Nighttime Light Images Research Articles

Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data

The nighttime light data records artificial light on the Earth’s surface and can be used to estimate the spatial distribution of the gross domestic product (GDP) and the electric power consumption (EPC). In early 2013, the first global NPP-VIIRS nighttime light data were released by the Earth Observation Group of National Oceanic and Atmospheric Administration’s National Geophysical Data Center (NOAA/NGDC). As new-generation data, NPP-VIIRS data have a higher spatial resolution and a wider radiometric detection range than the traditional DMSP-OLS nighttime light data. This study aims to investigate the potential of NPP-VIIRS data in modeling GDP and EPC at multiple scales through a case study of China. A series of preprocessing procedures are proposed to reduce the background noise of original data and to generate corrected NPP-VIIRS nighttime light images. Subsequently, linear regression is used to fit the correlation between the total nighttime light (TNL) (which is extracted from corrected NPP-VIIRS data and DMSP-OLS data) and the GDP and EPC (which is from the country’s statistical data) at provincial- and prefectural-level divisions of mainland China. The result of the linear regression shows that R2 values of TNL from NPP-VIIRS with GDP and EPC at multiple scales are all higher than those from DMSP-OLS data. This study reveals that the NPP-VIIRS data can be a powerful tool for modeling socioeconomic indicators; such as GDP and EPC.

Brightness of Nighttime Lights as a Proxy for Freight Traffic: A Case Study of China

Since economic reforms in 1978, China's huge growth has led to a rapid increase in demand for freight traffic. Timely assessments of past and current amounts of freight traffic are basis for predicting future demands of freight traffic and appropriately allocating transportation resources. Sum lights (summed digital number (DN) value of pixels of nighttime light imagery) for years 2000, 2004, and 2008 respectively are extracted from corresponding Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) stable lights annual image composites. The sum lights are then regressed on total freight traffic (TFT), railway freight traffic (RFT), and highway freight traffic (HFT), respectively, at the province level. Results show that sum light strongly correlates to TFT and HFT, so sum light can be used as a proxy for TFT and HFT at the province level. However, due to lack of strong correlations between RFT and GDP, sum light is not appropriate to be as a proxy of RFT. Finally we disaggregate each province/municipality's HFT to each pixel in proportion to the DN value of the pixel of the nighttime light image to produce a Chinese HFT map of 2008 with 1 km × 1 km resolution. Compared to traditional census-based freight traffic data, the freight traffic data derived from the nighttime light imagery contain more spatial information.

Estimation of in-use steel stock for civil engineering and building using nighttime light images

To establish a sustainable society, it is necessary to understand the flows and stocks of materials. However, traditional material flow analysis requires large quantities of data relating to the consumption and trade of materials in the past and the lifetime distributions of end use. To overcome the problem that such data may not be available, we have proposed using nighttime light images to estimate the in-use stocks of materials in countries for which the data are unavailable. In the previous study, in-use steel stock for civil engineering and building in 2006 was estimated using nighttime light images. However, several aspects of the methodology must be improved, and time-series analyses using nighttime light images have not yet been performed. Therefore, in this study, we improved the estimation of in-use steel stock by using new geological information (i.e., LandScan population distribution data) and correcting the pixel area. We prepared radiance-calibrated nighttime light data for 2006 and 2010 and conducted time-series analyses of the in-use steel stock using the nighttime light data. The in-use steel stock for civil engineering and building in 2010 was found to amount to approximately 11.3Gt, which was approximately 21% higher than that in 2006.

Satellite-Observed Nighttime Light Variation as Evidence for Global Armed Conflicts

The objective of this research is to investigate the potential of nighttime light images, acquired with Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS), in evaluating global armed conflicts. To achieve this purpose, we assessed the relationship between armed conflicts and the satellite-observed nighttime light variation over 159 countries through annual composites of the nighttime light images. Firstly, a light ratio index was developed to reduce the data inconsistency of annual nighttime light images during 1992-2010. Then 12 countries were selected as examples for a primary investigation, and we found the outbreak of a war can reduce the light and the ceasefire can increase the light from the remote sensing images, which indicates armed conflict events always have significant impact on the nighttime light. Based on this assertion, a nighttime light variation index (NLVI) was developed to quantify the variation of the time series nighttime light. Then using conditional probability analysis, the probability of a country suffering from armed conflicts increases with increase of NLVI. Particularly, when the NLVI value is in a very high level as defined, 80% of the countries have experienced armed conflicts. Furthermore, using correlation analysis, the number of global armed conflicts is highly correlated with the global NLVI in temporal dimension, with a correlation coefficient larger than 0.77. In summary, the potential of nighttime light images in armed conflict evaluation is extended from a regional scale to a global scale by this study.

Dynamics and Spatial Distribution of Global Nighttime Lights

We analyze the dynamics, and the spatial distribution of nighttime light using the open source data of the Defense Meteorological Satellite Program of the U.S. Air Force. A detailed analysis of the relevant literature and our study of the database allow us to set up a best-practice for the use of nighttime light images in different research projects. Over the past 17 years, we document a gradual shift of the light world center moving eastwards over a distance of roughly 1000 km, at a pace of about 60 km per year. We introduce the new concept of spatial light Gini coefficients. When removing unlit land from the calculations, we find that the Lorenz curves and the Gini coefficients converge for all the countries in our analysis, suggesting a universal pattern across different countries of human settlements. We also document a gradual increase of the spatial light Gini coefficient over most countries over the past 17 years, indicative of a centralization of light. This is explained by a larger growth of dimly lit surface (49%) compared with bright areas (19%) between 1992 and 2009. Finally, a detailed analysis of bright light (city) growth covering 160 different countries shows that nighttime light images provide the perfect tool to monitor the expansion of developing countries (like India and Brazil), the growth of new agglomeration sizes (like Shanghai in China or the Nile delta in Egypt), the regression in countries suffering from demographic decline and a reduction in urban population (like Russia and the Ukraine) and the success of light pollution abatement programs in western countries like Canada and the United Kingdom.

Automatic intercalibration of night-time light imagery using robust regression

In remote-sensing community, radiometric calibration of night-time light images has long been a problem, hindering change detection of images in different dates. Currently, an intercalibration model is regarded as the unique solution for the problem, but prior knowledge is needed to extract reference pixels with stable lights, which are hard to obtain in most of the applications. This study proposed an automatic algorithm to extract the reference pixels for convenient use of the intercalibration model, with an assumption that there are sufficient pixels with stable night-time lights in the multi-temporal images. To automatically extract the stable pixels from images in two dates, all pixels in the two dates were entered into a linear regression model, and the outliers viewed as suspected changed pixels were discarded iteratively. Consequently, some stable pixels were extracted and the intercalibration model was implemented. Annual night-time light composites in Beijing, China, from 1992 to 2010 were taken as the study material, and the results show that the multi-temporal calibrated night-time light data have higher correlation with gross domestic production (GDP) (R 2 = 0.8734) and urban population (UP) (R 2 = 0.9269) than those of the uncalibrated images (with the R 2 values 0.7963 and 0.8575, respectively). Furthermore, the data inconsistency from different night-time light satellites in the same year was reduced with the proposed algorithm. The results demonstrate that the proposed algorithm is effective in intercalibrating the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) images automatically.

High spatial resolution night-time light images for demographic and socio-economic studies

Satellite derived night-time lights have been used to study global economic and demographic differences between countries. The majority of studies to date have used the coarse spatial resolution datasets of the Defense Meteorological Satellite Program (DMSP). In this study, we hypothesize that night-time lights can serve as an indicator for demographic and socio-economic properties of built-up areas at a local scale. We used night-time light images acquired by the American DMSP (2003, 2.7km), Argentinean SAC-C (2007, 300m) and photographs taken by astronauts from the International Space Station (ISS; 2003, 60m). We compared the night-time lights of built-up areas based on their geographical location (Israel and the West Bank) and their population (Jewish and Arab). Israeli localities were better lit than West Bank localities, corresponding to the difference in the gross domestic product of the two entities. No difference was found in the night-time lights brightness of Jewish and Arab localities within Israel. However, night-time lights of built-up areas with a Jewish population within Israel and the West Bank were positively correlated with population density and roads density. In contrast, built-up areas with an Arab population had weaker correlations. Differences in the urban structure of Jewish and Arab built-up areas, as well as economic and geopolitical differences between Israel and the West Bank led to the observed differences in night-time lights patterns. Demographic and infrastructure data were able to explain 60% of the spatial variation of the ISS night-time lights, compared with only 28% of the spatial variation of the DMSP night-time lights dataset. The results of this study demonstrate potential uses of night-time lights databases of high spatial resolution, and emphasize the need for a dedicated night-time lights observing satellite.

夜間光衛星画像とGISを用いた建築用鋼材蓄積量の推計

夜間光衛星画像とGISを用いた建築用鋼材蓄積量の推計

Estimating in-use steel stock of civil engineering and building in China by nighttime light image

China is dramatically changing due to rapid development in recent years. This can be observed from the change in landscapes, which most resulted from new or replaced constructions. The floor area of residential and commercial construction had increased fourfold from 1990 to 2005, and its speed does not show any sign of slowing down. The construction will also drive the demand of steel, which comprises half of the total national consumption. However, there were not many studies aiming to quantify the construction steel stock in China, which was mainly due to lack of statistical data. In order to overcome this obstacle, we proposed a methodology to estimate sub-national steel stock using nighttime light image. As a result, we found out that the Beijing municipality possesses the most construction steel stock. Most construction steel stock exists on the eastern coast, and is most concentrated in the Beijing municipality, the Tianjin municipality, the Shanghai municipality, and the Guangdong province.

Creating a Global Grid of Distributed Fossil Fuel CO2 Emissions from Nighttime Satellite Imagery

The potential use of satellite observed nighttime lights for estimating carbon-dioxide (CO2) emissions has been demonstrated in several previous studies. However, the procedures for a moderate resolution (1 km2 grid cells) global map of fossil fuel CO2 emissions based on nighttime lights are still in the developmental phase. We report on the development of a method for mapping distributed fossil fuel CO2 emissions (excluding electric power utilities) at 30 arc-seconds or approximately 1 km2 resolution using nighttime lights data collected by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS). A regression model, Model 1, was initially developed based on carbon emissions from five sectors of the Vulcan data produced by the Purdue University and a nighttime satellite image of the U.S. The coefficient derived through Model 1 was applied to the global nighttime image but it resulted in underestimation of CO2 emissions for most of the world’s countries, and the states of the U.S. Thus, a second model, Model 2 was developed by allocating the distributed CO2 emissions (excluding emissions from utilities) using a combination of DMSP-OLS nighttime image and population count data from the U.S. Department of Energy's (DOE) LandScan grid. The CO2 emissions were distributed in proportion to the brightness of the DMSP nighttime lights in areas where lighting was detected. In areas with no DMSP detected lighting, the CO2 emissions were distributed based on population count, with the assumption that people who live in these areas emit half as much CO2 as people who live in the areas with DMSP detected lighting. The results indicate that the relationship between satellite observed nighttime lights and CO2 emissions is complex, with differences between sectors and variations in lighting practices between countries. As a result it is not possible to make independent estimates of CO2 emissions with currently available coarse resolution panchromatic satellite observed nighttime lights. However, the nighttime lights image in conjunction with the population grid can help in more accurate disaggregation of national CO2 emissions to a moderate resolution spatial grid.

In-Use Stock of Copper Analysis Using Satellite Nighttime Light Observation Data

We have developed a novel methodology for analyzing the worldwide copper stock-in-use by using nighttime light images. Radiance calibrated nighttime light imaged data (RCD) for the entire world has been assembled from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) by the National Geophysical Data Center. It has been recognized that the intensity of nighttime light is strongly associated with such aspects of human settlement as population density and energy consumption. We assumed that the presence of light implies the use of electrical conducting material, namely copper. The stock-in-use data for copper in Japan, North America, Australia and China were obtained from previous material flow analysis studies. We analyzed the relationship between light accumulation and the size of the copper stock in those countries. A significant correlation was found and the feasibility of this method was confirmed. We employed this method to analyze the stock-in-use in other Asian countries. The in-use stock of copper was correlated with the gross domestic product (GDP). [doi:10.2320/matertrans.M2009030]

衛星夜間光観測データを用いた銅のストック解析

We developed a novel methodology to analyze world-scale stock-in-use of copper by using a nighttime light image. Radiance calibrated nighttime light imaged data (RCD) of the world has been assembled from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) by the National Geophysical Data Center. It has been recognized that the intensities of nighttime light are strongly associated with human settlement, such as population density and energy consumption. We assumed that wherever the light exists the electrical conducting material, such as copper should be used. The stock-in-use data of copper such as in Japan, North America, Australia and China were obtained from existing studies on material flow analysis. We analyzed the relationship between the light accumulation density and the amount of stock of copper in those countries. A significant correlation was found and the feasibility of this method was confirmed. We applied this method to analyze stock-in-use in other Asian countries. The in-use stock of copper was correlated with gross domestic product (GDP).

Radiance Calibration of DMSP-OLS Low-Light Imaging Data of Human Settlements

Nocturnal lighting is a primary method for enabling human activity. Outdoor lighting is used extensively worldwide in residential, commercial, industrial, public facilities, and roadways. A radiance calibrated nighttime lights image of the United States has been assembled from Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS). The satellite observation of the location and intensity of nocturnal lighting provide a unique view of humanities presence and can be used as a spatial indicator for other variables that are more difficult to observe at a global scale. Examples include the modeling of population density and energy related greenhouse gas emissions.