Defense Meteorological Satellite Program Research Articles

Spatio-temporal dynamics of urban residential CO2 emissions and their driving forces in China using the integrated two nighttime light datasets

Increasing urban residential energy consumption and CO2 emissions pose a critical challenge for regional carbon reduction policy. This study integrated two nighttime light datasets: the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) nighttime light images and the Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) composite data to improve on estimates of urban residential CO2 emissions from 2000 to 2015 at 1 km resolution. Then, the driving forces including socio-economic factors and climatic factors were discussed using spatial econometrics models based on panel data covering 288 prefecture-level cities. The results show that models built for the northern and southern regions separately performed better than those for the entire country in estimating urban residential CO2 emissions, which strongly suggests that climatic factors affect the behavior of urban residents and CO2 emissions. The spatio-temporal analysis revealed that rapid growth in emissions occurred in provincial capitals and was mainly concentrated in central China. Gross Domestic Product and energy utilization technology were associated with higher CO2 emission while GDP per capita and the number of employed workers had a negative effect. Measures based on daily mean temperatures had a substantial negative correlation with CO2 emissions. In contrast, the average of daily maximum air temperature in summer correlated with higher CO2 emissions. We conclude that extreme weather events and energy efficiency should be of particular concern for policy makers.

Examining the spatial variations of determinants of energy-related CO2 emissions in China at the city level using Geographically Weighted Regression Model

Cities produce over 70% of the global CO2 emissions that result from energy use, and thus play a key role in climate mitigation and adaptation. While the factors influencing CO2 emissions have been subject to extensive study, via research that has explored the path of developing a low-carbon economy, little work has been undertaken at the city level as a result of a deficiency in data availability. Addressing this gap, this study firstly estimated CO2 emissions of cities in China using Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) nighttime light imagery. We then analyzed spatial variations in the estimated CO2 emissions at the city level, using a spatial analytical model, finding significant spatial autocorrelation in CO2 emissions. Subsequently, we compared the effects of different socioeconomic factors on CO2 emissions, using both global and local regression models. The results from the global regression model revealed that private car ownership, economic growth, and energy consumption were the major factors promoting CO2 emissions in China’s cities, while population density had an effect in reducing CO2 emissions. The use of a Geographically Weighted Regression (GWR) model provided more detailed results, revealing significant spatial heterogeneity in the impacts of different factors. Economic growth, private car ownership, and energy consumption all posed positive effects on CO2 emissions while the remainder of the factors studied were found to pose a bidirectional impact on CO2 emissions in different areas of China. Economic growth and private car ownership were to found to exert the strongest positive effects in the cities of western and central China, and energy consumption was shown to significantly and positively influence CO2 emissions in the southernmost part of China. Urban expansion and road density were identified as key promoting factors in CO2 emissions in the northeast of China; and the industrial structure demonstrated significantly positive effects in relation to CO2 levels in cities located in the Beijing-Tianjin-Hebei region. The role of foreign direct investment (FDI) was not found to be significant in most cities expect Guangdong, where a significant positive relationship appeared.

ESTIMATING INDUSTRIAL STRUCTURE CHANGES IN CHINA USING DMSP – OLS NIGHT-TIME LIGHT DATA DURING 1999–2012

Abstract. The Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) night-time light imagery has been proved to be a powerful tool to monitor economic development with its relatively high spatial resolution at large scales. Night-time lights caused by human activities derived from DMSP-OLS satellite imagery are widely used in socioeconomic parameter estimations and urbanization monitoring. In this paper, DMSP-OLS night-time stable light data from 1999 to 2012 are utilized to analyze inter-annual variation in GDP of per unit light intensity (RGDP) in China. Furthermore, RGDP was compared with statistical data of the tertiary industry structure for 28 provincial regions. The results show that the provincial RGDP decreased abruptly in 2001–2002, 2008–2009 and 2011–2012, which is consistent with the proportional growth of the tertiary industry in GDP. These results indicate that the changes in RGDP can reflect tertiary industry structural changes in China's province-level regions.

Detecting spatiotemporal dynamics of PM2.5 emission data in China using DMSP-OLS nighttime stable light data

Haze pollution in China is getting worse with the rapid growth of economy and urbanization rate, which is harmful to human health and closely related with China's sustainable development. In response to PM2.5 pollution problem in China, this study first analyzed the correlation between the intercalibrated Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) sensor nighttime stable light (NSL) data and statistical PM2.5 emissions at the provincial level from 1992 to 2012 respectively and the results demonstrated that there was a positive correlation between the intercalibrated DMSP-OLS NSL data and PM2.5 emissions. Then linear regression analysis was proposed to simulate spatiotemporal dynamics of PM2.5 emission at the 1 km resolution level in China by the intercalibrated DMSP-OLS NSL data and PM2.5 emission. Spatiotemporal dynamics of PM2.5 emission were analyzed from national scale down to regional and urban agglomeration scales. The results clearly showed that the variations of PM2.5 emissions in different regions and urban agglomerations were different and large. The high growth type and high grade of PM2.5 emissions were mainly located in the Eastern region, Central region, Shandong Peninsula and Beijing-Tianjin-Tangshan, with significant lower concentrations in the Western region, Northeastern region, Sichuan-Chongqing and Middle south of Liaoning. Considering the spatial and temporal patterns of PM2.5 emissions between the four economic regions, the mitigation strategies for Eastern and Central China should mainly focus on the industry structure adjustments, while Western and Northern China should pay more attention to the optimizations of regional energy structures and improvements of energy efficiencies. The results of this study is not only beneficial to understand accurately the regional discrepancies of spatiotemporal PM2.5 emission dynamics, but also helpful for proposing mitigation policies in air pollution control and providing scientific support for regional sustainable development.

Sea Ice Sensing From GNSS-R Data Using Convolutional Neural Networks

In this letter, a scheme that uses convolutional neural networks (CNNs) is proposed for sea ice detection and sea ice concentration (SIC) prediction from TechDemoSat-1 Global Navigation Satellite System Reflectometry delay-Doppler maps (DDMs). Specifically, a classification-orientated CNN was designed for sea ice detection and a regression-based one for SIC estimation. Here, DDM images were used as input, and SIC data from Nimbus-7 Scanning Multi-Channel Microwave Radiometer and Defense Meteorological Satellite Program Special Sensor Microwave Imager-Special Sensor Microwave Imager/Sounder sensors were modified as targeted output. In the experimental phase, the CNN output resulted from inputting full-size DDM data (128-by-20 pixels) showed better accuracy than that of the existing NN-based method. Besides, both CNNs and NNs with further processed input data (40-by-20 pixels, and with a fixed position in each image) were evaluated and the performance of both networks was enhanced. It was found that when DDM data are adequately preprocessed, CNNs and NNs share similar accuracy; otherwise the former outperforms the latter. Further conclusion was thus drawn that CNNs were more tolerant to the data format changes than NNs.

Analysis of the Dynamic Urban Expansion Based on Multi-Sourced Data from 1998 to 2013: A Case Study of Jiangsu Province

Recently, with the fast speed of urban expansion, research concerning the regulation of urban built-up area expansion is a significant topic, especially in Eastern China with its high urbanization level. The Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) nighttime light data has a high association with the urban-rural distribution, which provides a new method to study urban expansion effectively and with relatively high accuracy. Between 1998 and 2013, China experienced a rapid economic development period, making it crucial to learn the patterns and driving forces to better manage urban master planning and sustainable development. The urban built-up area for the research years are mapped, and the annual urban expansion speed, urbanization intensity index, and built-up area gravity center are analyzed in this paper. The results will show that the amount of the urban built-up area grows continuously from 1998 to 2008, with the development focus in southern Jiangsu, while from 2008 to 2013, the development center moves to northern Jiangsu. The main driving forces behind this urban built-up area expansion are population growth and economic development.

Spatio-temporal simulation of energy consumption in China's provinces based on satellite night-time light data

Delay in publication of energy statistics prevents a timely assessment of progress towards meeting targets for energy saving and emission reduction in China. This makes it difficult to meet the requirements to rapidly monitor and evaluate energy consumption for each province. In this study, an alternative approach is provided to estimate the energy consumption by using satellite remote sensing data. We develop spatio-temporal geographically weighted regression models to simulate energy consumption of provinces in China based on the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) global stable night-time light data. The models simulate China’s energy consumption accurately with the goodness of fit higher than 99%. Generally, the national average annual energy consumption is 2.8 billion tonnes of coal equivalent in China between 2000 and 2013, which is close to the actual value with errors smaller than 0.1%. From both temporal and spatial dimensions, the relative errors are smaller than 5.5% at the provincial level. Therefore, the use of satellite night-time light data provides a useful reference in monitoring and assessing provincial energy consumption in China.

Quantitative Responses of Satellite-Derived Nighttime Lighting Signals to Anthropogenic Land-Use and Land-Cover Changes across China

Remotely sensed artificial lighting radiances at night can provide spatially explicit proxy measures of the magnitude of human activity. Satellite-derived nighttime light images, mainly provided by the Defense Meteorological Satellite Program (DMSP) and the Visible Infrared Imaging Radiometer Suite (VIIRS) day/night band (DNB), have been increasingly used to study demographic and socioeconomic activities for a wide range of issues—for instance, human population dynamics, economic growth, and urbanization process—at multiple scales. In practice, the lack of texture information regarding man-made surfaces would usually lead to substantial difficulty in delineating the spatial dynamics in human settlements due to the diverse distributions of artificial nocturnal lighting sources, which are closely related to the predominant land-use/land-cover (LULC) types and their evolutions. An understanding of how nighttime lighting signals respond to synchronous anthropogenic LULC changes, therefore, is crucially important for the spatiotemporal investigations of human settlement dynamics. In this study, we used DMSP-derived nighttime light (NTL) data and Landsat-derived LULC maps to quantitatively estimate the pixel-level responses of NTL signals to different types of human-induced LULC conversions between 1995 and 2010 across China. Our results suggest that the majority (>70%) of pixel-level LULC conversions into artificial lands (including urban, rural, and built-up lands) might show a statistically significant increase in nighttime brightness with an average >20 (in digital number, DN) step change in nighttime lights (dNTL), both of which are distinctly higher than that in the LULC conversions into non-man-made surfaces on the whole. A receiver operating characteristic (ROC) curve-based analysis implies that we might have an average chance of ~90% to identify the nationwide LULC conversions into man-made surfaces from all types of conversions through the observed changes in artificial nocturnal luminosity signals. Moreover, ROC curve-based analyses also yield two nation-level optimal dNTL thresholds of 4.8 and 7.8 DN for recognizing newly emerged three types of artificial lands and urban lands between 1995 and 2010 across the entire country, respectively. In short, our findings reveal fundamental insights into the quantitative connections between the anthropogenic LULC changes and the corresponding responses of synchronous nightlight signals at the pixel-level, which are generally essential for further applications of satellite-derived nocturnal luminosity data in the spatiotemporal investigations of human settlement dynamics.

Interhemispheric Survey of Polar Cap Aurora

AbstractThis study investigates the interhemispheric nature of polar cap auroras via ultraviolet imaging, combined with particle data, to determine whether they occur on open or closed field lines. Data from the SSUSI (Special Sensor Ultraviolet Spectrographic Imager) instrument on board the DMSP (Defence Meteorological Satellite Program) spacecraft are examined. The DMSP spacecraft are in 90‐min orbits; hence, images of each hemisphere are separated by 45 min providing a good opportunity for interhemispheric study. 21 polar cap arc (PCA) events are recorded in December 2015 which have particle data from the SSJ/4 particle spectrometer associated with an arc in at least one hemisphere. Nine events are found to contain "arcs" consistent with a closed field line mechanism, that is, arcs associated with an ion signature present in both hemispheres. Six events contained arcs that were consistent with an "open field line" mechanism, that is, they were associated with electron‐only precipitation. Events containing arcs that were not consistent with either of these expectations are also explored, including an example of a "non‐conjugate" theta aurora and an interesting example of auroral morphology similar to a PCA which is associated with a geomagnetic storm. Seasonal effects are also investigated through a statistical analysis of PCAs over 4 months in 2015. It is found that PCAs are visible in the SSUSI data at least 20% of the time and that it is likely some are missed due to the spacecraft field of view and poor sensitivity in the summer hemisphere due to increased solar illumination.

Nighttime Enhancements in the Midlatitude Ionosphere and Their Relation to the Plasmasphere

AbstractIn situ electron density measurements by the CHAllenging Minisatellite Payload and the Defense Meteorological Satellites Program F17 satellites show that the midlatitude ionization at altitudes of ∼350 and 850 km is enhanced in the late evening. The enhancements increase to maximum around midnight and are clearly observed till early morning as the equatorial ionization decays to minimal level. They appear in the winter hemisphere during June and December solstices and in both hemispheres during equinox. The enhancements are well confined between ±30° and ±50° magnetic latitude, with the magnetic flux tubes of L = 1.3 − 2.4 connecting to the plasmasphere. Furthermore, coincident longitudinal variations exist in both the ionospheric enhancements and the plasmaspheric total electron content, especially during the solstice months. The coincidence may suggest essential plasma transport between the ionosphere and the plasmasphere. These facts support the idea that the plasmasphere provides extra plasma to the midlatitude ionosphere through downward plasma influx along the magnetic field lines to form the nighttime ionization enhancements when the sunlight is absent.

Mesoscale Plasma Convection Perturbations in the High‐Latitude Ionosphere

AbstractAn investigation of flow perturbations with spatial scale sizes between 100 and 500 km in the high‐latitude ionosphere is presented. These localized flow perturbations are deviations from the large‐scale background convection, expected to give us new insights into the magnetosphere‐ionosphere coupling process. Ion drift measurements from the Defense Meteorological Satellite Program F17 are utilized to identify these mesoscale flow perturbations. Our intent is to discover the properties of these perturbations in terms of perturbation flow speeds, location, scale size, and occurrence frequency as well as their dependence on the interplanetary magnetic field (IMF) and underlying large‐scale convection pattern. Observation suggests that flow perturbation locations strongly depend on the IMF orientation as does the occurrence frequency of the flow perturbations. For southward IMF, more flow perturbations occur in regions of sunward background flow than in regions of antisunward background flow. For flow perturbations with speeds over 300 m/s, an asymmetry in the preferred direction and scale size is seen for those embedded in sunward and antisunward background flows. Significantly less asymmetry is present for flow perturbations with speeds between 100 and 300 m/s. The flow perturbations exceeding 300 m/s are most likely closed locally with lower magnitude return flows or with adjacent flows across the convection reversal boundary and representing additional sources of frictional heating and momentum transfer to the thermosphere. The perturbation flow speed is almost independent of the scale size and underlying convection speed, but the largest speeds are preferentially seen at scale sizes between 200 and 300 km.

Coincident Observations by the Kharkiv IS Radar and Ionosonde, DMSP and Arase (ERG) Satellites, and FLIP Model Simulations: Implications for the NRLMSISE‐00 Hydrogen Density, Plasmasphere, and Ionosphere

AbstractThis paper reports the results of ionosphere and plasmasphere observations with the Kharkiv incoherent scatter radar and ionosonde, Defense Meteorological Satellite Program, and Arase (ERG) satellites and simulations with field line interhemispheric plasma model during the equinoxes and solstices of solar minimum 24. The results reveal the need to increase NRLMSISE‐00 thermospheric hydrogen density by a factor of ~2. For the first time, it is shown that the measured plasmaspheric density can be reproduced with doubled NRLMSISE‐00 hydrogen density only. A factor of ~2 decrease of plasmaspheric density in deep inner magnetosphere (L ≈ 2.1) caused by very weak magnetic disturbance (Dst > −22 nT) of 24 December 2017 was observed in the morning of 25 December 2017. During the next night, prominent effects of partially depleted flux tube were observed in the topside ionosphere (~50% reduced H+ ion density) and at the F2‐layer peak (~50% decreased electron density). The likely physical mechanisms are discussed.

Fundamental Climate Data Records of Microwave Brightness Temperatures

An intercalibrated Fundamental Climate Data Record (FCDR) of brightness temperatures (Tb) has been developed using data from a total of 14 research and operational conical-scanning microwave imagers. This dataset provides a consistent 30+ year data record of global observations that is well suited for retrieving estimates of precipitation, total precipitable water, cloud liquid water, ocean surface wind speed, sea ice extent and concentration, snow cover, soil moisture, and land surface emissivity. An initial FCDR was developed for a series of ten Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) instruments on board the Defense Meteorological Satellite Program spacecraft. An updated version of this dataset, including additional NASA and Japanese sensors, has been developed as part of the Global Precipitation Measurement (GPM) mission. The FCDR development efforts involved quality control of the original data, geolocation corrections, calibration corrections to account for cross-track and time-dependent calibration errors, and intercalibration to ensure consistency with the calibration reference. Both the initial SSMI(S) and subsequent GPM Level 1C FCDR datasets are documented, updated in near real-time, and publicly distributed.

From dispersed to clustered: New trend of spatial restructuring in China's metropolitan region of Yangtze River Delta

Rapid growth of metropolitan regions has become a key issue in relation to urban governance and planning in developing countries. The past decades have witnessed a dramatic spatial restructuring in metropolitan regions in China. Although many studies have been done, conclusions are yet to achieve consensus. Several main arguments still need to be discussed further: how to identify this spatial restructuring process; what is general trend of spatial restructuring; and how the spatial restructuring are affected by a variety of institutional and economic factors. This study aims to address these arguments by scrutinizing the Yangtze River Delta (YRD) of China as a case. We use a new data set, namely, nighttime light data derived from the Operational Linescan System of Defense Meteorological Satellite Program, to explore the spatial restructuring of YRD from 1992 to 2012. Results found that urban growth in YRD has been dominated by a “dispersed” pattern before the 2000s due to local industrialization and political decentralization. However, after the 2000s, a new “clustered” trend evolved in YRD, and inequalities in regional development tend to increase. A few politically or economically (or both) advantaged cities became new growth centres, while other cities grew slowly. These advantaged cities mainly were mega cities and province capital cities. A growth of importance of domestic consumer market gave more economic opportunities to these advantaged cities which had a large population size and a better political capability to adapt new economic situation. In particular, they were enabled to have more powers to make locally privileged policies to attract investments and population in the current process of deeply market-oriented forms in China.

Regional inequalities in comprehensive development in China from 1992 to 2013: Comparative estimation based on statistical and DMSP/OLS data

AbstractRegional inequality has attracted considerable interest among academics and policy makers. However, few studies have focused on regional inequality in comprehensive development. This study quantitatively estimated the regional inequalities and imbalances in China at multiple scales using gross domestic product (GDP), population, and the inter‐calibrated Defense Meteorological Satellite Program’s Operational Line‐Scan System (DMSP/OLS) nighttime stable light (NSL) data for 1992–2013. The results are as follows. First, the GDP‐derived inequalities exhibited an inverted U‐shaped pattern, while the NSL‐derived continued to decline. Second, for both GDP and NSL data, the inequality within the western region contributed most to the within‐region inequalities, while the eastern region contributed least. Third, the highest inter‐provincial inequality was observed in the developed area, while disparity within the underdeveloped area was the lowest. Finally, at the provincial level, the imbalances in comprehensive development generally decreased from 1992 to 2013. Moreover, a correlation analysis between the GDP‐ and NSL‐derived inequalities showed that there were some similarities in inequalities during 1992–2013, especially in the eastern region. These findings highlight that the regional inequalities in economic development and comprehensive development exhibit different tendencies, and hence it is crucial for both scholars and government to focus on this issue.

Monitoring surface mining belts using multiple remote sensing datasets: A global perspective

Quantifying the spatiotemporal change of land cover and understanding their ecological, environmental, and socioeconomic impacts are important for sustainable development. Surface mining by the minerals industry is one driver of the changes in land cover, leading to loss of natural vegetation and top soils, and interruption of ecosystem service flows. This study investigates the effectiveness of remote sensing datasets to identify and map land cover changes, with the specific goal of understanding the impact of surface mining activities on land cover globally from 1980s to 2013. Diverse remote sensing datasets with long term observations are analyzed, including high-resolution images in Google Earth, Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+)/Operational Land Imager (OLI), the Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Index (VI) product and Defense Meteorological Satellites Program (DMSP)/Operational Linescan System (OLS) stable night-time light. The results indicated that after entering 21st century, North America (e.g., the United States and Canada) was the only continent to have more surface mining spots categorized as Shrink type (rehabilitated) rather than Expand type. South America (e.g., Chile and Brazil) and Asia (e.g., India and China) had the highest proportions of Expand Type of surface mining spots. Detailed demonstrations on how those remote sensing datasets could help in mining spot monitoring are presented.

Poynting Flux in the Dayside Polar Cap Boundary Regions From DMSP F15 Satellite Measurements

AbstractPoynting flux, which describes electromagnetic energy flux, is an important energy source for the high‐latitude upper atmosphere. After the launch of Defense Meteorological Satellite Program (DMSP) F15 spacecraft with a boom‐mounted magnetometer on board, there was a new opportunity to calculate Earth‐directed Poynting flux at satellite altitudes (~850 km) in the upper atmosphere. A persistent enhancement of thermospheric density in the dayside polar cap boundary regions has been reported in the CHAMP satellite observations. To understand the significance of different physical mechanisms including Poynting flux and particle precipitation, and the correlation between them, a statistical study of Poytning flux and particle energy flux in the dayside cusp and low‐latitude boundary layer (LLBL) regions has been conducted based on DMSP F15 measurements. DMSP satellite observations showed a dominate downward Poynting flux for most cases in the cusp region. Our analysis of DMSP F15 data for five years (2000–2004) reveals that approximately 53% of 660 cusp crossings at 800–850 km showed strong downward Poynting flux (S > 10 mW/m2), 32% of the crossings had noticeable downward Poynting flux (S > 3 mW/m2), and 7% of the crossings did not show clear Poynting flux (S < 1 mW/m2). Only 13 out of 660 cusp crossings (~2%) showed noticeable upward Poynting flux. In the LLBL region, 35% of 11,641 LLBL crossings showed significant downward Poynting flux, 34% of the crossings had noticeable downward Poynting flux, and only 13% of the crossings did not show clear Poynting flux. On average, Poynting flux in LLBL is smaller than that in the cusp. The results show a slightly negative correlation between Poynting flux and particle precipitation energy flux in the dayside polar cap boundary regions. Statistically, Poynting flux in the cusp is enhanced during interplanetary magnetic field By positive conditions.

Urban Built-Up Area Extraction From Log- Transformed NPP-VIIRS Nighttime Light Composite Data

Accurate information on urban areas at regional and global scales is required for various socioeconomic and environmental applications. The nighttime light (NTL) composite data have proven to be an effective data source for extracting urban areas. Various urban mapping methods have been proposed in the literature to extract urban built-up areas from the Defense Meteorological Satellite Program’s Operational Linescan System NTL data with a variable accuracy. However, most of the previous methods cannot be directly applied to the NTL data derived from the Suomi National Polar-orbiting Partnership Satellite with the Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) sensor onboard. In this letter, we introduced a logarithmic transformation to preprocess the NPP-VIIRS NTL composite data. Then, four popular methods for urban built-up area extraction were tested using the original and log-transformed NTL data, respectively. The selected methods included the thresholding technique, Sobel-based edge detection, neighborhood statistics analysis, and watershed segmentation. The accuracy of the results was evaluated through validating the urban areas derived using each method against the referenced urban areas obtained from the National Land Cover Database for the U.S.. The results indicated that logarithmic transformation is an effective procedure for enhancing the difference between urban built-up areas and nonurban areas. The selected methods for urban built-up area extraction were found to perform better on the log-transformed NTL data than the original NTL data.

Exploring China's 21-year PM10 emissions spatiotemporal variations by DMSP-OLS nighttime stable light data

With the rapid growth of economy and urbanization rate, haze pollution is becoming more and more serious in China, and it is harmful to human health and China's sustainable development. For exploring spatiotemporal variations of PM10 pollution problem from 1992 to 2012 in China, we first proved that there existed a positive correlation between the intercalibrated Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) sensor nighttime stable light (NSL) data and PM10 emissions in this study. Then linear regression analysis was utilized to model spatiotemporal PM10 emission variations in China by the intercalibrated DMSP-OLS NSL data. PM10 emissions at prefectural level were selected as validation data for verifying the accuracy of spatiotemporal PM10 emissions variations and the results demonstrated that the DMSP-OLS NSL data can simulate PM10 emissions at 1 km resolution well. At last, spatiotemporal PM10 emission dynamics were analyzed from national scale down to regional and urban agglomeration scales. The results clearly noticed that the variations of PM10 emissions in different regions and urban agglomerations were different. The high-growth type of PM10 emissions was mainly located in the Eastern region, Central region, Western region, Shandong Peninsula, Wuhan Metropolitan Area and Beijing-Tianjin-Tangshan, with significant lower concentrations in the Northeastern region, Middle south of Liaoning and Pearl River Delta. The high grade of PM10 emissions was mainly distributed in the Eastern region, Central region and Shandong Peninsula, with significant lower concentrations in the Western region, Northeastern region, Sichuan-Chongqing. Considering the difference of temporal and spatial variations of PM10 emissions in the four regions, the mitigation strategy in the Eastern and Central China should mainly focus on the adjustment of industrial structure, while in Western and Northern China, we should pay attention to the improvement and optimization of regional energy structure and energy efficiency.

Analysis of Lighting Changes in the Tourist City Edogawa Using Nighttime Light Data

When assessing remote sensing data, nighttime light data have shortcomings that can be attributed to sensor limitations and the influence of the natural environment. Signal leakage errors in nighttime light data were identified in this study. A regression model was created to reduce signal leakage error by selecting sampling points in coastal area. Lighting variations in Edogawa between 2008 and 2013 were compared based on the Defense Meteorological Satellite Program’s nighttime light data. The lighting variation characteristics in Edogawa from 1992 to 2012 at 5-year intervals were also analyzed. The results show that the 2002 FIFA World Cup held in Japan led Edogawa’s light digital number values to peak in 2002. The annual Edogawa lighting changes from 2007 to 2013 were also explored. The 2008 global financial crisis led to the lowest compounded night light index and average digital number in Edogawa during these 7 years.