scholarly journals Pre-launch Radiometric Characterization of JPSS-2 VIIRS Thermal Emissive Bands

2019 ◽  
Vol 11 (6) ◽  
pp. 732
Author(s):  
Jeff McIntire ◽  
David Moyer ◽  
Hassan Oudrari ◽  
Xiaoxiong Xiong
Keyword(s):  
Performance Metrics ◽  
Infrared Imaging ◽  
Dynamic Range ◽  
Satellite System ◽  
Quality Data ◽  
Climate Data ◽  
Environmental Testing ◽  
Improved Performance ◽  
Estimation Of Uncertainties ◽  
Thermal Band

The Joint Polar Satellite System 2 (JPSS-2) Visible Infrared Imaging Radiometer Suite (VIIRS) is the third in its series of sensors designed to produce high quality data products for environmental and climate data records once launched. To meet this goal, the VIIRS instrument must be calibrated and characterized prior to launch. A comprehensive test program was conducted at the Raytheon Space and Airborne Systems facility in 2016–2017, including extensive environmental testing. The pre-launch thermal band radiometric performance and stability is the focus of this work including: the evaluation of a number of sensor performance metrics, comparison to the design requirements, and the estimation of uncertainties. Comparisons of the thermal band performance to the earlier Suomi National Polar-orbiting Partnership (SNPP) and JPSS-1 VIIRS instruments as well as the design specifications have shown that JPSS-2 VIIRS exhibits similar performance to its predecessors. The differences of note (decreased blackbody uniformity, reduced dynamic range for bands M15 and M16, and improved performance with respect to striping) are small and not expected to have a significant impact on the science products.

scholarly journals An Overall Assessment of JPSS-2 VIIRS Radiometric Performance Based on Pre-launch Testing

2018 ◽  
Author(s):  
Hassan Oudrari ◽  
Jeffrey McIntire ◽  
Xiaoxiong Xiong ◽  
James Butler ◽  
Qiang Ji ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Infrared Imaging ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Scattered Light ◽  
Light Response ◽  
Satellite System ◽  
Sensor Data ◽  
Polarization Sensitivity ◽  
Spectral Performance

The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the second Joint Polar Satellite System (JPSS) completed its sensor level testing in February 2018. The JPSS-2 (J2) mission is scheduled to launch in 2022, and will be very similar to its two predecessor missions, the Suomi National Polar-orbiting Partnership (SNPP) mission, launched on 28 October 2011, and JPSS-1 (renamed NOAA-20) launched on 18 November 2017. VIIRS instrument has 22 spectral bands covering the spectrum between 0.4 and 12.6 mircron: 14 reflective solar bands (RSB), 7 thermal emissive bands (TEB), and one day-night band (DNB). It is a cross-track scanning radiometer capable of providing global measurements through observations at two spatial resolutions, 375 m and 750 m at nadir for the imaging bands and moderate bands, respectively. This paper will provide an overview of J2 VIIRS characterization methodologies and calibration performance during the pre-launch testing phases performed by the National Aeronautics and Space Administration (NASA) VIIRS Characterization Support Team (VCST) to evaluate the at-launch baseline radiometric performance and generate the parameters needed to populate the sensor data record (SDR) Look-Up-Tables (LUTs). Key sensor performance metrics include the signal to noise ratio (SNR), radiance dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, spectral performance, response versus scan-angle (RVS), and scattered light response. A set of performance metrics generated during the pre-launch testing program will be compared to both the SNPP and JPSS-1 VIIRS sensors.

scholarly journals An Overall Assessment of JPSS-2 VIIRS Radiometric Performance Based on Pre-Launch Testing

2018 ◽  
Vol 10 (12) ◽  
pp. 1921 ◽  
Author(s):  
Hassan Oudrari ◽  
Jeff McIntire ◽  
Xiaoxiong Xiong ◽  
James Butler ◽  
Qiang Ji ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Infrared Imaging ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Scattered Light ◽  
Light Response ◽  
Satellite System ◽  
Sensor Data ◽  
Polarization Sensitivity ◽  
Spectral Performance

The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the second Joint Polar Satellite System (JPSS) completed its sensor level testing in February 2018. The JPSS-2 (J2) mission is scheduled to launch in 2022 and will be very similar to its two predecessor missions, the Suomi National Polar-orbiting Partnership (SNPP) mission, launched on 28 October 2011 and JPSS-1 (renamed NOAA-20) launched on 18 November 2017. VIIRS instrument has 22 spectral bands covering the spectrum between 0.4 and 12.6 μm: 14 reflective solar bands (RSB), 7 thermal emissive bands (TEB) and one day-night band (DNB). It is a cross-track scanning radiometer capable of providing global measurements through observations at two spatial resolutions, 375 m and 750 m at nadir for the imaging bands and moderate bands, respectively. This paper will provide an overview of J2 VIIRS characterization methodologies and calibration performance during the pre-launch testing phases performed by the National Aeronautics and Space Administration (NASA) VIIRS Characterization Support Team (VCST) to evaluate the at-launch baseline radiometric performance and generate the parameters needed to populate the sensor data record (SDR) Look-Up-Tables (LUTs). Our analysis results confirmed the good performance of J2 VIIRS, in general as good as previous VIIRS instruments and all non-compliances are expected to have low impact on data quality. Key sensor performance metrics include the signal to noise ratio (SNR), radiance dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, spectral performance, response versus scan-angle (RVS) and scattered light response. A set of performance metrics generated during the pre-launch testing program will be compared to both the SNPP and JPSS-1 VIIRS sensors.

scholarly journals An Overview of the Science Performances and Calibration/Validation of Joint Polar Satellite System Operational Products

2019 ◽  
Vol 11 (6) ◽  
pp. 698 ◽  
Author(s):  
Lihang Zhou ◽  
Murty Divakarla ◽  
Xingpin Liu ◽  
Arron Layns ◽  
Mitch Goldberg
Keyword(s):  
Performance Monitoring ◽  
Performance Metrics ◽  
Satellite System ◽  
Quality Data ◽  
Direct Result ◽  
Science Data ◽  
Successful Operation ◽  
Data Products ◽  
The Status ◽  
Polar Satellite

The Suomi National Polar-orbiting Partnership (S-NPP) satellite, launched in October 2011, initiated a series of the next-generation weather satellites for the National Oceanic and Atmospheric Administration (NOAA) Joint Polar Satellite System (JPSS) program. The JPSS program at the Center for Satellite Applications and Research (JSTAR) leads the development of the algorithms, the calibration and validation of the products to meet the specified requirements, and long-term science performance monitoring and maintenance. All of the S-NPP products have been validated and are in successful operation. The recently launched JPSS-1 (renamed as NOAA-20) satellite is producing high-quality data products that have been available from S-NPP, along with additional products, as a direct result of the instrument upgrades and science improvements. This paper presents an overview of the JPSS product suite, the performance metrics achieved for the S-NPP, and the utilization of the products by NOAA stakeholders and user agencies worldwide. The status of NOAA-20 science data products and ongoing calibration/validation (Cal/Val) efforts are discussed for user awareness. In addition, operational implementation statuses of JPSS enterprise (multisensor and multiplatform) science algorithms for product generation and science product reprocessing efforts for the S-NPP mission are discussed.

scholarly journals Cross-Sensor Nighttime Lights Image Calibration for DMSP/OLS and SNPP/VIIRS with Residual U-Net

2021 ◽  
Vol 13 (24) ◽  
pp. 5026
Author(s):  
Dmitry Nechaev ◽  
Mikhail Zhizhin ◽  
Alexey Poyda ◽  
Tilottama Ghosh ◽  
Feng-Chi Hsu ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Dynamic Range ◽  
Satellite System ◽  
Sensor Calibration ◽  
Environmental Light ◽  
Nighttime Lights ◽  
Military Conflicts ◽  
Highly Correlated ◽  
Polar Satellite

Remote sensing of nighttime lights (NTL) is widely used in socio-economic studies of economic growth, urbanization, stability of power grid, environmental light pollution, pandemics and military conflicts. Currently, NTL data are collected with two sensors: (1) Operational Line-scan System (OLS) onboard the satellites from the Defense Meteorology Satellite Program (DMSP) and (2) Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi NPP (SNPP) and NOAA-20 satellites from the Joint Polar Satellite System (JPSS). However, the nighttime images acquired by these two sensors are incompatible in spatial resolution and dynamic range. To address this problem, we propose a method for the cross-sensor calibration with residual U-net convolutional neural network (CNN). The CNN produces DMSP-like NTL composites from the VIIRS annual NTL composites. The pixel radiances predicted from VIIRS are highly correlated with NTL observed with OLS (0.96 < R2 < 0.99). The method can be used to extend long-term series of annual NTL after the end of DMSP mission or to cross-calibrate same year NTL from different satellites to study diurnal variations.

scholarly journals HDDM Hardware Evaluation for Robust Interference Mitigation

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6492
Author(s):  
Fabio Garzia ◽  
Johannes Rossouw van der Merwe ◽  
Alexander Rügamer ◽  
Santiago Urquijo ◽  
Wolfgang Felber
Keyword(s):  
Hardware Implementation ◽  
Interference Mitigation ◽  
Dynamic Range ◽  
State Of The Art ◽  
Satellite System ◽  
High Rate ◽  
Gnss Receivers ◽  
Improved Performance ◽  
Global Navigation Satellite ◽  
Mitigation Methods

Interference can significantly degrade the performance of global navigation satellite system (GNSS) receivers. Therefore, mitigation methods are required to ensure reliable operations. However, as there are different types of interference, robust, multi-purpose mitigation algorithms are needed. This paper describes the most popular state-of-the-art interference mitigation techniques. The high-rate DFT-based data manipulator (HDDM) is proposed as a possible solution to overcome their limitations. This paper presents a hardware implementation of the HDDM algorithm. The hardware HDDM module is integrated in three different receivers equipped with analog radio-frequency (RF) front-ends supporting signals with different dynamic range. The resource utilization and power consumption is evaluated for the three cases. The algorithm is compared to a low-end mass-market receiver and a high-end professional receiver with basic and sophisticated interference mitigation capabilities, respectively. Different type of interference are used to compare the mitigation capabilities of the receivers under test. Results of the HDDM hardware implementation achieve the similar or improved performance to the state of the art. With more complex interferences, like frequency hopping or pulsed, the HDDM shows even better performance.

scholarly journals The Diamond League athletic series: does the air quality sparkle?

2021 ◽  
Author(s):  
James R. Hodgson ◽  
Lee Chapman ◽  
Francis D. Pope
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Performance Metrics ◽  
Urban Air Pollution ◽  
Quality Data ◽  
Performance Variation ◽  
Short And Long Term ◽  
Respiratory Conditions ◽  
Race Performance

AbstractUrban air pollution can have negative short- and long-term impacts on health, including cardiovascular, neurological, immune system and developmental damage. The irritant qualities of pollutants such as ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM) can cause respiratory and cardiovascular distress, which can be heightened during physical activity and particularly so for those with respiratory conditions such as asthma. Previously, research has only examined marathon run outcomes or running under laboratory settings. This study focuses on elite 5-km athletes performing in international events at nine locations. Local meteorological and air quality data are used in conjunction with race performance metrics from the Diamond League Athletics series to determine the extent to which elite competitors are influenced during maximal sustained efforts in real-world conditions. The findings from this study suggest that local meteorological variables (temperature, wind speed and relative humidity) and air quality (ozone and particulate matter) have an impact on athletic performance. Variation between finishing times at different race locations can also be explained by the local meteorology and air quality conditions seen during races.

scholarly journals Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

2015 ◽  
Vol 8 (10) ◽  
pp. 4083-4110 ◽  
Author(s):  
R. C. Levy ◽  
L. A. Munchak ◽  
S. Mattoo ◽  
F. Patadia ◽  
L. A. Remer ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Infrared Imaging ◽  
Quantitative Information ◽  
Environmental Data ◽  
Retrieval Algorithm ◽  
Climate Data ◽  
Data Record ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångström Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March–April–May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ~ 0.025), while reducing the differences between AE. We characterize algorithm retrievability through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.

scholarly journals Multi-Criteria Performance Evaluation of Gridded Precipitation and Temperature Products in Data-Sparse Regions

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1597
Author(s):  
Ibrahim Mohammed Lawal ◽  
Douglas Bertram ◽  
Christopher John White ◽  
Ahmad Hussaini Jagaba ◽  
Ibrahim Hassan ◽  
...  
Keyword(s):  
Decision Making ◽  
Performance Metrics ◽  
Research Unit ◽  
Climate Data ◽  
Meteorological Forcing ◽  
Lake Chad ◽  
Climate Research ◽  
Princeton University ◽  
Lake Chad Basin ◽  
Precipitation And Temperature

Inadequate climate data stations often make hydrological modelling a rather challenging task in data-sparse regions. Gridded climate data can be used as an alternative; however, their accuracy in replicating the climatology of the region of interest with low levels of uncertainty is important to water resource planning. This study utilised several performance metrics and multi-criteria decision making to assess the performance of the widely used gridded precipitation and temperature data against quality-controlled observed station records in the Lake Chad basin. The study’s findings reveal that the products differ in their quality across the selected performance metrics, although they are especially promising with regards to temperature. However, there are some inherent weaknesses in replicating the observed station data. Princeton University Global Meteorological Forcing precipitation showed the worst performance, with Kling–Gupta efficiency of 0.13–0.50, a mean modified index of agreement of 0.68, and a similarity coefficient SU = 0.365, relative to other products with satisfactory performance across all stations. There were varying degrees of mismatch in unidirectional precipitation and temperature trends, although they were satisfactory in replicating the hydro-climatic information with a low level of uncertainty. Assessment based on multi-criteria decision making revealed that the Climate Research Unit, Global Precipitation Climatology Centre, and Climate Prediction Centre precipitation data and the Climate Research Unit and Princeton University Global Meteorological Forcing temperature data exhibit better performance in terms of similarity, and are recommended for application in hydrological impact studies—especially in the quantification of projected climate hazards and vulnerabilities for better water policy decision making in the Lake Chad basin.

scholarly journals Source mechanisms and near-source wave propagation from broadband seismograms

1994 ◽  
Vol 37 (6) ◽  
Author(s):  
J. Virieux ◽  
A. Deschamps ◽  
J. Perrot ◽  
J. Campos
Keyword(s):  
Wave Propagation ◽  
Coordinate System ◽  
Ray Tracing ◽  
Dynamic Range ◽  
Time Derivative ◽  
Quality Data ◽  
Heterogeneous Structure ◽  
Spherical Coordinate ◽  
Seismic Rupture ◽  
Converted Phases

Recording seismic events at teleseismic distances with broadband and high dynamic range instruments provides new high-quality data that allow us to interpret in more detail the complexity of seismic rupture as well as the heterogeneous structure of the medium surrounding the source where waves are initially propagating. Wave propagation analysis is performed by ray tracing in a local cartesian coordinate system near the source and in a global spherical coordinate system when waves enter the mantle. Seismograms are constructed at each station for a propagation in a 2.5-D medium. Many phases can be included and separately analyzed; this is one of the major advantages of ray tracing compared to other wave propagation techniques. We have studied four earthquakes, the 1988 Spitak Armenia Earthquake (Ms = 6.9), the 1990 Iran earthquake (Ms = 7.7), the 1990 romanian earthquake (Ms = 5.8) and the 1992 Erzincan, Turkey earthquake (Ms = 6.8). These earthquakes exhibit in different ways the complexity of the rupture and the signature of the medium surrounding the source. The use of velocity seismograms, the time derivative of displacement, increases the difficulty of the fit between synthetic seismograms and real seismograms but provides clear evidence for a need of careful time delay estimations of the different converted phases. We find that understanding of the seismic rupture as well as the influence of the medium surrounding the source for teleseismically recorded earthquakes requires a multi-stop procedure: starting with ground displacement seismograms, one is able to give a first description of the rupture as well as of the first-order influence of the medium. Then, considering the ground velocity seismograms makes the fit more difficult to obtain but increases our sensitivity to the rupture process and early converted phases. With increasing number of worldwide broadband stations, a complex rupture description is possible independently of field observations, which can be used to check the adequacy of such complicated models.

scholarly journals Data Aggregation and Its Impact on Performance Enhancement

2019 ◽  
Vol 9 (2S) ◽  
pp. 316-319
Keyword(s):  
Performance Improvement ◽  
Data Aggregation ◽  
Performance Metrics ◽  
Performance Enhancement ◽  
Data Availability ◽  
Quality Data ◽  
Data Organization ◽  
Data Handling ◽  
Aggregation Techniques ◽  
Important Position

Wireless sensor network incorporates an innovative aspect called as data handling technologies for big data organization. In today’s research the data aggregation occupies an important position and its emerging rapidly. Data aggregation incudes, process of accumulating the data at node, then either store or transfer further to reach out the destination. This survey depicts about the previous work on data aggregation in WSN and also its impact on the different services. There are number of data aggregation techniques available for reducing the data, processing the data and storing the data. Some of them are discussed here as a review. The data aggregation performed using certain techniques can also be aimed in having energy efficiency, time efficient, security could be in the form of confidentiality, unimpaired, authenticate, freshness, quality, data availability, access control, nonrepudiation, secrecy, secrecy. These are the relevant performance metrics to maintain the better Qos in WSNs applications. The goal of this paper is to display an overview of existing techniques for performance improvement in homogenous/ heterogenous networks.

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