Day/Night Band Research Articles

Enhancement of Nighttime Fire Detection and Combustion Efficiency Characterization Using Suomi-NPP and NOAA-20 VIIRS Instruments

We present the second-generation Fire Light Detection Algorithm (FILDA-2), which includes advances in fire detection and retrievals of radiative power (FRP), fire visible energy fraction (VEF), and fire modified combustion efficiency (MCE) at nighttime from the holistic use of multiple-spectral radiances measured by the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP (VNP) and NOAA-20/JPSS-1 (VJ1) satellites. Key enhancements include: (1) a new fast algorithm that maps VIIRS Day/Night Band (DNB) radiances to the pixel footprints of VIIRS Moderate (M) and Imagery (I) bands; (2) identification of potential fire pixels through the use of the DNB anomalies and I-Band thermal anomalies; (3) dynamic thresholds for contextual testing of fire pixels; and (4) pixel-specific estimates of FRP, VEF, and MCE. The global benchmark test demonstrates that FILDA-2 can detect approximately 25-30% more smaller and cooler fires than the operational VIIRS Active Fire 375 m I-band algorithm with the added benefit of providing daily global pixel-level characterizations of MCE for nighttime surface fires. The MCE derived by FILDA-2 is in good agreement with limited ground-based observations near the fires. Additionally, FILDA-2 reduces angular dependence in FRP estimates and significantly reduces the ”bow-tie” (double-counting) effect in fire detection compared to the AF-I product. The cross-validation of FILDA-2 products from VNP and VJ1 retrievals confirms good consistency in FRP and MCE retrievals globally. FILDA-2 is being implemented by NASA to generate a new VIIRS data product for fire monitoring, chemical-speciated fire emission estimates, and fire line characterization.

JPSS-2 VIIRS Pre-Launch Reflective Solar Band Testing and Performance

The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments on-board the Suomi National Polar-orbiting Partnership (S-NPP) and Joint Polar Satellite System (JPSS) spacecrafts 1 and 2 provides calibrated sensor data record (SDR) reflectance, radiance, and brightness temperatures for use in environment data record (EDR) products. The SDRs and EDRs are used in weather forecasting models, weather imagery and climate applications such as ocean color, sea surface temperature and active fires. The VIIRS has 22 bands covering a spectral range 0.4–12.4 µm with resolutions of 375 m and 750 m for imaging and moderate bands respectively on four focal planes. The bands are stratified into three different types based on the source of energy sensed by the bands. The reflective solar bands (RSBs) detect sunlight reflected from the Earth, thermal emissive bands (TEBs) sense emitted energy from the Earth and the day/night band (DNB) detects both solar and lunar reflected energy from the Earth. The SDR calibration uses a combination of pre-launch testing and the solar diffuser (SD), on-board calibrator blackbody (OBCBB) and space view (SV) on-orbit calibrator sources. The pre-launch testing transfers the National Institute of Standards and Technology (NIST) traceable calibration to the SD, for the RSB, and the OBCBB, for the TEB. Post-launch, the on-board calibrators track the changes in instrument response and adjust the SDR product as necessary to maintain the calibration. This paper will discuss the pre-launch radiometric calibration portion of the SDR calibration for the RSBs that includes the dynamic range, detector noise, calibration coefficients and radiometric uncertainties for JPSS-2 VIIRS.

A Framework for Satellite-Based 3D Cloud Data: An Overview of the VIIRS Cloud Base Height Retrieval and User Engagement for Aviation Applications

Satellites have provided decades of valuable cloud observations, but the data from conventional passive radiometers are biased toward information from at or near cloud top. Tied with the Joint Polar Satellite System (JPSS) Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Calibration/Validation research, we developed a statistical Cloud Base Height (CBH) algorithm using the National Aeronautics and Space Administration (NASA) A-Train satellite data. This retrieval, which is currently part of the National Oceanic and Atmospheric Administration (NOAA) Enterprise Cloud Algorithms, provides key information needed to display clouds in a manner that goes beyond the typical top-down plan view. The goal of this study is to provide users with high-quality three-dimensional (3D) cloud structure information which can maximize the benefits and performance of JPSS cloud products. In support of the JPSS Proving Ground Aviation Initiative, we introduced Cloud Vertical Cross-sections (CVCs) along flight routes over Alaska where satellite data are extremely helpful in filling significant observational gaps. Valuable feedback and insights from interactions with aviation users allowed us to explore a new approach to provide satellite-based 3D cloud data. The CVC is obtained from multiple cloud retrieval products with supplementary data such as temperatures, Pilot Reports (PIREPs), and terrain information. We continue to improve the product demonstrations based on user feedback, extending the domain to the contiguous United States with the addition of the Geostationary Operational Environmental Satellite (GOES)-16 Advanced Baseline Imager (ABI). Concurrently, we have refined the underlying science algorithms for improved nighttime and multilayered cloud retrievals by utilizing Day/Night Band (DNB) data and exploring machine learning approaches. The products are evaluated using multiple satellite data sources and surface measurements. This paper presents our accomplishments and continuing efforts in both scientific and user-engagement improvements since the beginning of the VIIRS era.

Spatial-temporal expansion and determinants of light pollution in India's riparian habitats

As the world embraced Artificial Light at Night (ALAN) and its numerous benefits, the transforming nocturnal environment witnessed the negative impacts of this contaminant of emerging concern, and its consequent Light Pollution, on the fitness and populations of numerous organisms. Over the decades, India's unbridled population growth and rapid urbanization have accelerated the use of ALAN yet research on light pollution, in India, as a potential biodiversity threat remains almost untapped.The present study utilized nighttime light data from the Visible and Infrared Imaging Radiation Suite Day-Night Band (VIIRS DNB) to investigate the spatio-temporal trends of ALAN across India's major river basins, emphasizing on critical riparian habitats. The study also aimed to identify the significant effects on night-time brightness in these habitats.Our findings indicated the year, riparian fauna group and presence within and near protected areas as significant determinants of light pollution in the riparian habitats of species of conservation concern. Light pollution was observed to grow in these habitats from the year 2012 to 2020. Higher radiance, in general, were observed for habitats near conurbations, airports, ports and docks, petroleum refineries, thermal power plants, and nuclear power stations. Otter and Turtle habitats had higher night-time brightness than other groups.The significant increase of ALAN within a span of eight years is concerning, particularly for the critically endangered gharial, which was observed to inhabit predominantly darker habitats.This, along with the gaps in our knowledge regarding the effects of ALAN on these species, urgently warrants a better understanding of its effects in riparian ecosystems. We have highlighted research gaps on ALAN from India's perspective and suggest that national biodiversity programs should evaluate ALAN as a potential biodiversity threat to limit its expansion in critical riparian ecosystems.

JPSS-1 VIIRS Prelaunch Reflective Solar Band Testing and Performance

The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments on board both the Suomi National Polar-orbiting Partnership (S-NPP) and the first Joint Polar Satellite System (JPSS-1) spacecraft provides calibrated reflectance, radiance, and brightness temperature products for weather and climate applications. It has 22 bands with resolutions of 375 and 750 m for imaging and moderate bands, respectively, on 4 focal planes covering a spectral range of 400–12,490 nm. The bands are stratified into reflective solar bands (RSBs), thermal emissive bands (TEBs), and the Day/Night Band (DNB). VIIRS has three on-board calibration sectors: the solar diffuser (SD), on-board calibrator blackbody (OBCBB), and space view (SV). The on-board calibrator targets are used to track on-orbit degradation and background offset drift. Extensive prelaunch radiometric testing of the RSB, TEB, and DNB detector’s radiometric sensitivity and noise was performed for both S-NPP and JPSS-1 VIIRS. The combination of prelaunch testing and on-orbit calibrators is used to produce calibrated sensor data record (SDR) reflectance, radiance, and brightness temperatures for use in environmental data record (EDR) products. This paper will discuss the prelaunch radiometric calibration activities for the RSBs only and includes the dynamic range, calibration coefficients, detector noise, and radiometric uncertainties for JPSS-1 VIIRS.

Continuous monitoring of nighttime light changes based on daily NASA's Black Marble product suite

Monitoring nighttime light (NTL) change enables us to quantitatively analyze the dynamic patterns of human activity and socioeconomic features. NASA's Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) atmospheric- and Lunar-BRDF-corrected Black Marble product (VNP46A2) provides daily global nighttime radiances with high temporal consistency. However, timely and continuous monitoring of NTL changes based on the dense daily DNB time series is still lacking. In this study, we proposed a novel Viewing Zenith Angle (VZA) stratified COntinuous monitoring of Land Disturbance (COLD) algorithm (VZA-COLD) to detect NTL change at 15 arc-second spatial resolution with daily updating capability based on NASA's Black Marble products. Specifically, we divided the clear observations into four VZA intervals (0–20°, 20°–40°, 40°–60°, and 0–60°) to mitigate the temporal variation of the NTL data caused by the combined angular effects of viewing geometry and the complex surface conditions (e.g., building heights, vegetation canopy covers, etc.). Single-term harmonic models were continuously estimated for new observations from each VZA interval, and by comparing the model predictions with the actual DNB observations, a unified set of NTL changes can be captured continuously among the different VZA intervals. The final NTL change maps were generated after excluding the consistent dark pixels. Results showed that the VZA-COLD algorithm reduced the DNB data temporal variations caused by disparities among different viewing angles and surface conditions, and successfully detected NTL changes for six globally distributed test sites with an overall accuracy of 99.71%, a user's accuracy of 87.18%, and a producer's accuracy of 68.88% for the NTL change category.

Fifty years of nightly global low-light imaging satellite observations

The history of satellite remote sensing of nighttime lights traces it is roots back the U.S. Air Force Defense Meteorological Satellite Program (DMSP) which began flying polar orbiting satellites with cloud imaging sensors in the 1970’s. The meteorologists found that they could improve weather predictions with visible and thermal band imagery. The visible band channels on early DMSP satellites worked well in the daytime—but were unable to see clouds at nights. Visible band low light imaging was added in the mid-1970’s using photomultiplier tubes to amplify the signal, enabling the detection of moonlit clouds. In 1992, NOAA established a digital archive for DMSP data at the National Geophysical Data Center in Boulder, Colorado. The Earth Observation Group (EOG) was formed in 1994 and dedicated it is efforts to making global nighttime light data products for uses by the science and policy communities. Many of the shortcomings of DMSP data were addressed with the NASA/NOAA Visible Infrared Imaging Radiometer Suite (VIIRS) day/night band (DNB), which opened a new era in nighttime light studies. In total, EOG has produced 65 annual global nighttime light products and over 650 monthly products.

Ten Years of VIIRS EDR Imagery Validation and User Interactions

Over ten years of Visible Infrared Imaging Radiometer Suite (VIIRS) Environmental Data Records (EDR) Imagery Team activities have included primarily imagery validation, but also product generation and display and user interactions. VIIRS imagery validation starts with pre-launch preparations leading up to producing first-light imagery shortly after the launch of each Joint Polar Satellite System (JPSS) satellite. Imagery quality is scrutinized for typical imagery visualization problems, as well as the overall ability to utilize VIIRS imagery for analysis and forecasting purposes. Then, long-term monitoring of imagery continues through the lifetime of each VIIRS instrument. The VIIRS EDR Imagery Team has undertaken four major ground system code changes. The first of these code changes was needed in 2013 when Near Constant Contrast (NCC) Imagery at night was not routinely being generated from the Day-Night Band (DNB) due to incorrect sensitivity limits. The second applied Terrain Correction to the VIIRS EDR Imagery in 2020. The third, in 2021, was needed to fix an imagery banding anomaly in the NCC, which was masked for years by the natural variability of most NCC Imagery. The fourth was the increase from 6 M-band EDRs to all 16 M-band EDRs in 2021, allowing for the display of true-color and other multi-band imagery products from VIIRS Imagery EDRs. Here, we summarize the efforts of the VIIRS EDR Imagery Team which have resulted in a valuable suite of quality-controlled imagery products for the user community.

Rapid assessment of disaster damage and economic resilience in relation to the flooding in Zhengzhou, China in 2021

ABSTRACT The timely and accurate assessment of flooding disasters and economic resilience is significant for post-disaster reconstruction and recovery. In July 2021, the National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) Day/Night Band (DNB) daily data were explored as a proxy to assess the flooding damage caused by heavy rainfall in Zhengzhou City, China. A combination of the night-time light (NTL) changes and the radiation normalization method was used to rapidly identify affected areas and extract populations following the flooding disaster. A daily gross domestic product (GDP) prediction model was developed to evaluate the economic resilience of Zhengzhou City using multi-temporal DNB daily and monthly NTL data. The severity of the disaster was estimated by the extent of power outages, flooding crisis regions, and affected populations. It has been predicted that the Zhengzhou economy is unlikely to be restored to its normal level before the end of 2021 owing to the dual impact of the coronavirus outbreak and flooding disaster; the revised recovery-time prediction is late April 2022. We concluded that our NTL data provided new, simple, and effective insights into the post-flooding assessment of the affected areas, populations, GDP forecast, and economic recovery.

Automatic boat detection based on diffusion and radiation characterization of boat lights during night for VIIRS DNB imaging data.

Visible infrared imaging radiometer suite (VIIRS) day/night band (DNB) data has been used to detect lit boats during night as it is very sensitive to low radiances. The existing methods for boat detection from VIIRS DNB data are mainly based on thresholds that are estimated by the statistical characteristics of pixels or artificial experience. This may generate detection errors and poor adaptability due to the lack of characterization of boat lights. In this paper, a two-step threshold detection algorithm based on the point spread and the radiative characteristics of nightlight point sources is proposed, so that the interference from adjacent pixels could be reduced as much as possible and a reasonable threshold could be determined. Meanwhile, this algorithm is applied to three study areas, namely the sea area around Tianjin Port in Bohai Sea, the sea area around Shanghai Port in East China Sea, and the sea area around Port Sulphur in Gulf of Mexico. It is demonstrated that the detection precision of the proposed algorithm reaches up to 90% and the recall rate reaches up to 85% in three areas when validated by visual interpretation, and the precision is 85.71% when validated by automatic identification system (AIS) data in the study area of the sea area around Port Sulphur in Gulf of Mexico, which approximately increases by 5% compared with the previous algorithm.

Data of satellite observation for environmental assessment before and during COVID‐19 pandemic in part of Indonesia using the cloud‐computing platform

AbstractThe global pandemic of COVID‐19 has been insisted by many countries in the world to implement social distancing, including Indonesia. This research measured the environmental impact before and during the COVID‐19 pandemic in Indonesia. Variables, such as nitrogen dioxide (NO2) of Sentinel‐5P Tropospheric Monitoring Instrument (Tropomi), nighttime light condition of Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) and land surface temperature (LST) of Thermal InfraRed Sensor (TIRS) of Landsat‐8 Operational Land Imager (OLI), were monitored using the cloud‐based computing platform of Google Earth Engine (GEE). This study found that all monitored variables decreased during the period of the COVID‐19 pandemic compared to the period before the pandemic. However, the pattern of reduction of NO2 concentration and nighttime light was not observed to be coherent with large‐scale social distancing regulation enforced by the government. This study found that the reduction has begun 2 months earlier than the official regulation enforced by the government. The lower LST shown in both the time‐series map and the graph demonstrated changes before and during the pandemic. The hypothesis was tested using the t‐test method, and the statistical results show the significant difference between two groups of observed variables (e.g. before and during the pandemic) with the lower p‐values and higher Cohen's d. Results of this study indicate that it should be feasible to monitor the environmental impact of the COVID‐19 pandemic using the combination of NO2 concentration, nighttime light and LST information as a proxy.

The VIIRS Day/Night Band: A Flicker Meter in Space?

The VIIRS day/night band (DNB) high gain stage (HGS) pixel effective dwell time is in the range of 2–3 milliseconds (ms), which is about one third of the flicker cycle present in lighting powered by alternating current. Thus, if flicker is present, it induces random fluctuations in nightly DNB radiances. This results in increased variance in DNB temporal profiles. A survey of flicker characteristics conducted with high-speed camera data collected on a wide range of individual luminaires found that the flicker is most pronounced in high-intensity discharge (HID) lamps, such as high- and low-pressure sodium and metal halides. Flicker is muted, but detectable, in incandescent luminaires. Modern light-emitting diodes (LEDs) and fluorescent lights are often nearly flicker-free, thanks to high-quality voltage smoothing. DNB pixel footprints are about half a square kilometer and can contain vast numbers of individual luminaires, some of which flicker, while others do not. If many of the flickering lights are drawing from a common AC supplier, the flicker can be synchronized and leave an imprint on the DNB temporal profile. In contrast, multiple power supplies will throw the flickering out of synchronization, resulting in a cacophony with less radiance fluctuation. The examination of DNB temporal profiles for locations before and after the conversion of high-intensity discharge (HID) to LED streetlight conversions shows a reduction in the index of dispersion, calculated by dividing the annual variance by the mean. There are a number of variables that contribute to radiance variations in the VIIRS DNB, including the view angle, cloud optical thickness, atmospheric variability, snow cover, lunar illuminance, and the compilation of temporal profiles using pixels whose footprints are not perfectly aligned. It makes sense to adjust the DNB radiance for as many of these extraneous effects as possible. However, none of these adjustments will reduce the radiance instability introduced by flicker. Because flicker is known to affect organisms, including humans, the development of methods to detect and rate the strength of flickering from space will open up new areas of research on the biologic impacts of artificial lighting. Over time, there is a trend towards the reduction of flicker in outdoor lighting through the replacement of HID with low-flicker LED sources. This study indicates that the effects of LED conversions on the brightness and steadiness of outdoor lighting can be analyzed with VIIRS DNB temporal profiles.

Nightlights and Subnational Economic Activity: Estimating Departmental GDP in Paraguay

Subnational measures of economic activity are crucial for analyzing inequalities that persist across subnational regions and for tracking progress towards sustainable development within a country. Eighteen of the Sustainable Development Goals (SDG) indicators require having estimates of Gross Domestic Product (GDP), making subnational GDP estimates crucial for local SDG monitoring. However, many countries do not produce official subnational GDP estimates. Using Paraguay as an example, we show how nightlights imagery from the Visible Infrared Imaging Radiometer Suite’s Day-Night Band (VIIRS-DNB) and data from neighboring countries can be used to produce subnational GDP estimates. We first estimate the relationship between VIIRS and economic activity in South American countries at the first subnational administrative level, employing various econometric models. Results suggest that nightlights are strongly predictive of subnational GDP variation in South American countries with available data. We assess various models’ goodness-of-fit using both cross-validation against other countries’ subnational GDP data and comparing predictions against an input–output accounting of Paraguay’s subnational GDP. Finally, we use the preferred model to produce a time series of department-level GDP in Paraguay.

A Physical Basis for the Overstatement of Low Clouds at Night by Conventional Satellite Infrared‐Based Imaging Radiometer Bi‐Spectral Techniques

AbstractMarine boundary layer (MBL) clouds, ubiquitous to the world’s oceans, help govern the radiative balance of Earth’s climate system. Satellite remote sensing provides the most practical means to monitor cloud worldwide. Whereas visible‐based detection of MBL clouds from environmental satellites is relatively straightforward during the daytime, the night presents challenges. In certain conditions, the conventional infrared (IR) methods used for nocturnal cloud detection, such as the commonly used 11–3.9 μm brightness temperature difference, offer poor thermal and spectral contrast between clouds and the clear‐sky background—resulting in missed clouds. A less explored question is to what extent these IR techniques overstate the cloud field. The Day/Night Band (DNB), a novel low‐light sensor carried on the Joint Polar Satellite System constellation, is helping to address this question. By way of its daytime‐analog moonlight reflectance cloud detection, the DNB reveals situations where IR‐based techniques yield false‐alarm low clouds. These problems occur in conditions of cool surface and a warm/moist lower atmosphere, prevalent in areas of coastal upwelling, tidal mixing, river estuaries, and along oceanic fronts and cyclonic eddies. We show how differential sensitivity to MBL moisture can trigger algorithmic thresholds for cloud detection. Presented here are examples illustrating the problem and an evaluation of our hypothesis against idealized radiative transfer simulations. We consider the implications of such artifacts, including climate data records of sea surface temperature which rely upon IR‐based nocturnal cloud masks. The results provide a framework for designing algorithmic improvements to nighttime MBL cloud detection.

An Improved Method for Destriping of VIIRS Day/Night Band Images

The VIIRS Day/Night Band (DNB) images have opened a new era of nocturnal monitoring of global ocean, lands, and atmospheric activities at a reasonably high spatial resolution of 742 m. However, the quality of VIIRS day/night band images is seriously affected with periodic horizontal stripe noises. The image quality is further reduced on the along-track scene edges due to the complex banding effects. The noise pattern and amplitude vary according to the observation time, background light condition, and the pixel position/characteristics. To enhance the utility of VIIRS day/night band image data, we developed a novel method to reduce the noise effects and evaluate the denoised output data to ensure its radiometric integrity and quality. The noise pattern is multiplicative in nature and generated due to the detector-to-detector response variation depending on the incident light condition across the scene. Accordingly, the observed pixels in the day and night images were separated into several classes using the Otsu’s threshold value. The images recorded during twilight were classified using the solar zenith angles. Pixel-by-pixel correction of the noise effects was done by multiplying the row-wise detector gains and column-wise error factors for each class. This method was tested on several day/night and twilight images captured over the different regions with varying light conditions. The results are excellent in terms of successfully removing the striping noise and reconstructing the denoised images without spatial discontinuity across the scene regardless of its observation condition.

JPSS-2 VIIRS Day–Night Band Prelaunch Radiometric Calibration and Performance

The first two flight models of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument continue to operate onboard the Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 spacecrafts. The third flight model is set to be launched as one of a complement of instruments onboard the Joint Polar–orbiting Satellite System-2 (JPSS-2) satellite. In addition to its 14 reflective solar bands and 7 thermal emissive bands, VIIRS has a unique Day-Night Band (DNB). The DNB is a panchromatic imager based on CCD detectors, covering a spectral range of about 500 – 900 nm. The DNB is made up of three gain stages, allowing the sensor to operate over a large dynamic range (3×10-9 - 0.02 W/cm2/sr). As part of VIIRS pre-launch ground testing, the DNB has been characterized to determine its functionality and performance under a space-like environment. The results are compared against the design specification and to previous VIIRS flight models when applicable. This paper presents a comprehensive summary of the VIIRS DNB prelaunch testing and the results of radiometric and spectral assessments. The expected impact to on-orbit operations and calibrated data products are also discussed.

Evaluating the Ability of NOAA-20 Monthly Composite Data for Socioeconomic Indicators Estimation and Urban Area Extraction

The new visible infrared imaging radiometer suite (VIIRS) onboard the National Oceanic and Atmospheric Administration-20 satellite (NOAA-20) is capable of imaging the Earth during both daytime and nighttime. The NOAA-20 VIIRS’ day/night band (DNB) enables a new generation of nighttime imaging applications. However, few studies investigated the ability of NOAA-20 DNB nighttime light data in modeling socioeconomic indicators [such as the gross domestic product (GDP) and electric power consumption (EPC)] and extracting urban areas. In this article, we first used a simple linear regression model to investigate the potential of NOAA-20 nighttime light data for estimating GDP and EPC at multiple scales; we then extracted urban areas from NOAA-20 nighttime light data by using support vector machines. Taking mainland China as the study area, we found that the correlation coefficient of determination <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> between NOAA-20 nighttime light data and GDP/EPC at both provincial and prefectural scales are higher than 0.7. By comparing the results with NPP-VIIRS nighttime light data, similar <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> values were obtained at both two scales, indicating that NOAA-20 nighttime light data and NPP-VIIRS data are comparable in estimating socioeconomic indicators. Moreover, NOAA-20 also shows a similar detection ability with NPP-VIIRS in extracting urban areas. This article demonstrated that NOAA-20 and NPP-VIIRS are comparable in economic statistics estimation and urban area extraction. The NOAA-20 nighttime light data can be a useful data source for enlightening more applications in the fields of socioeconomic and urban studies.

NASA’s Black Marble Multiangle Nighttime Lights Temporal Composites

In addition to the daily Black Marble products (VNP46A1/A2), the recently released temporal composite products (VNP46A3/A4) are generated from daily high-quality, atmospheric, and lunar-Bidirectional Reflectance Distribution Function (BRDF) corrected, Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) nighttime radiances (VNP46A2). This letter describes the algorithm of NASA&#x2019;s Black Marble monthly and annual (VNP46A3/A4) Nighttime Light (NTL) composites that are operationally produced for multiple view angle categories and snow conditions, along with ancillary metrics and mandatory quality assurance flags. Boxplot metrics are calculated to systematically remove outliers and minimize reliance on empirical or regional thresholds. VNP46A3/A4 products represent all nighttime conditions (i.e., moon-lit and moon-free periods), leading to an increased number of high-quality observations. To fully make use of the VIIRS DNB&#x2019;s wide-swath (3040 km), both VNP46A3/A4 are generated for three view zenith angle categories (near-nadir, off-nadir, and all-angles) and two different snow conditions (snow-free and snow-covered). The introduction of global multidirectional data should be of interest to the scientific and applications communities. In particular, they can enable standardized intercomparisons across NTL products and allow a greater capability to track additional dimensions of NTL change, including the intrinsic characteristics of human settlements and their infrastructure. VNP46A3/A4 products are currently made available retrospectively via NASA&#x2019;s Level-1 and Atmosphere Archive and Distribution System (LAADS) from the start of the Suomi-National Polar-orbiting Partnership (S-NPP) mission period (c. January 2012).

Extending the DMSP Nighttime Lights Time Series beyond 2013

Data collected by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) sensors have been archived and processed by the Earth Observation Group (EOG) at the National Oceanic and Atmospheric Administration (NOAA) to make global maps of nighttime images since 1994. Over the years, the EOG has developed automatic algorithms to make Stable Lights composites from the OLS visible band data by removing the transient lights from fires and fishing boats. The ephemeral lights are removed based on their high brightness and short duration. However, the six original satellites collecting DMSP data gradually shifted from day/night orbit to dawn/dusk orbit, which is to an earlier overpass time. At the beginning of 2014, the F18 satellite was no longer collecting usable nighttime data, and the focus had shifted to processing global nighttime images from Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) data. Nevertheless, it was soon discovered that the F15 and F16 satellites had started collecting pre-dawn nighttime data from 2012 onwards. Therefore, the established algorithms of the previous years were extended to process OLS data from 2013 onwards. Moreover, the existence of nighttime data from three overpass times for the year 2013–DMSP satellites F18 and F15 from early evening and pre-dawn, respectively, and the VIIRS from after midnight, made it possible to intercalibrate the images of three different overpass times and study the diurnal pattern of nighttime lights.

Spatiotemporal Characterization of VIIRS Night Light

The Visible Infrared Imaging Radiometer Suite (VIIRS) Day Night Band (DNB) on board the Suomi NPP satellite now provides almost a decade of daily observations of night light. The temporal frequency of sampling, without the degree of temporal averaging of annual composites, makes it necessary to consider the distinction between apparent temporal changes of night light related to the imaging process and actual changes in the underlying sources of the night light being imaged. The most common approach to night light change detection involves direct attribution of observed changes to the phenomenon of interest. Implicit in this approach is the assumption that other forms of actual and apparent change in the light source are negligible or non-existent. An alternative approach is to characterize the spatiotemporal variability prior to deductive attribution of causation so that the attribution can be made in the context of the full range of spatial and temporal variation. The primary objective of this study is to characterize night light variability over a range of spatial and temporal scales to provide a context for interpretation of night light changes observed on both subannual and interannual time scales. This analysis is based on a combination of temporal moments, spatial correlation and Empirical Orthogonal Function (EOF) analysis. A key result of this study is the pervasive heteroskedasticity of VIIRS monthly mean night light. Specifically, the monotonic decrease of variability with increasing mean brightness. Anthropogenic night light is remarkably stable on subannual time scales while background luminance varies considerably. The variance partition from the eigenvalues of the spatiotemporal covariance matrix are 88, 2 and 2% for spatial, seasonal and interannual variance (respectively) in the most diverse region on Earth (Eurasia). Heteroskedasticity is pervasive in the monthly composites; present in all areas for all months of the year, suggesting that much, if not most, of the month-to-month variability may be related to luminance of otherwise stable sources subjected to multiple aspects of the imaging process varying in time. Given the skewed distribution of all night light arising from radial peripheral dimming of bright sources subject to atmospheric scattering, even aggregate metrics using thresholds must be interpreted in light of the fact that much larger numbers of more variable low luminance pixels may statistically overwhelm smaller numbers of stable higher luminance pixels and cause apparent changes related to the imaging process to be interpreted as actual changes in the light sources.