peak signal to noise ratio (PSNR) and correlated noise, and they are placed in context with an assessment of the current technology readiness level (TRL) of the two standards.
A new era in atmospheric remote sensing will begin with the launch of the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) spacecraft in 2006, and the multiple operational NPOESS launches in sun-synchronous orbital planes (nominally 13:30, 17:30, or 21:30 local equatorial crossing times) starting in 2009. Cloud and atmosphere polar-orbiting environmental satellite data will be profoundly improved in radiometric quality, spectral coverage, and spatial resolution relative to current operational civilian and military polar-orbiting systems. The NPOESS Visible Infrared Imaging Radiometer Suite (VIIRS) will provide Environmental Data Records (EDRs) for day and night atmosphere and cloud operational requirements, as well as sea surface temperature (SST) and many important land EDRs by ground processing of raw data records (RDRs) from the VIIRS sensor. VIIRS will replace three currently operating sensors: the Defense Meteorological Satellite Program (DMSP) Operational Line-scanning System (OLS), the NOAA Polar-orbiting Operational Environmental Satellite (POES) Advanced Very High Resolution Radiometer (AVHRR), and the NASA Earth Observing System (EOS Terra and Aqua) MODerate-resolution Imaging Spectroradiometer (MODIS). This paper describes the VIIRS all-reflective 22-band single-sensor design, following the Critical Design Review (CDR) in Spring 2002. VIIRS provides low noise (driven by ocean color for the reflective visible and near-IR spectral bands and by SST for the emissive mid and long-wave IR spectral bands), excellent calibration and stability (driven by atmospheric aerosol and cloud EDRs, as well as SST), broad spectral coverage, and fine spatial resolution driven by the cloud imagery EDR. In addition to improved radiometric, spectral, and spatial performance, VIIRS features DMSP OLS-like near-constant resolution, global twice-daily coverage in each orbit plane, and direct heritage to proven design innovations from the successful Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Earth Observing System (Terra and Aqua) MODIS.
The National Polar-orbiting Operational Environmental Satellite System (NPOESS) Visible and Infrared Imager/Radiometer Suite (VIIRS) has responsibility for 23 Environmental Data Recrods (EDRs), three of them key NPOESS EDRs of highest value to opertional users: Imagery, Sea Surface Temrpature (SST), and Soil Moisture (primary EDR from the NPOESS conical microwave imager/sounder [CMIS]). The VIIRS design was guided by a set of government requirements priorities, which were topped by key EDR performance. Taking advantage of the MODerate-resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field Sensor (SeaWiFs) heritage, Raytheon's challenge was to optimize VIIRS system performance using Cost As Independent Variable (CAIV) analyses. The SST key EDR solution combines the traditional long-wave infrared (LWIR) split window with a second split window in the mid-wave infrared (MWIR) 3-4 μm region to offer a globally robust "dual split-window" SST algorithm operable daytime and nighttime with a precision of 0.25 K, and an overall uncertainty of 0.35 K (intermediate objective) across the entire SST measurement range. This capability was recently validated by the heritage MODIS on NASA's Terra satellite. The imagery key EDR solution permits superb multi-spectral detection and discrimination of cloud presence and type MODIS. The soil moisture solution is a cross-sensor fusion approach that combines the finer spatial resolution of VIIRS with traditional coarse resolution microwave-derived soil moisture retrievals to achieve objectives under open and partially vegetated scenes. This paper briefly describes the VIIRS sensor design, the key EDR performance, and the CAIV design process with three specific hardware and EDR tradeoff exmaples. Finally, the paper concludes with a description of the key risk-reduction design processes that led to a relativley low-risk (for advanced space-borne hardware programs) developmental design, which is now approaching hardware realization.
This paper presents an overview of the Visible and Infrared Imaging Radiometer Suite (VIIRS) design process that achieved exceptional competitive IPO ratings for system optimization, sensor system design, and systems engineering, integration and test (SEIT). A novel aspect of the competition was provision to the sensor competitors of a specification of geophysical measurement requirements called Environmental Data Records (EDRs), rather than a sensor hardware specification. The contractors were required to derive optimal VIIRS hardware specifications from the EDRs and Raytheon's process is the subject of this paper. VIIRS will become the next-generation United States polar-orbiting Operational Environmental Satellite System (MPOESS) Preparatory Project (NPP) spacecraft. Beginning in 2008, the NPOESS VIIRS instrument will be launched into 1370, 1730, and 2130 local-time ascending-node sun-synchronous polar orbits as the single operational source for dozens of civil and defense environmental and weather products, as well as climate research data. VIIRS will replace three different currently operating sensors: the Defense Meteorological Satellite Program (DMSP) Operational Line-scan System (OLS), the NOAA Polar-orbiting Operational Environmental Satellite (POES) Advanced Very High Resolution Radiometer (AVHRR), and the NASA Earth Observing System (EOS Terra and Aqua) MODerate-resolution Imaging Spectroradiometer (MODIS). A critical VIIRS challenge was design optimization to differing requirements from the three user agencies (DoD, NOAA, and NASA) represented by the NPOESS Integrated Program Office.