National Polar-orbiting Partnership Research Articles

Does China's Urban Development Satisfy Zipf's Law? A Multiscale Perspective from the NPP-VIIRS Nighttime Light Data.

Currently, whether the urban development in China satisfies Zipf’s law across different scales is still unclear. Thus, this study attempted to explore whether China’s urban development satisfies Zipf’s law across different scales from the National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data. First, the NPP-VIIRS data were corrected. Then, based on the Zipf law model, the corrected NPP-VIIRS data were used to evaluate China’s urban development at multiple scales. The results showed that the corrected NPP-VIIRS data could effectively reflect the state of urban development in China. Additionally, the Zipf index (q) values, which could express the degree of urban development, decreased from 2012 to 2018 overall in all provinces, prefectures, and counties. Since the value of q was relatively close to 1 with an R2 value > 0.70, the development of the provinces and prefectures was close to the ideal Zipf’s law state. In all counties, q > 1 with an R2 value > 0.70, which showed that the primate county had a relatively stronger monopoly capacity. When the value of q < 1 with a continuous declination in the top 2000 counties, the top 250 prefectures, and the top 20 provinces in equilibrium, there was little difference in the scale of development at the multiscale level with an R2 > 0.90. The results enriched our understanding of urban development in terms of Zipf’s law and had valuable implications for relevant decision-makers and stakeholders.

Australian Lidar Measurements of Aerosol Layers Associated with the 2015 Calbuco Eruption

The Calbuco volcano in southern Chile (41.3° S, 72.6° W) underwent three separate eruptions on 22–23 April 2015. Following the eruptions, distinct layers of enhanced lidar backscatter at 532 nm were observed in the lower stratosphere above Buckland Park, South Australia (34.6° S, 138.5° E), and Kingston, Tasmania (43.0° S, 147.3° E), during a small set of observations in April–May 2015. Using atmospheric trajectory modelling and measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) space-borne lidar and the Ozone Mapping Profiler Suite (OMPS) instrument on the Suomi National Polar-orbiting Partnership (NPP) satellite, we show that these layers were associated with the Calbuco eruptions. Buckland Park measurements on 30 April and 3 May detected discrete aerosol layers at and slightly above the tropopause, where the relative humidity was well below saturation. Stratospheric aerosol layers likely associated with the eruptions were observed at Kingston on 17 and 22 May in narrow discrete layers accompanied by weaker and more vertically extended backscatter. The measurements on 22 May provided a mean value of the particle linear depolarisation ratio within the main observed volcanic aerosol layer of 18.0 ± 3.0%, which was consistent with contemporaneous CALIOP measurements. The depolarisation measurements indicated that this layer consisted of a filament dominated by ash backscatter residing above a main region having likely more sulfate backscatter. Layer-average optical depths were estimated from the measurements. The mean lidar ratio for the volcanic aerosols on 22 May of 86 ± 37 sr is consistent with but generally higher than the mean for ground-based measurements for other volcanic events. The inferred optical depth for the main volcanic layer on 17 May was consistent with a value obtained from OMPS measurements, but a large difference on 22 May likely reflected the spatial inhomogeneity of the volcanic plume. Short-lived enhancements of backscatter near the tropopause of 17 May likely represented the formation cirrus that was aided by the presence of associated volcanic aerosols. We also provide evidence that gravity waves potentially influenced the layers, particularly in regard to the vertical motion observed in the strong layer on 22 May. Overall, these observations provide additional information on the dispersal and characteristics of the Calbuco aerosol plumes at higher southern latitudes than previously reported for ground-based lidar measurements.

Identification of Shrinkage and Growth Patterns of a Shrinking City in China Based on Nighttime Light Data: A Case Study of Yichun

Urban shrinkage has become a topic of major concern to scholars of geography and urban science. However, the methods of identifying urban shrinkage and growth have mostly focused on traditional statistical methods, and studies based on nighttime light (NTL) data are rare. Here, we use the NTL data for 56 months from 2012 to 2019 obtained by the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar Orbiting Partnership (NPP) to identify the shrinkage and growth patterns of Yichun in China, by calculating the slope of the NTL radiance value after denoising. At the same time, by combining high-resolution Google satellite images and traditional demographic data, we analyzed the shrinkage characteristics of Yichun. The results of the study confirmed the characteristics of partial shrinkage in China’s shrinking cities. In addition, the use of NPP-VIIRS NTL data was able to more accurately identify the urban shrinkage and growth patterns, and may also be seen to present a more objective picture of reality, thus providing a new perspective for studies of urban shrinkage.

Enhanced Aerosol Estimations From Suomi-NPP VIIRS Images Over Heterogeneous Surfaces

The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (NPP) is a new-generation polar-orbiting satellite imaging sensor. It has generated a variety of operational products similar to the widely used Moderate Resolution Imaging Spectroradiometer (MODIS) products. However, there are high uncertainties in official VIIRS aerosol products based on our previous validations, and a reduction in these uncertainties is needed before they can be used with confidence. To this end, we developed a revised high-spatial-resolution aerosol retrieval algorithm which can considerably improve the aerosol optical depth (AOD) estimations. The improvements mainly arise from: 1) correction of the surface bidirectional reflectance using the RossThick-LiSparse model with parameters obtained from the MODIS bidirectional reflectance distribution function (BRDF)/Albedo products; 2) finer customized monthly aerosol types assumed from the historical Aerosol Robotic Network (AERONET) measurements of optical properties; and 3) improved cloud screening with the revised dynamic threshold cloud detection algorithm. The new 750-m AOD retrievals are validated against AERONET AOD measurements and compared with the official VIIRS AOD products from 2014 to 2017 over the Beijing–Tianjin–Hebei region in China. The results illustrated that the retrievals are highly consistent with ground measurements ( $R = 0.926$ ), with ~72% of them falling within the expected error of [±(0.05 + 20%)] on a regional scale. The mean absolute error is 0.082 and the root-mean-square error is 0.120. The new algorithm can significantly reduce the overestimations and improve the aerosol estimations over heterogeneous urban surfaces compared to the official aerosol products, especially in winter. This new VIIRS AOD product will thus be more useful for air pollution studies over medium- or small-scale areas.

Are Karst Rocky Desertification Areas Affected by Increasing Human Activity in Southern China? An Empirical Analysis from Nighttime Light Data.

Due to remarkable socioeconomic development, an increasing number of karst rocky desertification areas have been severely affected by human activities in southern China. Effectively analyzing human activities in karst rocky desertification areas is a critical prerequisite for managing and restoring areas with tremendous negative impacts from desertification. At present, a timely and accurate way of quantifying the spatiotemporal variations of human activities in karst rocky desertification areas is still lacking. In this communication, we attempted to quantify human activities from the corrected Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) nighttime light composite data from 2012 to 2018 based on statistical analysis. The results show that a significant increase of night lights could be clearly identified during the study period. The total nighttime lights (TL) related to severe karst rocky desertification (S) were particularly concentrated in Guizhou and Yunnan. The nighttime light intensity (LI) related to the S areas in Chongqing was the strongest due to its rapid socioeconomic development. The annual growth rate of nighttime lights (GL) has been slow or even negative in Guangdong because of its various karst rocky desertification restoration programs. This communication could provide an effective approach for quantifying human activities and provide useful information about where prompt attention is required for policy-making on the restoration of the karst rocky desertification areas.

Preliminary Dual-Satellite Observations of Atmospheric Gravity Waves in Airglow

Atmospheric gravity waves (AGWs) are among the important energy and momentum transfer mechanisms from the troposphere to the middle and upper atmosphere. Despite their understood importance in governing the structure and dynamics of these regions, mesospheric AGWs remain poorly measured globally, and largely unconstrained in numerical models. Since late 2011, the Suomi National Polar-orbiting Partnership (NPP) Visible/Infrared Imaging Radiometer Suite (VIIRS) day–night band (DNB) has observed global AGWs near the mesopause by virtue of its sensitivity to weak emissions of the OH* Meinel bands. The wave features, detectable at 0.75 km spatial resolution across its 3000 km imagery swath, are often confused by the upwelling emission of city lights and clouds reflecting downwelling nightglow. The Ionosphere, Mesosphere, upper Atmosphere and Plasmasphere (IMAP)/ Visible and near-Infrared Spectral Imager (VISI) O2 band, an independent measure of the AGW structures in nightglow based on the International Space Station (ISS) during 2012–2015, contains much less noise from the lower atmosphere. However, VISI offers much coarser resolution of 14–16 km and a narrower swath width of 600 km. Here, we present preliminary results of comparisons between VIIRS/DNB and VISI observations of AGWs, focusing on several concentric AGW events excited by the thunderstorms over Eastern Asia in August 2013. The comparisons point toward suggested improvements for future spaceborne airglow sensor designs targeting AGWs.

GDP spatialization in Ningbo City based on NPP/VIIRS night-time light and auxiliary data using random forest regression

Accurate spatial distribution information on gross domestic product (GDP) is of great importance for the analysis of economic development, industrial distribution and urbanization processes. Traditional administrative unit-based GDP statistics cannot depict the detailed spatial differences in GDP within each administrative unit. This paper presents a study of GDP spatialization in Ningbo City, China based on National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL) data and town-level GDP statistical data. The Landsat image, land cover, road network and topographic data were also employed as auxiliary data to derive independent variables for GDP modelling. Multivariate linear regression (MLR) and random forest (RF) regression were used to estimate GDP at the town scale and were assessed by cross-validation. The results show that the RF model achieved significantly higher accuracy, with a mean absolute error (MAE) of 109.46 million China Yuan (CNY)·km−2 and a determinate coefficient (R2 = 0.77) than the MLR model (MAE = 161.8 million CNY·km−2, R2 = 0.59). Meanwhile, by comparing with the estimated GDP data at the county level, the town-level estimated data showed a better performance in mapping GDP distribution (MAE decreased from 115.1 million CNY·km−2 to 74.8 million CNY·km−2). Among all of the independent variables, NTL, land surface temperature (Ts) and plot ratio (PR) showed higher impacts on the GDP estimation accuracy than the other variables. The GDP density map generated by the RF model depicted the detailed spatial distribution of the economy in Ningbo City. By interpreting the spatial distribution of the GDP, we found that the GDP of Ningbo was high in the northeast and low in the southwest and formed continuous clusters in the north. In addition, the GDP of Ningbo also gradually decreased from the urban centre to its surrounding areas. The produced GDP map provides a good reference for the future urban planning and socio-economic development strategies.

Satellite data cloud detection using deep learning supported by hyperspectral data

ABSTRACTDeep learning methods can play an important role in satellite data cloud detection. The number and quality of training samples directly affect the accuracy of cloud detection based on deep learning. Therefore, selecting a large number of representative and high-quality training samples is a key step in cloud detection based on deep learning. For different satellite data sources, choosing sufficient and high-quality training samples has become an important factor limiting the application of deep learning in cloud detection. This paper presents a fast method for obtaining high-quality learning samples, which can be used for cloud detection of different satellite data with deep learning methods. AVIRIS (Airborne Visible Infrared Imaging Spectrometer) data, which have 224 continuous bands in the spectral range from 400–2500 nm, are used to provide cloud detection samples for different types of satellite data. Through visual interpretation, a sufficient number of cloud and clear sky pixels are selected from the AVIRIS data to construct a hyperspectral data sample library, which is used to simulate different satellite data (such as data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Operational Land Imager (OLI) satellites) as training samples. This approach avoids selecting training samples for different satellite sensors. Based on the Keras deep learning framework platform, a backpropagation (BP) neural network is employed for cloud detection from Landsat 8 OLI, National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) and Terra MODIS data. The results are compared with cloud coverage results interpreted via artificial vision. The results demonstrate that the algorithm achieves good cloud detection results for the above data, and the overall accuracy is greater than 90%.

Multiscale analysis on spatiotemporal dynamics of energy consumption CO2 emissions in China: Utilizing the integrated of DMSP-OLS and NPP-VIIRS nighttime light datasets

CO2 emissions caused by socioeconomic development and energy consumption in China have put enormous pressure on emissions reduction for Chinese government. In response to CO2 emissions reduction in China, this study integrated the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) stable nighttime light (SNL) data and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) composite data, and established the integrated nighttime light datasets from 1992 to 2016. The estimated CO2 emissions model utilizing the integrated nighttime light datasets and statistical CO2 emissions at the provincial level from 1995 to 2016 were established. Finally, spatiotemporal dynamics of CO2 emissions were simulated from multiscale. The results clearly showed that: (1) The fitting results of regression relationship between DMSP-OLS SNL data and NPP-VIIRS composite data met the accuracy requirements. The CO2 emissions estimated model was valid. (2) The total amount of energy consumption CO2 emissions in China had increased from 1889.3340 Mt in 1995 to 4683.3165 Mt in 2016, with a total growth of 2.47 times. (3) The high CO2 emissions regions were clearly agglomerated in eastern coastal China from the pixel scale, the highest CO2 emissions provinces were concentrated in Hebei and Shandong, the high CO2 emissions prefecture cities were concentrated in Around Bohai Gulf area, eastern coastal China and some developed cities, and the high CO2 emissions counties were concentrated in eastern coastal China and western energy intensive counties. (4) The relatively-slow growth accounted for the highest proportion among the five growth types, and the CO2 emissions rapid growth regions were concentrated in eastern China at provincial, prefectural and county scale. The western regions accounted for the largest area proportion in five growth types at prefectural scale. We provided policy implications based on the results, which was beneficial to propose mitigation CO2 emissions reduction in China.

Evaluation of Luojia 1-01 nighttime light imagery for impervious surface detection: A comparison with NPP-VIIRS nighttime light data

Impervious surface detection is significant to urban dynamic monitoring and environment management. One of the most effective approaches to evaluating the impervious surface is the use of nighttime light imagery. However, little work on this subject was carried out with the new generation nighttime light data from Luojia 1-01 satellite, which has a finer spatial resolution than the predecessors such as the nightlight data from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) Satellite. Therefore, this study conducted the first investigation of the capacity of Luojia 1-01 nighttime light data in detecting the extent and degree of impervious surfaces. Focusing on three cities of Beijing, Shanghai, and Guangzhou, several maps of the spatial extent of impervious surface areas were first extracted from two types of nighttime lights data (Luojia 1-01 and NPP-VIIRS data) by applying a dynamic threshold segmentation method. Meanwhile, a series of polynomial regression models were adopted to estimate the relation between imperiousness degree and light intensity. The results compared with the reference data derived from Landsat 8 Operational Land Imager (OLI) show that Luojia 1-01 data can produce a more precise map of the spatial extent of impervious surfaces than NPP-VIIRS data owing to the finer spatial resolution and the wider measurement range. Nevertheless, Luojia 1-01 data failed to provide reliable estimates of the imperviousness degree in comparison with NPP-VIIRS data as this nighttime light imagery with finer spatial resolution can better discriminate the surfaces that have the same imperviousness degree but are illuminated with different light intensities, consequently resulting in a weak correlation between imperviousness degree and light intensity. The over- and under-estimates of imperviousness degree suggested an increase in spatial resolution of nightlight imagery does not always improve the accuracy and reliability of nighttime light-based estimations. These study results confirmed that Luojia 1-01 nightlight imagery is a potential and promising data source for mapping the spatial extent of impervious surface areas, but difficult to accurately estimate the imperviousness degree. Future research may improve the accuracy of imperviousness degree estimation by integrating the Luojia 1-01 nightlight imagery with other useful data sources.

Measuring internal solitary wave parameters based on VIIRS/DNB data

ABSTRACT The day/night band (DNB) mounted on the National Polar-Orbiting Partnership has powerful environmental detection capabilities. It can be used to observe internal solitary waves (ISWs) using sunglint during the day and moonglint at night. In this article, the two-dimensional Stockwell transform method was introduced into the ISW observation from single DNB images to determine the horizontal wavelength and propagation direction distribution of ISWs. This allowed us to achieve quantitative measurements of ISW parameters under both day and night conditions. In addition, by using paired images of daytime and night-time ISWs near Dongsha Atoll, Taiwan, China, ISW information contained in the two images could be coupled, allowing us to track ISW propagation. The displacements of the paired ISWs were measured, and thus, the average propagation speeds were calculated to be 1.70, 2.25, and 2.49 m s–1, respectively.

Radiometric Inter-Consistency of VIIRS DNB on Suomi NPP and NOAA-20 from Observations of Reflected Lunar Lights over Deep Convective Clouds

The Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) is capable of observing reflected lunar radiances at night with its high gain stage (HGS), and the radiometric calibration is traceable to the sun through gain transfer from the low gain stage (LGS) calibrated near the terminator with the solar diffuser. Meanwhile, deep convective clouds (DCC) are known to have a stable reflectance in the visible spectral range. Therefore, the reflected lunar radiance at night from the DCC provides a unique dataset for the inter-calibration of VIIRS DNB on different satellites such as Suomi National Polar-orbiting Partnership (NPP) and NOAA-20, as well as quantifying the lunar radiance as a function of lunar phase angle. This study demonstrates a methodology for comparing nighttime Suomi NPP and NOAA-20 VIIRS DNB measured DCC reflected lunar radiance at various phase angles using data from July 2018 to March 2019 with an 86 second sampling interval and comparing Suomi NPP VIIRS DNB measured lunar radiances with those from lunar model predictions. The result shows good consistency between these two instruments on the two satellites, although a low bias in the NOAA-20 VIIRS DNB of ~5% is found. Also, observed lunar radiance from VIIRS DNB on Suomi NPP is found to be consistent with model predictions within 3% ± 5% (1σ) for a large range of lunar phase angles. However, discrepancies are significant near full moon, due to lunar opposition effects, and limitations of the lunar models. This study is useful not only for monitoring the DNB calibration stability and consistency across satellites, but also may help validate lunar models independently.

Cross-Comparison between MODIS and VIIRS Snow Cover Products for the 2016 Hydrological Year

The VIIRS (Visible Infrared Imaging Radiometer Suite) instrument on board the Suomi-NPP (National Polar-Orbiting Partnership) satellite aims to provide long-term continuity of several environmental data series including snow cover initiated with MODIS (Moderate Resolution Imaging Spectroradiometer). Although it is speculated that MODIS and VIIRS snow cover products may differ because of their differing spatial resolutions and spectral coverage, quantitative comparisons between their snow products are currently limited. Therefore, this study intercompares MODIS and VIIRS snow products for the 2016 Hydrological Year over the Midwestern United States and southern Canada. Two hundred and forty-four swath snow products from MODIS/Aqua (MYD10L2) and the VIIRS EDR (Environmental Data Records) (VSCMO/binary) were intercompared using confusion matrices, comparison maps and false color imagery. Thresholding the MODIS NDSI (Normalized Difference Snow Index) Snow Cover product at a snow cover fraction of 30% generated binary snow maps are most comparable to the NOAA VIIRS binary snow product. Overall agreement between MODIS and VIIRS was found to be approximately 98%. This exceeds the VIIRS accuracy requirements of 90% probability of correct typing. The agreement was highest during the winter but lower during late fall and spring. MODIS and VIIRS often mapped snow/no-snow transition zones as a cloud. The assessment of total snow and cloud pixels and comparison snow maps of MODIS and VIIRS indicate that VIIRS is mapping more snow cover and less cloud cover compared to MODIS. This is evidenced by the average area of snow in MYD10L2 and VSCMO being 5.72% and 11.43%, no-snow 26.65% and 28.67% and cloud 65.02% and 59.91%, respectively. While VIIRS and MODIS have a similar capacity to map snow cover, VIIRS has the potential to map snow cover area more accurately, for the successful development of climate data records.

Evaluating the Potential of LJ1-01 Nighttime Light Data for Modeling Socio-Economic Parameters.

The LJ1-01 satellite is the first dedicated nighttime light remote sensing satellite in the world and offers a higher spatial resolution than the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) satellites of the United States. This study compared the LJ1-01 nighttime light data with NPP/VIIRS data in the context of modeling socio-economic parameters. In the eastern and central regions of China, 10 parameters from the four aspects of gross regional product (annual average population, electricity consumption, and area of land in use) were selected to build linear regression models. The results showed that the LJ1-01 nighttime light data offered better potential for modeling socio-economic parameters than the equivalent NPP/VIIRS data; the former can be an effective tool for establishing models for socio-economic parameters. There were significant positive correlations between the two types of nighttime light data and the 10 socio-economic parameters; that for the gross regional product was the highest.

The Terra Vega Active Light Source: A First Step in a New Approach to Perform Nighttime Absolute Radiometric Calibrations and Early Results Calibrating the VIIRS DNB

A fully automated, National Institute of Standards and Technology (NIST)-traceable artificial light source called Terra Vega has been developed to radiometrically calibrate the Visible Infrared Imaging Radiometer (VIIRS) Day Night Band (DNB) working in high gain stage (HGS) mode. The Terra Vega active point source is a calibrated integrating sphere that is only a fraction in size of a VIIRS DNB pixel. As such, it can be considered analogous to a ground-based photometric reference star. Vicarious calibrations that employ active point sources are different than those that make use of traditional extended sources and can be applyed to quantify the brightness of artificial light sources. The active source is successfully fielded, and early results indicate that it can be used to augment and validate the radiometric calibration of the VIIRS DNB HGS sensor on both the Suomi National Polar-orbiting Partnership (NPP) and NOAA-20 satellites. The VIIRS DNB HGS sensor can benefit from this technology as on-board calibration is challenging and hinges on transferring low gain stage (LGS) calibration using a solar diffuser to the medium gain stage (MGS) and HGS via regions of overlap. Current vicarious calibration methods that use a lunar-illuminated extended source estimate the HGS radiometric accuracy to within 8-15%. By comparison, early results and analysis showed that Terra Vega is stable to about 1%. Under clear dark night conditions, predicted top-of-atmosphere radiance from Terra Vega ranged between 1–11% of VIIRS measured values. Terra Vega’s excellent stability opens up new opportunities to validate and develop nighttime imaging applications based on point sources.

Measurement of blooming effect of DMSP-OLS nighttime light data based on NPP-VIIRS data

ABSTRACTNighttime light (NTL) imagery offers important data for socio-economic research since it depicts human activities at night. Blooming effect is one of the main problems of DMSP-OLS NTL data, but the problem has been largely mitigated in NPP-VIIRS data. Blooming effect smooths light intensity through diffusing the brightness from the bright area to the dark areas. This effect could be quantified by the alteration of spatial heterogeneity in light intensity which can be represented by spatial texture indices. Taking NPP-VIIRS data as the standard, this study calculates relative difference of spatial texture indices between NPP-VIIRS and DMSP-OLS images to measure the blooming effect of DMSP-OLS data at pixel scale in mainland China. Results show that within the real urban area, spatial texture indices of DMSP-OLS pixels are generally smaller than that of NPP-VIIRS, suggesting that blooming effect underestimates spatial heterogeneity and it is more serious towards to urban centres where nighttime light is stronger. DMSP-OLS underestimates 90% spatial heterogeneity when NPP-VIIRS value >10. On the contrary, in the region outside real urban area, spatial texture indices of DMSP-OLS data are greater than that of NPP-VIIRS, suggesting that blooming effect introduces fake spatial heterogeneity outside the real urban area.Abbreviations: NTL: Nighttime light; DMSP: Defense Meteorological Satellite Program; OLS: Operational Linescan System; NPP: National Polar-orbiting Partnership; VIIRS: Visible Infrared Imaging Radiometer Suite; NOAA: The National Oceanic and Atmospheric Administration; NGDC: The National Geophysical Data Center; NCV: Normalized coefficient of variation; DN: Digital number

An image layer difference index method to extract light area from NPP/VIIRS nighttime light monthly data

ABSTRACTNighttime light data have been proven to perform well for economic measurements and built-up area extractions. However, the new generation of monthly NPP/VIIRS data series products, which collected from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) Satellite contains background values, which relatively restrict the potential application of nighttime images. Therefore, the image layer difference index (LDI) was constructed to obtain high-intensity pixels that have radiance mainly caused by urban light glow. In addition, an empirical threshold was used to extract low-intensity pixels. Thirty-eight counties in Chongqing Province in China were used as an example for this experimental research. To verify the accuracy of the proposed method, a linear regression model, which was based on the quantitative statistics of the pixels, exhibited the coefficient of determination R2 values of 0.980 and 0.947. Considering the interrelation between the light intensity and economic level, statistical data of the county-level economy was also used for further confirmation; the R2 values of the linear regression between the computed indexes were 0.924 and 0.909.

Evolution of a Mesospheric Bore in a Duct Observed by Ground‐Based Double‐Layer Imagers and Satellite Observations Over the Tibetan Plateau Region

AbstractA mesospheric bore event was observed in the airglow layers of both OH and OI (557.7 nm) bands by two all‐sky airglow imagers in Lhasa (29.66°N, 90.98°E) on the Tibetan Plateau and the Day Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar‐orbiting Partnership (NPP) satellite on the night of 16–17 December 2014. Simultaneous temperature and OH intensity observations from the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument onboard the TIMED satellite and wind measurement by a Doppler meteor radar were used to characterize the environment of the bore propagation. A large mesospheric inversion layer was identified from the temperature measured by the SABER instrument. The observed winds in the height range of the OH layer were almost orthogonal to the propagation direction of the mesospheric bore. Both hydraulic jump theory and observations showed that the duct initially shrank followed by an expansion. The duct mainly existed in the OH layer but was weak in the OI layer, as revealed by the double‐layer imaging and satellite observations. The horizontal wavelengths and observed phase speeds of the bore packet decreased as the duct shrank and increased as the duct expanded. The intensity amplitude of the bore packet decreased slowly and then decreased sharply after dissipation. With the variation of the depth of the duct, the bore may have leak out of the duct. The presented study advances the understanding of mesospheric bore evolution and how the ducted environment influences the propagation of the bore.

Interannual Variation in Night-Time Light Radiance Predicts Changes in National Electricity Consumption Conditional on Income-Level and Region

Using remotely-sensed Suomi National Polar-orbiting Partnership (NPP)-VIIRS (Visible Infrared Imagery Radiometer Suite) night-time light (NTL) imagery between 2012 and 2016 and electricity consumption data from the IEA World Energy Balance database, we assemble a five-year panel dataset to evaluate if and to what extent NTL data are able to capture interannual changes in electricity consumption within different countries worldwide. We analyze the strength of the relationship both across World Bank income categories and between regional clusters, and we evaluate the heterogeneity of the link for different sectors of consumption. Our results show that interannual variation in nighttime light radiance is an effective proxy for predicting within-country changes in power consumption across all sectors, but only in lower-middle income countries. The result is robust to different econometric specifications. We discuss the key reasons behind this finding. The regions of Sub-Saharan Africa, Middle-East and North Africa, Latin America and the Caribbeans, and East Asia and the Pacific render a significant outcome, while changes in Europe, North America and South Asia are not successfully predicted by NTL. The designed methodological steps to process the raw data and the findings of the analysis improve the design and application of predictive models for electricity consumption based on NTL at different spatio-temporal scales.

Mesospheric Bore Observations Using Suomi-NPP VIIRS DNB during 2013–2017

This paper reports mesospheric bore events observed by Day/Night Band (DNB) of the Visible/Infrared Imaging Radiometer Suite (VIIRS) on the National Oceanic and Atmospheric Administration/National Aeronautics and Space Administration (NOAA/NASA) Suomi National Polar-orbiting Partnership (NPP) environmental satellite over five years (2013–2017). Two types of special mesospheric bore events were observed, enabled by the wide field of view of VIIRS: extremely wide bores (&gt;2000 km extension perpendicular to the bore propagation direction), and those exhibiting more than 15 trailing crests and troughs. A mesospheric bore event observed simultaneously from space and ground was investigated in detail. DNB enables the preliminary global observation of mesospheric bores for the first time. DNB mesospheric bores occurred more frequently in March, April and May. Their typical lengths are between 300 km and 1200 km. The occurrence rate of bores at low latitudes is higher than that at middle latitudes. Among the 61 bore events, 39 events occurred in the tropical region (20°S–20°N). The high occurrence rate of mesospheric bores during the spring months in the tropical region coincides with the reported seasonal and latitudinal variations of mesospheric inversion layers.