60 research outputs found

    MODIS and VIIRS On-Orbit Calibration and Characterization Using Observations from Spacecraft Pitch Maneuvers

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    Two MODIS instruments (Terra and Aqua) and two VIIRS instruments (S-NPP and JPSS-1) are currently operated inspace, continuously making global earth observations in the spectral range from visible (VIS) to long-wave infrared(LWIR). These observations have enabled a broad range of environmental data records to be generated and distributed insupport of both operational and scientific community. Despite extensive pre-launch calibration and characterizationperformed for both MODIS and VIIRS instruments and routine on-orbit calibration activities carried out using their onboardcalibrators (OBC), various spacecraft maneuvers have also been designed and implemented to further enhance thesensor on-orbit calibration and data quality. This paper focuses on the use of observations made during spacecraft pitchmaneuvers of MODIS and VIIRS in support of their on-orbit characterization of thermal emissive bands (TEB) responseversus scan-angle (RVS). In the case of Terra MODIS, lunar observations made from instrument nadir view duringspacecraft pitch maneuvers are used to compare with that made regularly through instrument space view (SV) port toevaluate on-orbit changes in RVS and band-to-band registration (BBR) for the reflective solar bands (RSB). In additionto results derived from spacecraft pitch maneuvers performed for MODIS and VIIRS, discussion is provided on theadvantages, challenges, and lessons for future considerations and improvements

    Post-Launch Calibration Support for VIIRS Onboard NASA NPP Spacecraft

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    The NPP Instrument Calibration Support Element (NICSE) is one of the elements within the NASA NPP Science Data Segment (SDS). The primary responsibility of NICSE is to independently monitor and evaluate on-orbit radiometric and geometric performance of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument and to validate its Sensor Data Record (SDR) [1]. The NICSE interacts and works closely with other SDS Product Evaluation and Analysis Tools Elements (PEATE) and the NPP Science Team (ST) and supports their on-orbit data product calibration and validation efforts. The NICSE also works closely with the NPP Instrument Calibration Support Team (NICST) during sensor pre-launch testing in ambient and thermal vacuum environment [2]. This paper provides an overview of NICSE VIIRS sensor post-launch calibration support with a focus on the use of sensor on-board calibrators (OBC) for the radiometric calibration and characterization. It presents the current status of NICSE post-launch radiometric calibration tool development effort based on its design requirement

    Initial Calibration Activities and Performance Assessments of NOAA-20 VIIRS

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    The second VIIRS instrument was launched on-board the NOAA-20 (formerly JPSS-1) satellite onNovember 18, 2017. It was designed and built with the same performance requirements as the first VIIRSon-board the S-NPP launched on October 28, 2011. Currently, the NOAA-20 is orbiting the Earth in thesame plane as the S-NPP but separated in time and space by 50 minutes. The VIIRS observations are made in22 spectral bands, including a day-night band (DNB) that cover wavelengths from visible to long-waveinfrared. The sensor's on-orbit calibration is provided by a set of on-board calibrators (OBCs), which includea solar diffuser (SD), a solar diffuser stability monitor (SDSM), and a blackbody (BB). After turn-on, theVIIRS instrument conducted a series of post-launch testing (PLT) and intensive calibration and validation(ICV) activities, including those performed via spacecraft maneuvers, designed to verify and establishinstrument on-orbit calibration performance baseline. This paper provides an overview of NOAA-20 VIIRSICV activities and an assessment of its initial on-orbit performance with a focus on several key calibrationparameters, such as the detector response (or gain), dynamic range, and signal-to-noise ratio (SNR). Variousissues identified and lessons learned from initial instrument operation and calibration are also discussed insupport of long-term monitoring (LTM) of NOAA-20 VIIRS calibration and data quality

    Vicarious Methodologies to Assess and Improve the Quality of the Optical Remote Sensing Images: A Critical Review

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    Over the past decade, number of optical Earth observing satellites performing remote sensing has increased substantially, dramatically increasing the capability to monitor the Earth. The quantity of remote sensing satellite increase is primarily driven by improved technology, miniaturization of components, reduced manufacturing, and launch cost. These satellites often lack on-board calibrators that a large satellite utilizes to ensure high quality (e.g., radiometric, geometric, spatial quality, etc.) scientific measurement. To address this issue, this work presents “best” vicarious image quality assessment and improvement techniques for those kinds of optical satellites which lacks on-board calibration system. In this article, image quality categories have been explored, and essential quality parameters (e.g., absolute and relative calibration, aliasing, etc.) have been identified. For each of the parameters, appropriate characterization methods are identified along with its specifications or requirements. In cases of multiple methods, recommendation has been made based-on the strengths and weaknesses of each method. Furthermore, processing steps have been presented, including examples. Essentially, this paper provides a comprehensive study of the criteria that needs to be assessed to evaluate remote sensing satellite data quality, and best vicarious methodologies to evaluate identified quality parameters such as coherent noise, ground sample distance, etc

    Sensor Performance Assessment for Terra and Aqua MODIS Using Unscheduled Lunar Observations

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    The Moderate Resolution Imaging Spectroradiometer (MODIS) has been in operation for over 18 and 16 years on the Terra and Aqua spacecrafts, respectively. In order to maintain long-term calibration stability over the life of each mission, MODIS uses a set of on-board calibrators as well as observations of the Moon and selected Earth-view targets. The lunar observations nominally occur in a narrow phase angle range, 55 degrees - 56 degrees, and use scheduled spacecraft maneuvers in order to bring the Moon into alignment with the MODIS space-view port. These observations are used to help characterize the MODIS scan-mirror response versus scan-angle. In addition to these scheduled lunar observations, MODIS also views the Moon through the space-view port without a spacecraft maneuver when the geometry is appropriately aligned. This occurs over a wider phase angle range, between 51 degrees - 82 degrees, than those of the scheduled moon observations. While the phase angle restriction of our scheduled observations provides consistency between the calibration events, the unscheduled Moon data can provide a valuable assessment of many calibration related investigations that use the Moon. In this paper, we compare the results of unscheduled versus scheduled lunar observations for several sensor calibration and performance assessments. These include the lunar calibration trending used to characterize the scan-mirror response versus scan angle and the electronic crosstalk correction of bands 27-30, which are currently used in the MODIS Level-1B data products, as well as sensor performance assessments such as band-to-band and detector-to-detector spatial registration

    On-Orbit Lunar Modulation Transfer Function Measurements for the Moderate Resolution Imaging Spectroradiometer

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    Spatial quality of an imaging sensor can be estimated by evaluating its modulation transfer function (MTF) from many different sources such as a sharp edge, a pulse target, or bar patterns with different spatial frequencies. These well-defined targets are frequently used for prelaunch laboratory tests, providing very reliable and accurate MTF measurements. A laboratory-quality edge input source was included in the spatial-mode operation of the Spectroradiometric Calibration Assembly (SRCA), which is one of the onboard calibrators of the Moderate Resolution Imaging Spectroradiometer (MODIS). Since not all imaging satellites have such an instrument, SRCA MTF estimations can be used as a reference for an on-orbit lunar MTF algorithm and results. In this paper, the prelaunch spatial quality characterization process from the Integrated Alignment Collimator and SRCA is briefly discussed. Based on prelaunch MTF calibration using the SRCA, a lunar MTF algorithm is developed and applied to the lifetime on-orbit Terra and Aqua MODIS lunar collections. In each lunar collection, multiple scan-directionMoon-to-background transition profiles are aligned by the subpixel edge locations from a parametric Fermi function fit. Corresponding accumulated edge profiles are filtered and interpolated to obtain the edge spread function (ESF). The MTF is calculated by applying a Fourier transformation on the line spread function through a simple differentiation of the ESF. The lifetime lunar MTF results are analyzed and filtered by a relationship with the Sun-Earth-MODIS angle. Finally, the filtered lunarMTF values are compared to the SRCA MTF results. This comparison provides the level of accuracy for on-orbit MTF estimations validated through prelaunch SRCA measurements. The lunar MTF values had larger uncertainty than the SRCA MTF results; however, the ratio mean of lunarMTF fit and SRCA MTF values is within 2% in the 250- and 500-m bands. Based on the MTF measurement uncertainty range, the suggested lunar MTF algorithm can be applied to any on-orbit imaging sensor with lunar calibration capability

    Mapping regional land cover and land use change using MODIS time series

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    Coarse resolution satellite observations of the Earth provide critical data in support of land cover and land use monitoring at regional to global scales. This dissertation focuses on methodology and dataset development that exploit multi-temporal data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to improve current information related to regional forest cover change and urban extent. In the first element of this dissertation, I develop a novel distance metric-based change detection method to map annual forest cover change at 500m spatial resolution. Evaluations based on a global network of test sites and two regional case studies in Brazil and the United States demonstrate the efficiency and effectiveness of this methodology, where estimated changes in forest cover are comparable to reference data derived from higher spatial resolution data sources. In the second element of this dissertation, I develop methods to estimate fractional urban cover for temperate and tropical regions of China at 250m spatial resolution by fusing MODIS data with nighttime lights using the Random Forest regression algorithm. Assessment of results for 9 cities in Eastern, Central, and Southern China show good agreement between the estimated urban percentages from MODIS and reference urban percentages derived from higher resolution Landsat data. In the final element of this dissertation, I assess the capability of a new nighttime lights dataset from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) for urban mapping applications. This dataset provides higher spatial resolution and improved radiometric quality in nighttime lights observations relative to previous datasets. Analyses for a study area in the Yangtze River Delta in China show that this new source of data significantly improves representation of urban areas, and that fractional urban estimation based on DNB can be further improved by fusion with MODIS data. Overall, the research in this dissertation contributes new methods and understanding for remote sensing-based change detection methodologies. The results suggest that land cover change products from coarse spatial resolution sensors such as MODIS and VIIRS can benefit from regional optimization, and that urban extent mapping from nighttime lights should exploit complementary information from conventional visible and near infrared observations

    Band-to-Band Misregistration of the Images of MODIS On-Board Calibrators and Its Impact to Calibration

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    The MODIS instruments aboard Terra and Aqua satellites are radiometrically calibrated on-orbit with a set of onboard calibrators (OBC) including a solar diffuser (SD), a blackbody (BB) and a space view (SV) port through which the detectors can view the dark space. As a whisk-broom scanning spectroradiometer, thirty-six MODIS spectral bands are assembled in the along-scan direction on four focal plane assemblies (FPA). These bands capture images of the same target sequentially with the motion of a scan mirror. Then the images are co-registered on board by delaying appropriate band dependent amount of time depending on the band locations on the FPA. While this co-registration mechanism is functioning well for the "far field" remote targets such as Earth view (EV) scenes or the Moon, noticeable band-to-band misregistration in the along-scan direction has been observed for near field targets, in particular the OBCs. In this paper, the misregistration phenomenon is presented and analyzed. It is concluded that the root cause of the misregistration is that the rotating element of the instrument, the scan mirror, is displaced from the focus of the telescope primary mirror. The amount of the misregistration is proportional to the band location on the FPA and is inversely proportional to the distance between the target and the scan mirror. The impact of this misregistration to the calibration of MODIS bands is discussed. In particular, the calculation of the detector gain coefficient m1 of bands 8-16 (412 nm 870 nm) is improved by up to 1.5% for Aqua MODIS

    Earth observations from DSCOVR EPIC instrument

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    The National Oceanic and Atmospheric Administration (NOAA) Deep Space Climate Observatory (DSCOVR) spacecraft was launched on 11 February 2015 and in June 2015 achieved its orbit at the first Lagrange point (L1), 1.5 million km from Earth toward the sun. There are two National Aeronautics and Space Administration (NASA) Earth-observing instruments on board: the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR). The purpose of this paper is to describe various capabilities of the DSCOVR EPIC instrument. EPIC views the entire sunlit Earth from sunrise to sunset at the backscattering direction (scattering angles between 168.5° and 175.5°) with 10 narrowband filters: 317, 325, 340, 388, 443, 552, 680, 688, 764, and 779 nm. We discuss a number of preprocessing steps necessary for EPIC calibration including the geolocation algorithm and the radiometric calibration for each wavelength channel in terms of EPIC counts per second for conversion to reflectance units. The principal EPIC products are total ozone (O3) amount, scene reflectivity, erythemal irradiance, ultraviolet (UV) aerosol properties, sulfur dioxide (SO2) for volcanic eruptions, surface spectral reflectance, vegetation properties, and cloud products including cloud height. Finally, we describe the observation of horizontally oriented ice crystals in clouds and the unexpected use of the O2 B-band absorption for vegetation properties.The NASA GSFC DSCOVR project is funded by NASA Earth Science Division. We gratefully acknowledge the work by S. Taylor and B. Fisher for help with the SO2 retrievals and Marshall Sutton, Carl Hostetter, and the EPIC NISTAR project for help with EPIC data. We also would like to thank the EPIC Cloud Algorithm team, especially Dr. Gala Wind, for the contribution to the EPIC cloud products. (NASA Earth Science Division)Accepted manuscrip

    Pre-Aerosol, Clouds, and Ocean Ecosystem (PACE) Mission Science Definition Team Report

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    We live in an era in which increasing climate variability is having measurable impact on marine ecosystems within our own lifespans. At the same time, an ever-growing human population requires increased access to and use of marine resources. To understand and be better prepared to respond to these challenges, we must expand our capabilities to investigate and monitor ecological and bio geo chemical processes in the oceans. In response to this imperative, the National Aeronautics and Space Administration (NASA) conceived the Pre-Aerosol, Clouds, and ocean Ecosystem (PACE) mission to provide new information for understanding the living ocean and for improving forecasts of Earth System variability. The PACE mission will achieve these objectives by making global ocean color measurements that are essential for understanding the carbon cycle and its inter-relationship with climate change, and by expanding our understanding about ocean ecology and biogeochemistry. PACE measurements will also extend ocean climate data records collected since the 1990s to document changes in the function of aquatic ecosystems as they respond to human activities and natural processes over short and long periods of time. These measurements are pivotal for differentiating natural variability from anthropogenic climate change effects and for understanding the interactions between these processes and various human uses of the ocean. PACE ocean science goals and measurement capabilities greatly exceed those of our heritage ocean color sensors, and are needed to address the many outstanding science questions developed by the oceanographic community over the past 40 years
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