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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Emerging Techniques for Vicarious Calibration of Visible Through Short Wave Infrared Remote Sensing Systems

Simple field-portable white light LED calibration source shows promise for visible range (420-750 nm) 1) Prototype demonstrated <0.5% drift over 10-40 C temperature range; 2) Additional complexity (more LEDs) will be necessary for extending spectral range into the NIR and SWIR; 3) LED long lifetimes should produce at least several hundreds of hours or more stability, minimizing need for expensive calibrations and supporting long-duration field campaigns; and 4) Enabling technology for developing autonomous sites.

Ryan, Robert E.↗
NASA NTRS2007

An Overview of the CBERS-2 Satellite and Comparison of the CBERS-2 CCD Data with the L5 TM Data

CBERS satellite carries on-board a multi sensor payload with different spatial resolutions and collection frequencies. HRCCD (High Resolution CCD Camera), IRMSS (Infrared Multispectral Scanner), and WFI (Wide-Field Imager). The CCD and the WFI camera operate in the VNIR regions, while the IRMSS operates in SWIR and thermal region. In addition to the imaging payload, the satellite carries a Data Collection System (DCS) and Space Environment Monitor (SEM).

Chandler, Gyanesh↗
NASA NTRS2008

The Cloud Slicing Technique-Measuring the Unmeasureable

In satellite remote sensing clouds are usually considered an annoying interference. Satellite investigators go to unusual lengths to try to avoid clouds or to correct for their effects, and satellite data users routinely exclude cloudy data from analysis. Yet it was shown about a decade ago using TOMS data that for the study of tropospheric constituents, such as ozone, clouds can play a very beneficial role by allowing one to measure what otherwise cannot be directly measured from space. We call this technique "cloud Slicing". The so-called Convective Cloud Differential (CCD) method is one particular application of cloud slicing that has been applied successfully to data from TOMS and other similar satellite instruments to study the behavior of tropical tropospheric ozone at variety of spatial and temporal scales. However, there has been considerable confusion in the literature as to what exactly one measures from reflected sunlight instruments such as TOMS in cloudy atmospheres. We will discuss recently completed analysis of data taken by the Ozone Monitoring Instrument (OMI) on the Aura satellite in conjunction with several other instruments on the A-train satellite constellation to present new insight on how clouds affect absorption by aerosols and trace gases at reflected wavelengths (UV-SWIR). We will show several examples to illustrate how this insight is helping us to study the behavior of trace gases and aerosols in the atmosphere that cannot be studied by focusing only on cloud-free scenes.

Bhartia, P.↗
NASA NTRS2008

MODIS On-board Blackbody Performance

Currently, there are two MODIS instruments operated on-orbit: one on-board the Terra spacecraft launched in December 1999 and the other on-board the Aqua spacecraft launched in May 2002. MODIS is a scanning radiometer that has 16 thermal emissive bands (TEBs) in the MWIR and LWIR regions. The remaining spectral bands are in the VISINIR and SWIR regions. The TEBs have a total of 160 detectors (10 detectors per band), which are calibrated on-orbit using an on-board blackbody (BB). MODIS TEB calibration is performed via a quadratic algorithm with its linear calibration coefficients updated on a scan-by-scan basis using each detector's response to the BB. The offset and nonlinear terms of the quadratic calibration equation are stored in a look-up table (LUT). The LUT parameters are derived from pre-launch calibration and updated on-orbit from BB observations, as needed. Typically, the BB is set at a fixed temperature. Periodically, a warm-up and cool-down activity is performed, which enables the BB temperature to be varied from instrument ambient up to 315K. The temperature of the BB is measured each scan using 12 thermistors, which were fully characterized pre-launch with reference to the NIST temperature scale. This paper describes MODIS on-board BB operational activities and performance. The TEB detector response (short-term stability and long-term changes) and noise characterization results derived from BB observations and their impact on the TEB calibration uncertainty are also presented.

Xiong, Xiaoxiong↗
NASA NTRS2006

Flora: A Proposed Hyperspectral Mission

In early 2004, one of the authors (Stephen Ungar, NASA GSFC) presented a mission concept called "Spectrasat" at the AVIRIS Workshop in Pasadena, CA. This mission concept grew out of the lessons learned from the Earth Observing-One (EO-1) Hyperion Imaging Spectrometer and was structured to more effectively accomplish the types of studies conducted with Hyperion. The Spectrasat concept represented an evolution of the technologies and operation strategies employed on EO-I. The Spectrasat concept had been preceded by two community-based missions proposed by Susan Ustin, UC Davis and Robert Green, NASA JPL. As a result of community participation, starting at this AVIRIS Workshop, the Spectrasat proposal evolved into the Flora concept which now represents the combined visions of Gregory Asner (Carnegie Institute), Stephen Ungar, Robert Green and Robert Knox, NASA GSFC. Flora is a proposed imaging spectrometer mission, designed to address global carbon cycle science issues. This mission centers on measuring ecological disturbance for purposes of ascertaining changes in global carbon stocks and draws heavily on experience gained through AVIRIS airborne flights and Hyperion space born flights. The observing strategy exploits the improved ability of imaging spectrometers, as compared with multi-spectral observing systems, to identify vegetation functional groups, detect ecosystem response to disturbance and assess the related discovery. Flora will be placed in a sun synchronous orbit, with a 45 meter pixel size, a 90 km swath width and a 31 day repeat cycle. It covers the spectral range from 0.4 to 2.5 micrometers with a spectral sampling interval of 10 nm. These specifications meet the needs of the Flora science team under the leadership of Gregory Asner. Robert Green, has introduced a spectrometer design for Flora which is expected to have a SNR of 600: 1 in the VNIR and 450: 1 in the SWIR. The mission team at NASA GSFC is designing an Intelligent Payload Module (IPM) designed to effectively reduce the volume of data required to be transmitted down to the ground. This paper discusses mission science objectives, describes the mission concept and presents the current status of possible funding opportunities leading to realization of the mission.

Ungar, Stephen↗
NASA NTRS2010

Normalized-Difference Snow Index (NDSI)

The Normalized-Difference Snow Index (NDSI) has a long history. 'The use of ratioing visible (VIS) and near-infrared (NIR) or short-wave infrared (SWIR) channels to separate snow and clouds was documented in the literature beginning in the mid-1970s. A considerable amount of work on this subject was conducted at, and published by, the Air Force Geophysics Laboratory (AFGL). The objective of the AFGL work was to discriminate snow cover from cloud cover using an automated algorithm to improve global cloud analyses. Later, automated methods that relied on the VIS/NIR ratio were refined substantially using satellite data In this section we provide a brief history of the use of the NDSI for mapping snow cover.

Hall, Dorothy K.↗
NASA NTRS2009

Characterization of MODIS and SeaWiFS Solar Diffuser On-Orbit Degradation

MODIS has 20 reflective solar bands (RSB), covering the VIS, NIR, and SWIR spectral regions. They are calibrated on-orbit using a solar diffuser (SD) panel, made of space-grade Spectralon. The SD bi-directional reflectance factor (BRF) was characterized pre-launch by the instrument vendor reference to the NIST reflectance standard. Its on-orbit degradation is tracked by an on-board solar diffuser stability monitor (SDSM). The SeaWifS on-orbit calibration strategy uses monthly lunar observations to monitor the long-term radiometric stability of the instrument and applies daily observations of its solar diffuser (an aluminum plate coated with YB71 paint) to track the short-term changes in the instrument response. This paper provides an overview of MODIS and SeaWiFS SD observations, applications, and approaches used to track their on-orbit degradations. Results from sensors are presented with emphasis on the spectral dependence and temporal trends of the SD degradation. Lessons and challenges from the use of SD for sensor on-orbit calibration are also discussed.

Xiong, X.↗
NASA NTRS2011

Miniaturized Airborne Imaging Central Server System

In recent years, some remote-sensing applications require advanced airborne multi-sensor systems to provide high performance reflective and emissive spectral imaging measurement rapidly over large areas. The key or unique problem of characteristics is associated with a black box back-end system that operates a suite of cutting-edge imaging sensors to collect simultaneously the high throughput reflective and emissive spectral imaging data with precision georeference. This back-end system needs to be portable, easy-to-use, and reliable with advanced onboard processing. The innovation of the black box backend is a miniaturized airborne imaging central server system (MAICSS). MAICSS integrates a complex embedded system of systems with dedicated power and signal electronic circuits inside to serve a suite of configurable cutting-edge electro- optical (EO), long-wave infrared (LWIR), and medium-wave infrared (MWIR) cameras, a hyperspectral imaging scanner, and a GPS and inertial measurement unit (IMU) for atmospheric and surface remote sensing. Its compatible sensor packages include NASA s 1,024 1,024 pixel LWIR quantum well infrared photodetector (QWIP) imager; a 60.5 megapixel BuckEye EO camera; and a fast (e.g. 200+ scanlines/s) and wide swath-width (e.g., 1,920+ pixels) CCD/InGaAs imager-based visible/near infrared reflectance (VNIR) and shortwave infrared (SWIR) imaging spectrometer. MAICSS records continuous precision georeferenced and time-tagged multisensor throughputs to mass storage devices at a high aggregate rate, typically 60 MB/s for its LWIR/EO payload. MAICSS is a complete stand-alone imaging server instrument with an easy-to-use software package for either autonomous data collection or interactive airborne operation. Advanced multisensor data acquisition and onboard processing software features have been implemented for MAICSS. With the onboard processing for real time image development, correction, histogram-equalization, compression, georeference, and data organization, fast aerial imaging applications, including the real time LWIR image mosaic for Google Earth, have been realized for NASA fs LWIR QWIP instrument. MAICSS is a significant improvement and miniaturization of current multisensor technologies. Structurally, it has a complete modular and solid-state design. Without rotating hard drives and other moving parts, it is operational at high altitudes and survivable in high-vibration environments. It is assembled from a suite of miniaturized, precision-machined, standardized, and stackable interchangeable embedded instrument modules. These stackable modules can be bolted together with the interconnection wires inside for the maximal simplicity and portability. Multiple modules are electronically interconnected as stacked. Alternatively, these dedicated modules can be flexibly distributed to fit the space constraints of a flying vehicle. As a flexibly configurable system, MAICSS can be tailored to interface a variety of multisensor packages. For example, with a 1,024x1,024 pixel LWIR and a 8,984x6,732 pixel EO payload, the complete MAICSS volume is approximately 7x9x11 in. (=18x23x28 cm), with a weight of 25 lb (=11.4 kg).

Sun, Xiuhong↗
NASA NTRS2011

MODIS Cloud Optical Property Retrieval Uncertainties Derived from Pixel-Level VNIR/SWIR Radiometric Uncertainties

Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of optical thickness and effective particle radius for liquid water and ice phase clouds employ a well-known VNIR/ SWIR solar reflectance technique. For this type of algorithm, we evaluate the quantitative uncertainty in simultaneous retrievals of these two cloud parameters to pixel-level radiometric calibration estimates and other fundamental (and tractable) error sources.

Platnick, S.↗
NASA NTRS2012

Landsat Data Continuity Mission Expected Instrument Performance

The Landsat Data Continuity Mission (LDCM) is scheduled for a December 2012 launch date. LDCM is being managed by an interagency partnership between NASA and the U.S. Geological Survey (USGS). In order to provide the necessary spectral coverage of the visible through shortwave-infrared (SWIR) and the thermal-infrared (TIR), the satellite will carry two sensors. The Operational Land Imager (OLI) will collect data for nine visible to shortwave spectral bands with a spatial resolution of 30 m (with a 15 m panchromatic band). The Thermal Infrared Sensor (TIRS) will collect coincident image data for two TIR bands with a spatial resolution of 100 m. The OLI is fully assembled and tested and has been shipped by it's manufacturer, Ball Aerospace and Technology Corporation, to the Orbital Sciences Corporation (Orbital) facility where it is being integrated onto the LDCM spacecraft. Pre-launch testing indicates that OLI will meet all performance specification with margin. TIRS is in development at the NASA Goddard Space F!ight Center (GSFC) and is in final testing before shipping to the Orbital facility in January, 2012. The presentation will describe the LDCM satellite instrument systems, present pre-launch performance data for OLI and TIRS, and present simulated images to highlight notable features and expected imaging performance.

Dabney, Philip W.↗
NASA NTRS2011

Using the Moon to Track MODIS Reflective Solar Bands Calibration Stability

MODIS has 20 reflective solar bands (RSB) in the visible (VIS), near infrared (NIR), and short-wave infrared (SWIR) spectral regions. In addition to instrument on-board calibrators (OBC), lunar observations have been used by both Terra and Aqua MODIS to track their reflective solar bands (RSB) on-orbit calibration stability. On a near monthly basis, lunar observations are scheduled and implemented for each instrument at nearly the same lunar phase angles. A time series of normalized detector responses to the Moon is used to monitor its on-orbit calibration stability. The normalization is applied to correct the differences of lunar viewing geometries and the Sun-Moon-Sensor distances among different lunar observations. Initially, the lunar calibration stability monitoring was only applied to MODIS bands (1-4 and 8-12) that do not saturate while viewing the Moon. As the mission continued, we extended the lunar calibration stability monitoring to other RSB bands (bands 13-16) that contain saturated pixels. For these bands, the calibration stability is monitored by referencing their non-saturated pixels to the matched pixels in a non-saturation band. In this paper, we describe this relative approach and apply it to MODIS regularly scheduled lunar observations. We present lunar trending results for both Terra and Aqua MODIS over their entire missions. Also discussed in the paper are the advantages and limitations of this approach and its potential applications to other earth-observing sensors. Keywords: Terra, Aqua, MODIS, sensor, Moon, calibration, stability

Xiong, Xiaoxiong↗
NASA NTRS2012

On-orbit Performance of MODIS Solar Diffuser Stability Monitor

MODIS has 20 reflective solar bands (RSBs) in the visible (VIS), near-infrared (NIR) , and shortwave infrared (SWIR) spectral regions. MODIS RSBs are calibrated on-orbit by a solar diffuser (SD) with its on-orbit degradation tracked by a solar diffuser stability monitor (SDSM). The SDSM is an instrument by itself, consisting of a solar integration sphere (SIS) with 9 individual filtered detectors covering wavelengths from 0.41 to 0.94 micrometers. It functions as a ratioing radiometer with alternate observations made of the direct sunlight (Sun view) and that diffusely reflected from the SD panel (SD view) during each scheduled SD/SDSM calibration event. Since launch, Terra and Aqua MODIS and their SDSM have successfully operated for more than 12 and 10 years, respectively. The VIIRS, on-board the newly launched Suomi National Polar orbiting Partnership (NPP) spacecraft, has been designed and built with strong MODIS heritage and carries a similar and improved SD and SDSM calibration system. This paper provides an overview of SDSM design functions, its on-orbit calibration strategies and performance for both Terra and Aqua MODIS missions. Discussions of its on-orbit performance are focused on changes in SDSM detector responses over time and their impact on tracking SD on-orbit degradation. Also presented in this paper are lessons learned from MODIS SDSM and improvements made for the VIIRS SDSM, and preliminary comparisons of their on-orbit performance.

Xiong, Xiaoxiong↗
NASA NTRS2012

Initial On-Orbit Radiometric Calibration of the Suomi NPP VIIRS Reflective Solar Bands

The on-orbit radiometric response calibration of the VISible/Near InfraRed (VISNIR) and the Short-Wave InfraRed (SWIR) bands of the Visible/Infrared Imager/Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) satellite is carried out through a Solar Diffuser (SD). The transmittance of the SD screen and the SD's Bidirectional Reflectance Distribution Function (BRDF) are measured before launch and tabulated, allowing the VIIRS sensor aperture spectral radiance to be accurately determined. The radiometric response of a detector is described by a quadratic polynomial of the detector?s digital number (dn). The coefficients were determined before launch. Once on orbit, the coefficients are assumed to change by a common factor: the F-factor. The radiance scattered from the SD allows the determination of the F-factor. In this Proceeding, we describe the methodology and the associated algorithms in the determination of the F-factors and discuss the results.

Lei, Ning↗
NASA NTRS2012

The Landsat Data Continuity Mission Operational Land Imager (OLI) Sensor

The Landsat Data Continuity Mission (LDCM) is being developed by NASA and USGS and is currently planned for launch in January 2013 [1]. Once on-orbit and checked out, it will be operated by USGS and officially named Landsat-8. Two sensors will be on LDCM: the Operational Land Imager (OLI), which has been built and delivered by Ball Aerospace & Technology Corp (BATC) and the Thermal Infrared Sensor (TIRS)[2], currently being built and tested at Goddard Space Flight Center (GSFC) with a planned delivery of Winter 2012. The OLI covers the Visible, Near-IR (NIR) and Short-Wave Infrared (SWIR) parts of the spectrum; TIRS covers the Thermal Infrared (TIR). This paper discusses only the OLI instrument and its pre-launch characterization; a companion paper covers TIRS.

Markham, Brian L.↗
NASA NTRS2011

High Speed, Multi-Channel, Thermal Instrument Development in Support of HyspIRI-TIR

The Jet Propulsion Laboratory is currently developing an end-to-end instrument which will provide a proof of concept prototype vehicle for a high data rate, multi-channel, thermal instrument in support of the Hyperspectral Infrared Imager (HyspIRI)-Thermal Infrared (TIR) space mission. HyspIRI mission was recommended by the National Research Council Decadal Survey (DS). The HyspIRI mission includes a visible shortwave infrared (SWIR) pushboom spectrometer and a multispectral whiskbroom thermal infrared (TIR) imager. The prototype testbed instrument addressed in this effort will only support the TIR. Data from the HyspIRI mission will be used to address key science questions related to the Solid Earth and Carbon Cycle and Ecosystems focus areas of the NASA Science Mission Directorate. Current designs for the HyspIRI-TIR space borne imager utilize eight spectral bands delineated with filters. The system will have 60m ground resolution, 200mK NEDT, 0.5C absolute temperature resolution with a 5-day repeat from LEO orbit. The prototype instrument will use mercury cadmium telluride (MCT) technology at the focal plane array in time delay integration mode. A custom read out integrated circuit (ROIC) will provide the high speed readout hence high data rates needed for the 5 day repeat. The current HyspIRI requirements dictate a ground knowledge measurement of 30m, so the prototype instrument will tackle this problem with a newly developed interferometeric metrology system. This will provide an absolute measurement of the scanning mirror to an order of magnitude better than conventional optical encoders. This will minimize the reliance on ground control points hence minimizing postprocessing (e.g. geo-rectification computations).

Multi-spectral↗
NASA NTRS2012

Optical Sensors for Planetary Radiant Energy (OSPREy): Calibration and Validation of Current and Next-Generation NASA Missions

A principal objective of the Optical Sensors for Planetary Radiance Energy (OSPREy) activity is to establish an above-water radiometer system as a lower-cost alternative to existing in-water systems for the collection of ground-truth observations. The goal is to be able to make high-quality measurements satisfying the accuracy requirements for the vicarious calibration and algorithm validation of next-generation satellites that make ocean color and atmospheric measurements. This means the measurements will have a documented uncertainty satisfying the established performance metrics for producing climate-quality data records. The OSPREy approach is based on enhancing commercial-off-the-shelf fixed-wavelength and hyperspectral sensors to create hybridspectral instruments with an improved accuracy and spectral resolution, as well as a dynamic range permitting sea, Sun, sky, and Moon observations. Greater spectral diversity in the ultraviolet (UV) will be exploited to separate the living and nonliving components of marine ecosystems; UV bands will also be used to flag and improve atmospheric correction algorithms in the presence of absorbing aerosols. The short-wave infrared (SWIR) is expected to improve atmospheric correction, because the ocean is radiometrically blacker at these wavelengths. This report describes the development of the sensors, including unique capabilities like three-axis polarimetry; the documented uncertainty will be presented in a subsequent report.

Hooker, Stanford B.↗
NASA NTRS2014

Satellite Ocean Color Sensor Design Concepts and Performance Requirements

In late 1978, the National Aeronautics and Space Administration (NASA) launched the Nimbus-7 satellite with the Coastal Zone Color Scanner (CZCS) and several other sensors, all of which provided major advances in Earth remote sensing. The inspiration for the CZCS is usually attributed to an article in Science by Clarke et al. who demonstrated that large changes in open ocean spectral reflectance are correlated to chlorophyll-a concentrations. Chlorophyll-a is the primary photosynthetic pigment in green plants (marine and terrestrial) and is used in estimating primary production, i.e., the amount of carbon fixed into organic matter during photosynthesis. Thus, accurate estimates of global and regional primary production are key to studies of the earth's carbon cycle. Because the investigators used an airborne radiometer, they were able to demonstrate the increased radiance contribution of the atmosphere with altitude that would be a major issue for spaceborne measurements. Since 1978, there has been much progress in satellite ocean color remote sensing such that the technique is well established and is used for climate change science and routine operational environmental monitoring. Also, the science objectives and accompanying methodologies have expanded and evolved through a succession of global missions, e.g., the Ocean Color and Temperature Sensor (OCTS), the Seaviewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Medium Resolution Imaging Spectrometer (MERIS), and the Global Imager (GLI). With each advance in science objectives, new and more stringent requirements for sensor capabilities (e.g., spectral coverage) and performance (e.g., signal-to-noise ratio, SNR) are established. The CZCS had four bands for chlorophyll and aerosol corrections. The Ocean Color Imager (OCI) recommended for the NASA Pre-Aerosol, Cloud, and Ocean Ecosystems (PACE) mission includes 5 nanometers hyperspectral coverage from 350 to 800 nanometers with three additional discrete near infrared (NIR) and shortwave infrared (SWIR) ocean aerosol correction bands. Also, to avoid drift in sensor sensitivity from being interpreted as environmental change, climate change research requires rigorous monitoring of sensor stability. For SeaWiFS, monthly lunar imaging accurately tracked stability at an accuracy of approximately 0.1% that allowed the data to be used for climate studies [2]. It is now acknowledged by the international community that future missions and sensor designs need to accommodate lunar calibrations. An overview of ocean color remote sensing and a review of the progress made in ocean color remote sensing and the variety of research applications derived from global satellite ocean color data are provided. The purpose of this chapter is to discuss the design options for ocean color satellite radiometers, performance and testing criteria, and sensor components (optics, detectors, electronics, etc.) that must be integrated into an instrument concept. These ultimately dictate the quality and quantity of data that can be delivered as a trade against mission cost. Historically, science and sensor technology have advanced in a "leap-frog" manner in that sensor design requirements for a mission are defined many years before a sensor is launched and by the end of the mission, perhaps 15-20 years later, science applications and requirements are well beyond the capabilities of the sensor. Section 3 provides a summary of historical mission science objectives and sensor requirements. This progression is expected to continue in the future as long as sensor costs can be constrained to affordable levels and still allow the incorporation of new technologies without incurring unacceptable risk to mission success. The IOCCG Report Number 13 discusses future ocean biology mission Level-1 requirements in depth.

Ocean Color↗
NASA NTRS2011

The Prototype HyspIRI Thermal Infrared Radiometer (PHyTIR): A High Speed, Multispectral, Thermal Instrument Development in Support of HyspIRI-TIR

The Prototype HyspIRI Thermal Infrared Radiometer (PHyTIR) is being developed as part of the risk reduction activities associated with the Hyperspectral Infrared Imager (HyspIRI). The HyspIRI mission was recommended by the National Research Council Decadal Survey and includes a visible shortwave infrared (SWIR) pushboom spectrometer and a multispectral whiskbroom thermal infrared (TIR) imager. Data from the HyspIRI mission will be used to address key science questions related to the Solid Earth and Carbon Cycle and Ecosystems focus areas of the NASA Science Mission Directorate. The HyspIRI TIR system will have 60m ground resolution, better than 200mK noise equivalent delta temperature (NEDT), 0.5C absolute temperature resolution with a 5-day repeat from LEO orbit. PHyTIR addresses the technology readiness level (TRL) of certain key subsystems of the TIR imager, primarily the detector assembly and scanning mechanism. PHyTIR will use Mercury Cadmium Telluride (MCT) technology at the focal plane and operate in time delay integration mode. A custom read out integrated circuit (ROIC) will provide the high speed readout hence allowing the high data rates needed for the 5 day repeat. PHyTIR will also demonstrate a newly developed interferometeric metrology system. This system will provide an absolute measurement of the scanning mirror to an order of magnitude better than conventional optical encoders. This will minimize the reliance on ground control points hence minimizing post-processing (e.g. geo-rectification computations).

National Research Council Decadal Survey↗