Suomi National Polar-orbiting Partnership Spacecraft Research Articles

Refined Carbon Emission Measurement Based on NPP-VIIRS Nighttime Light Data: A Case Study of the Pearl River Delta Region, China.

The accurate measurement of CO2 emissions is helpful for realizing the goals of "carbon neutralization" and "carbon peak". However, most current research on CO2 emission measurements utilizes the traditional energy balance coefficient and top-down methods. The data granularity is large, and most studies are concentrated at the national, provincial, municipal, or district/county administrative unit scale. As an important part of the Guangdong-Hong Kong-Macao Greater Bay Area of China, the Pearl River Delta region has good nighttime light vitality and faces huge carbon emission pressure. Using the Pearl River Delta as the research area, this study constructed an optimized pixel-scale regression model based on NPP-VIIRS (The Visible Infrared Imaging Radiometer Suite on the Suomi National Polar-Orbiting Partnership spacecraft) nighttime light data and CO2 emissions data at the district and county levels for 2017. In addition, the spatial pattern of CO2 emissions in the Pearl River Delta was analyzed based on the predicted CO2 emission status. The results showed that the spatial pattern of CO2 emissions in the Pearl River Delta had the distinct characteristics of the "center-edge" effect, the spatial spillover effect, and high-value aggregation, which should be considered when making related social or public decisions.

Impact of Monsoon-Transported Anthropogenic Aerosols and Sun-Glint on the Satellite-Derived Spectral Remote Sensing Reflectance in the Indian Ocean

Spectral remote sensing reflectance (Rrs(λ), sr−1) is one of the most important products of ocean color satellite missions, where accuracy is essential for retrieval of in-water, bio-optical, and biogeochemical properties. For the Indian Ocean (IO), where Rrs(λ) accuracy has not been well documented, the quality of Rrs(λ) products from Moderate Resolution Imaging Spectroradiometer onboard both Terra (MODIS-Terra) and Aqua (MODIS-Aqua), and Visible Infrared Imaging Radiometer Suite onboard the Suomi National Polar-Orbiting Partnership spacecraft (VIIRS-NPP), is evaluated and inter-compared based on a quality assurance (QA) system, which can objectively grade each individual Rrs(λ) spectrum, with 1 for a perfect spectrum and 0 for an unusable spectrum. Taking the whole year of 2016 as an example, spatiotemporal pattern of Rrs(λ) quality in the Indian Ocean is characterized for the first time, and the underlying factors are elucidated. Specifically, QA analysis of the monthly Rrs(λ) over the IO indicates good quality with the average scores of 0.93 ± 0.02, 0.92 ± 0.02 and 0.92 ± 0.02 for VIIRS-NPP, MODIS-Aqua, and MODIS-Terra, respectively. Low-quality (~0.7) data are mainly found in the Bengal Bay (BB) from January to March, which can be attributed to the imperfect atmospheric correction due to anthropogenic absorptive aerosols transported by the northeasterly winter monsoon. Moreover, low-quality (~0.74) data are also found in the clear oligotrophic gyre zone (OZ) of the south IO in the second half of the year, possibly due to residual sun-glint contributions. These findings highlight the effects of monsoon-transported anthropogenic aerosols, and imperfect sun-glint removal on the Rrs(λ) quality. Further studies are advocated to improve the sun-glint correction in the oligotrophic gyre zone and aerosol correction in the complex ocean–atmosphere environment.

Inter-calibration of DMSP-OLS and SNPP-VIIRS-DNB annual nighttime light composites using machine learning

ABSTRACT The satellite-based nighttime lights (NTL) data from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS), available in the public domain from 1992 to 2013, are extensively used for socio-economic studies. The improved NTL products from the Visible Infrared Imaging Radiometer Suite’s Day/Night Band (VIIRS-DNB), on-board the Suomi National Polar-Orbiting Partnership spacecraft and National Oceanic and Atmospheric Administration – 20 (NOAA-20) spacecraft’s, are now available since April 2012. This study investigates the potential of machine-learning algorithms for inter-calibrating them (i.e., DMSP-OLS and VIIRS-DNB) to produce time-series annual VIIRS-DNB-like NTL datasets for the time when VIIRS-DNB data did not exist, for long-term studies. Uttar Pradesh, one of the most populous and largest States of India, is selected as the study area. Two machine-learning algorithms are utilized: (1) Multi-Layer Perceptron (MLP), having deep neural networks (DNN) architecture, and (2) Random Forest (RF), a widely used method. The DMSP-OLS and VIIRS-DNB data of 2013 (common year of data availability) and ancillary data pertaining to land cover, topography, and road network are used to train the models. The qualitative and quantitative analysis of annual VIIRS-DNB-like NTL images simulated from annual DMSP-OLS composites of 2004–2012 indicates that RF captures better spatial details at the local-scale and is able to efficiently handle the saturation problem at urban centers; while MLP is found to be superior at regional-scale. Both MLP and RF models significantly reduce the blooming effect around settlements, a common problem observed in DMSP-OLS data. It is inferred that depending on the research objectives, both RF and MLP algorithms can be appropriately utilized for producing VIIRS-DNB-like NTL images from DMSP-OLS annual NTL composites. The research can be further expanded by using other DNN architecture-based algorithms and improved spatio-temporal ancillary datasets over areas with different socio-economic, physiographic, and climatic settings.

Solar observation of Ozone Mapping and Profiler Suite nadir system during the first 3 years of on-orbit operation

The Ozone Mapping and Profiler Suite (OMPS) on the National Oceanic and Atmospheric Administration Suomi National Polar-Orbiting Partnership spacecraft has completed three more years of orbital operation since the OMPS opened its nadir door for the scene data collection on January 26, 2012. The sensors’ spectral channels have been calibrated in-flight by a working solar diffuser and a reference solar diffuser. The instruments’ optical degradation is determined through the changes in the instruments’ throughput via orbital solar observations. The observed degradation at the shortest wavelengths is <1% for the sensor optics, and in excess of 2% for the OMPS working solar diffuser. The absolute irradiance calibration uncertainties meet the system requirement of 7% for most of the channels. Unexpected orbital wavelength variation in sensor scan direction is evidenced to cause about 2.6% error, not compliant with a 2% allocation and so some margin will be needed to accommodate the exceedance.

Detector-level spectral characterization of the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite long-wave infrared bands M15 and M16.

The Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) sensor data record (SDR) product achieved validated maturity status in March 2014 after roughly two years of on-orbit characterization (S-NPP spacecraft launched on 28 October 2011). During post-launch analysis the VIIRS Sea Surface Temperature (SST) Environmental Data Record (EDR) team observed an anomalous striping pattern in the daytime SST data. Daytime SST retrievals use the two VIIRS long-wave infrared bands: M15 (10.7μm) and M16 (11.8μm). To assess possible root causes due to detector-level spectral response function (SRF) effects, a study was conducted to compare the radiometric response of the detector-level and operational-band averaged SRFs of VIIRS bands M15 and M16. The study used simulated hyperspectral blackbody radiance data and clear-sky ocean hyperspectral radiances under different atmospheric conditions. It was concluded that the SST product is likely impacted by small differences in detector-level SRFs and that if users require optimal radiometric performance, detector-level processing is recommended for both SDR and EDR products. Future work should investigate potential SDR product improvements through detector-level processing in support of the generation of Suomi NPP VIIRS climate quality SDRs.

Early On-Orbit Performance of the Visible Infrared Imaging Radiometer Suite Onboard the Suomi National Polar-Orbiting Partnership (S-NPP) Satellite

The Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the key environmental remote-sensing instruments onboard the Suomi National Polar-Orbiting Partnership spacecraft, which was successfully launched on October 28, 2011 from the Vandenberg Air Force Base, California. Following a series of spacecraft and sensor activation operations, the VIIRS nadir door was opened on November 21, 2011. The first VIIRS image acquired signifies a new generation of operational moderate resolution-imaging capabilities following the legacy of the advanced very high-resolution radiometer series on NOAA satellites and Terra and Aqua Moderate-Resolution Imaging Spectroradiometer for NASA's Earth Observing system. VIIRS provides significant enhancements to the operational environmental monitoring and numerical weather forecasting, with 22 imaging and radiometric bands covering wavelengths from 0.41 to 12.5 microns, providing the sensor data records for 23 environmental data records including aerosol, cloud properties, fire, albedo, snow and ice, vegetation, sea surface temperature, ocean color, and nigh-time visible-light-related applications. Preliminary results from the on-orbit verification in the postlaunch check-out and intensive calibration and validation have shown that VIIRS is performing well and producing high-quality images. This paper provides an overview of the on-orbit performance of VIIRS, the calibration/validation (cal/val) activities and methodologies used. It presents an assessment of the sensor initial on-orbit calibration and performance based on the efforts from the VIIRS-SDR team. Known anomalies, issues, and future calibration efforts, including the long-term monitoring, and intercalibration are also discussed.

Performance and Calibration of the Nadir Suomi-NPP Ozone Mapping Profiler Suite From Early-Orbit Images

The Ozone Mapping Profiler Suite (OMPS) was launched aboard the Suomi National Polar-orbiting Partnership spacecraft on October 28, 2011. A successful thorough Early Orbit Checkout (EOC) enabled the current Intensive Calibration and Validation stage. We present our analyses and results of OMPS Nadir early-orbit sensor performance and calibration. We collected and analyzed data from both nominal and diagnostic activities via orbital measurements of detector dark current, sensor linearity, and solar irradiance. Our results demonstrate that the OMPS Nadir sensors smoothly transitioned from ground to orbit by meeting or exceeding sensor level requirements. The orbital measurements agree with the predicted values determined during the prelaunch calibration and characterization of OMPS. Our results also suggest that the effects of charge coupled device (CCD) lattice damage due to energetic particle hits onto the CCD must be accounted for in the dark current calibration.