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Special Issue "Remote Sensing with Nighttime Lights"

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A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (30 September 2014)

Special Issue Editor

Guest Editor
Dr. Christopher D. Elvidge (Website)

Earth Observation Group, NOAA National Geophysical Data Center, Boulder, CO 80305, USA
Interests: remote sensing of nighttime lights; gas flares and biomass burning

Special Issue Information

Dear Colleagues,

Nearly every person in the world has at one time or another appreciated the beauty of city lights at night. This may have been on the ground viewing a commercial center, from a tall building, a mountain, or from an aircraft. The points and splays of light surrounded by darkness attract our eyes. Indeed, nocturnal lighting is one of the hallmarks of human presence on the surface of the earth. Nocturnal lighting has emerged as one of the primary remote sensing observables linked to the presence of built infrastructure and human activity levels.

Today, we have a two decade record of global nighttime lights observed by DMSP (1992-2012). While the DMSP nighttime lights have recognized flaws, they have still been widely used to demonstrate the potential of nighttime lights as a spatial proxy for variables that would be difficult to map directly and globally using other means. The DMSP nighttime lights gave a glimpse of how this style of observation can be used as a scientific data product. A new series of nighttime products is beginning to emerge from the VIIRS instrument, which resolves many of the shortcoming of the DMSP. In the future, we expect that even better instruments will fly in space to collect higher spatial resolution multispectral (or even hyperspectral) nighttime lights.

This special issue of Remote Sensing is designed to explore nighttime lights and the scientific applications that have been developed for them. Prospective authors are invited to contribute to this Special Issue of Remote Sensing by submitting an original manuscript of their latest research results in the field of advances in remotely sensed nighttime lights. Review contributions are also welcomed.

Papers are solicited over the wide range of topics encompassed by the remote sensing of nighttime lights, including:

  • Sensor designs for observation of nighttime lights
  • Methods used for global mapping of nighttime lights
  • Use of nighttime lights as a spatial proxy for variables such economic activity, population, and CO2 emissions
  • Modeling the density of constructed surfaces and habitat fragmentation
  • Light pollution studies
  • Spectral analysis of nighttime lights
  • Nighttime lights change detection – analysis of urban growth patterns
  • Ecological impacts of nocturnal lighting
  • Fusion of nighttime lights with other remote sensing data
  • Morphological analysis of development
  • Intercomparison of DMSP and VIIRS low light imaging data

Dr. Christopher D. Elvidge
Guest Editor

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed Open Access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs).

Published Papers (23 papers)

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Open AccessArticle A Test of the New VIIRS Lights Data Set: Population and Economic Output in Africa
Remote Sens. 2015, 7(4), 4937-4947; doi:10.3390/rs70404937
Received: 30 September 2014 / Accepted: 8 April 2015 / Published: 22 April 2015
Cited by 3 | PDF Full-text (716 KB) | HTML Full-text | XML Full-text
Abstract
The present study analyses the new Visible Infrared Imaging Radiometer Suite (VIIRS) lights data to determine whether it can provide more accurate proxies for socioeconomic data in areas with poor quality data than proxies based on stable lights. Our analysis indicates that [...] Read more.
The present study analyses the new Visible Infrared Imaging Radiometer Suite (VIIRS) lights data to determine whether it can provide more accurate proxies for socioeconomic data in areas with poor quality data than proxies based on stable lights. Our analysis indicates that VIIRS lights are a promising supplementary source for standard measures on population and economic output at a small scale, especially for low population and economic density areas in Africa. The current analysis also suggests that in comparison to stable lights generated by the DMSP-OLS system, data generated by the VIIRS system provide more information to estimate population than output index. However, further analysis and formal statistical models are needed to evaluate the usefulness of VIIRS lights versus other lights products. With more advanced methods, there is also a potential to generate a synthetic index by combining different lights products to produce a better proxy measure for other indexes. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle Global Trends in Exposure to Light Pollution in Natural Terrestrial Ecosystems
Remote Sens. 2015, 7(3), 2715-2730; doi:10.3390/rs70302715
Received: 30 September 2014 / Revised: 19 February 2015 / Accepted: 3 March 2015 / Published: 9 March 2015
Cited by 5 | PDF Full-text (1196 KB) | HTML Full-text | XML Full-text
Abstract
The rapid growth in electric light usage across the globe has led to increasing presence of artificial light in natural and semi-natural ecosystems at night. This occurs both due to direct illumination and skyglow - scattered light in the atmosphere. There is [...] Read more.
The rapid growth in electric light usage across the globe has led to increasing presence of artificial light in natural and semi-natural ecosystems at night. This occurs both due to direct illumination and skyglow - scattered light in the atmosphere. There is increasing concern about the effects of artificial light on biological processes, biodiversity and the functioning of ecosystems. We combine intercalibrated Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) images of stable night-time lights for the period 1992 to 2012 with a remotely sensed landcover product (GLC2000) to assess recent changes in exposure to artificial light at night in 43 global ecosystem types. We find that Mediterranean-climate ecosystems have experienced the greatest increases in exposure, followed by temperate ecosystems. Boreal, Arctic and montane systems experienced the lowest increases. In tropical and subtropical regions, the greatest increases are in mangroves and subtropical needleleaf and mixed forests, and in arid regions increases are mainly in forest and agricultural areas. The global ecosystems experiencing the greatest increase in exposure to artificial light are already localized and fragmented, and often of particular conservation importance due to high levels of diversity, endemism and rarity. Night time remote sensing can play a key role in identifying the extent to which natural ecosystems are exposed to light pollution. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle DMSP-OLS Radiance Calibrated Nighttime Lights Time Series with Intercalibration
Remote Sens. 2015, 7(2), 1855-1876; doi:10.3390/rs70201855
Received: 1 October 2014 / Revised: 4 January 2015 / Accepted: 7 January 2015 / Published: 9 February 2015
Cited by 4 | PDF Full-text (19785 KB) | HTML Full-text | XML Full-text
Abstract
The Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) stable lights products are made using operational OLS data collected at high gain settings, resulting in sensor saturation on brightly lit areas, such as city centers. This has been a paramount shortcoming of the [...] Read more.
The Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) stable lights products are made using operational OLS data collected at high gain settings, resulting in sensor saturation on brightly lit areas, such as city centers. This has been a paramount shortcoming of the DMSP-OLS stable lights time series. This study outlines a methodology that greatly expands the dynamic range of the OLS data using observations made at different fixed-gain settings, and by incorporating the areas not affected by saturation from the stable lights product. The radiances for the fixed-gain data are computed based on each OLS sensor’s pre-flight calibration. The result is a product known as the OLS radiance calibrated nighttime lights. A total of eight global datasets have been produced, representing years from 1996 to 2010. To further facilitate the usefulness of these data for time-series analyses, corrections have been made to counter the sensitivity differences of the sensors, and coefficients are provided to adjust the datasets to allow inter-comparison. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle Integrating Multiple Source Data to Enhance Variation and Weaken the Blooming Effect of DMSP-OLS Light
Remote Sens. 2015, 7(2), 1422-1440; doi:10.3390/rs70201422
Received: 25 October 2014 / Accepted: 22 January 2015 / Published: 29 January 2015
Cited by 2 | PDF Full-text (42643 KB) | HTML Full-text | XML Full-text
Abstract
Defense Meteorological Satellite Program/Operational Linescan System (DMSP-OLS) nighttime light has proved to be an effective tool to monitor human activities, especially in mapping urban areas. However, the inherent defects of DMSP-OLS light including saturation and blooming effects remain to be tackled. In [...] Read more.
Defense Meteorological Satellite Program/Operational Linescan System (DMSP-OLS) nighttime light has proved to be an effective tool to monitor human activities, especially in mapping urban areas. However, the inherent defects of DMSP-OLS light including saturation and blooming effects remain to be tackled. In this study, the Normalized Difference Vegetation Index (NDVI) product of the Moderate-resolution Imaging Spectroradiometer/Normalized Difference Vegetation Index 1-Month (MODND1M), the temperature product of Moderate-resolution Imaging Spectroradiometer/Land Surface Temperature 1-Month (MODLT1M) and DMSP-OLS light were integrated to establish the Vegetation Temperature Light Index (VTLI), aiming at weakening the saturation and blooming effects of DMSP-OLS light. In comparison with DMSP-OLS nighttime light, this new methodology achieved the following improvements: (1) the high value (30%–100%) range of VTLI was concentrated in the urban areas; (2) VTLI could effectively enhance the variation of DMSP-OLS light, especially in the urban center; and (3) VTLI reached convergence faster than Vegetation Adjusted Normalized Urban Index (VANUI). Results showed that the urban areas extracted by VTLI were closer to those from Landsat TM images with the accuracy of kappa coefficients in Beijing (0.410), Shanghai (0.718), Lanzhou (0.483), and Shenyang (0.623), respectively. Thus, it can be concluded that the proposed index is able to serve as a favorable option for urban areas mapping. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle Nighttime Light Derived Assessment of Regional Inequality of Socioeconomic Development in China
Remote Sens. 2015, 7(2), 1242-1262; doi:10.3390/rs70201242
Received: 24 June 2014 / Accepted: 15 January 2015 / Published: 23 January 2015
Cited by 2 | PDF Full-text (18377 KB) | HTML Full-text | XML Full-text
Abstract
Satellite-derived nighttime light (NTL) data have been extensively used as an efficient proxy measure for monitoring urbanization dynamics and socioeconomic activity. This is because remotely sensed NTL signals can be quantitatively connected to demographic and socioeconomic variables at regional and global scales. [...] Read more.
Satellite-derived nighttime light (NTL) data have been extensively used as an efficient proxy measure for monitoring urbanization dynamics and socioeconomic activity. This is because remotely sensed NTL signals can be quantitatively connected to demographic and socioeconomic variables at regional and global scales. The recently composited cloud-free NTL imagery derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite provides spatially detailed observations of human settlements. We quantitatively estimated socioeconomic development inequalities across 30 provinces and municipalities in mainland China using VIIRS NTL data associated with both regional gross domestic product (GDP) and population census data. We quantitatively investigated relations between NTL, GDP, and population using a linear regression model. Our results suggest that NTL radiances have significant positive correlations with GDP and population at different levels. Several inequality coefficients, commonly used in economics, were derived from VIIRS NTL data and statistical data at multiple spatial scales. Compared with the statistical data, NTL-derived inequality coefficients enabled us to elicit more detailed information on differences in regional development at multiple levels. Our study of provinces and municipalities revealed that county-level inequality was more significant than city-level inequality. The results of population-weighted NTL inequality indicate an obvious regional disparity with NTL distribution being more unequal in China’s undeveloped western regions compared with more developed eastern regions. Our findings suggest that given the timely and spatially explicit advantages of VIIRS, NTL data are capable of providing comprehensive information regarding inequality at multiple levels, which is not possible through the use of traditional statistical sources. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
Open AccessArticle Utilization of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band for Arctic Ship Tracking and Fisheries Management
Remote Sens. 2015, 7(1), 971-989; doi:10.3390/rs70100971
Received: 10 June 2014 / Accepted: 25 December 2014 / Published: 16 January 2015
Cited by 3 | PDF Full-text (8253 KB) | HTML Full-text | XML Full-text
Abstract
Maritime ships operating on-board illumination at night appear as point sources of light to highly sensitive low-light imagers on-board environmental satellites. Unlike city lights or lights from offshore gas platforms, whose locations remain stationary from one night to the next, lights from [...] Read more.
Maritime ships operating on-board illumination at night appear as point sources of light to highly sensitive low-light imagers on-board environmental satellites. Unlike city lights or lights from offshore gas platforms, whose locations remain stationary from one night to the next, lights from ships typically are ephemeral. Fishing boat lights are most prevalent near coastal cities and along the thermal gradients in the open ocean. Maritime commercial ships also operate lights that can be detected from space. Such observations have been made in a limited way via U.S. Department of Defense satellites since the late 1960s. However, the Suomi National Polar-orbiting Partnership (S-NPP) satellite, which carries a new Day/Night Band (DNB) radiometer, offers a vastly improved ability for users to observe commercial shipping in remote areas such as the Arctic. Owing to S-NPP’s polar orbit and the DNB’s wide swath (~3040 km), the same location in Polar Regions can be observed for several successive passes via overlapping swaths—offering a limited ability to track ship motion. Here, we demonstrate the DNB’s improved ability to monitor ships from space. Imagery from the DNB is compared with the heritage low-light sensor, the Operational Linescan System (OLS) on board the Defense Meteorological Support Program (DMSP) satellites, and is evaluated in the context of tracking individual ships in the Polar Regions under both moonlit and moonless conditions. In a statistical sense, we show how DNB observations of ship lights in the East China Sea can be correlated with seasonal fishing activity, while also revealing compelling structures related to regional fishery agreements established between various nations. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle Estimating Land Development Time Lags in China Using DMSP/OLS Nighttime Light Image
Remote Sens. 2015, 7(1), 882-904; doi:10.3390/rs70100882
Received: 30 June 2014 / Accepted: 6 January 2015 / Published: 14 January 2015
Cited by 1 | PDF Full-text (7841 KB) | HTML Full-text | XML Full-text
Abstract
The Chinese real estate industry has experienced rapid growth since China’s economic reform. Along with a booming industry, a third of purchased lands were left undeveloped in the last decade. Knowledge of real estate development time lags between land being purchased and [...] Read more.
The Chinese real estate industry has experienced rapid growth since China’s economic reform. Along with a booming industry, a third of purchased lands were left undeveloped in the last decade. Knowledge of real estate development time lags between land being purchased and property being occupied can enable policymakers to produce more effective policies and regulations to guide the real estate industry and sustain economic development and social welfare. This paper presents an innovative method to estimate provincial land development time lags in China using DMSP/OLS NTL imagery and real estate statistical data. The results showed that real estate development time lag was common in China during 2000–2010. More than half of the study sites showed development time lags of three years or longer. An Increment of Developed Pixels (IDP) index was established to outline yearly land development completions in China between 2000 and 2010. A Comprehensive Real Estate Price Index (CREPI) was created to explore the causes of the time lags. A strong and positive correlation was found between the real estate development time lags and CREPI values (with r = 0.619, n = 31, p < 0.0005). The results indicated that the land development time lag during the study period was positively correlated to the activity of the local real estate market, the price trend of land and housing properties, and the local economic situation. The results also proved that with the support of statistical data the DMSP/OLS NTL image could offer an economically efficient and reliable solution to estimate the time lag of real estate development. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle High-Resolution Imagery of Earth at Night: New Sources, Opportunities and Challenges
Remote Sens. 2015, 7(1), 1-23; doi:10.3390/rs70100001
Received: 12 September 2014 / Accepted: 15 December 2014 / Published: 23 December 2014
Cited by 9 | PDF Full-text (10987 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Images of the Earth at night are an exceptional source of human geographical data, because artificial light highlights human activity in a way that daytime scenes do not. The quality of such imagery dramatically improved in 2012 with two new spaceborne detectors. [...] Read more.
Images of the Earth at night are an exceptional source of human geographical data, because artificial light highlights human activity in a way that daytime scenes do not. The quality of such imagery dramatically improved in 2012 with two new spaceborne detectors. The higher resolution and precision of the data considerably expands the scope of possible applications. In this paper, we introduce the two new data sources and discuss their potential limitations using three case studies. Data from the Visible Infrared Imaging Radiometer Suite Day-Night Band (VIIRS DNB) is shown to have sufficient resolution to identify major sources of waste light, such as airports, and we find considerable variation in the peak radiance of the world’s largest airports. Nighttime imagery brings “cultural footprints” to light: DNB data reveals that American cities emit many times more light per capita than German cities and that cities in the former East of Germany emit more light per capita than those in the former West. Photographs from the International Space Station, the second new source of imagery, provide some limited spectral information, as well as street-level resolution. These images may be of greater use for epidemiological studies than the lower resolution DNB data. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle Aladdin’s Magic Lamp: Active Target Calibration of the DMSP OLS
Remote Sens. 2014, 6(12), 12708-12722; doi:10.3390/rs61212708
Received: 9 September 2014 / Revised: 24 November 2014 / Accepted: 24 November 2014 / Published: 17 December 2014
PDF Full-text (2153 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Nighttime satellite imagery from the Defense Meteorological Satellite Programs’ Operational Linescan System (DMSP OLS) is being used for myriad applications including population mapping, characterizing economic activity, disaggregate estimation of CO2 emissions, wildfire monitoring, and more. Here we present a method for [...] Read more.
Nighttime satellite imagery from the Defense Meteorological Satellite Programs’ Operational Linescan System (DMSP OLS) is being used for myriad applications including population mapping, characterizing economic activity, disaggregate estimation of CO2 emissions, wildfire monitoring, and more. Here we present a method for in situ radiance calibration of the DMSP OLS using a ground based light source as an active target. We found that the wattage of light used by our active target strongly correlates with the signal measured by the DMSP OLS. This approach can be used to enhance our ability to make intertemporal and intersatellite comparisons of DMSP OLS imagery. We recommend exploring the possibility of establishing a permanent active target for the calibration of nocturnal imaging systems. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
Open AccessArticle The S-NPP VIIRS Day-Night Band On-Orbit Calibration/Characterization and Current State of SDR Products
Remote Sens. 2014, 6(12), 12427-12446; doi:10.3390/rs61212427
Received: 1 October 2014 / Revised: 4 December 2014 / Accepted: 5 December 2014 / Published: 10 December 2014
Cited by 7 | PDF Full-text (3892 KB) | HTML Full-text | XML Full-text
Abstract
The launch of VIIRS on-board the Suomi-National Polar-orbiting Partnership (S-NPP) on 28 October 2011, marked the beginning of the next chapter on nighttime lights observation started by the Defense Meteorological Satellite Program’s (DMSP) OLS sensor more than two decades ago. The VIIRS [...] Read more.
The launch of VIIRS on-board the Suomi-National Polar-orbiting Partnership (S-NPP) on 28 October 2011, marked the beginning of the next chapter on nighttime lights observation started by the Defense Meteorological Satellite Program’s (DMSP) OLS sensor more than two decades ago. The VIIRS observes the nighttime lights on Earth through its day-night band (DNB), a panchromatic channel covering the wavelengths from 500 nm to 900 nm. Compared to its predecessors, the VIIRS DNB has a much improved spatial/temporal resolution, radiometric sensitivity and, more importantly, continuous calibration using on-board calibrators (OBCs). In this paper, we describe the current state of the NASA calibration and characterization methodology used in supporting mission data quality assurance and producing consistent mission-wide sensor data records (SDRs) through NASA’s Land Product Evaluation and Analysis Tool Element (Land PEATE). The NASA calibration method utilizes the OBCs to determine gains, offset drift and sign-to-noise ratio (SNR) over the entire mission. In gain determination, the time-dependent relative spectral response (RSR) is used to correct the optical throughput change over time. A deep space view acquired during an S-NPP pitch maneuver is used to compute the airglow free dark offset for DNB’s high gain stage. The DNB stray light is estimated each month from new-moon dark Earth surface observations to remove the excessive stray light over the day-night terminators. As the VIIRS DNB on-orbit calibration is the first of its kind, the evolution of the calibration methodology is evident when the S-NPP VIIRS’s official calibrations are compared with our latest mission-wide reprocessing. In the future, the DNB calibration methodology is likely to continue evolving, and the mission-wide reprocessing is a key to providing consistently calibrated DNB SDRs for the user community. In the meantime, the NASA Land PEATE provides an alternative source to obtain mission-wide DNB SDR products that are calibrated based on the latest NASA DNB calibration methodology. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle Quantitative Analysis of VIIRS DNB Nightlight Point Source for Light Power Estimation and Stability Monitoring
Remote Sens. 2014, 6(12), 11915-11935; doi:10.3390/rs61211915
Received: 10 September 2014 / Revised: 18 November 2014 / Accepted: 18 November 2014 / Published: 1 December 2014
Cited by 10 | PDF Full-text (1977 KB) | HTML Full-text | XML Full-text
Abstract
The high sensitivity and advanced onboard calibration on the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) enables accurate measurements of low light radiances which leads to enhanced quantitative applications at night. The finer spatial resolution of DNB also allows users [...] Read more.
The high sensitivity and advanced onboard calibration on the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) enables accurate measurements of low light radiances which leads to enhanced quantitative applications at night. The finer spatial resolution of DNB also allows users to examine social economic activities at urban scales. Given the growing interest in the use of the DNB data, there is a pressing need for better understanding of the calibration stability and absolute accuracy of the DNB at low radiances. The low light calibration accuracy was previously estimated at a moderate 15% using extended sources while the long-term stability has yet to be characterized. There are also several science related questions to be answered, for example, how the Earth’s atmosphere and surface variability contribute to the stability of the DNB measured radiances; how to separate them from instrument calibration stability; whether or not SI (International System of Units) traceable active light sources can be designed and installed at selected sites to monitor the calibration stability, radiometric and geolocation accuracy, and point spread functions of the DNB; furthermore, whether or not such active light sources can be used for detecting environmental changes, such as aerosols. This paper explores the quantitative analysis of nightlight point sources, such as those from fishing vessels, bridges, and cities, using fundamental radiometry and radiative transfer, which would be useful for a number of applications including search and rescue in severe weather events, as well as calibration/validation of the DNB. Time series of the bridge light data are used to assess the stability of the light measurements and the calibration of VIIRS DNB. It was found that the light radiant power computed from the VIIRS DNB data matched relatively well with independent assessments based on the in situ light installations, although estimates have to be made due to limited ground truth data and lack of suitable radiative transfer models. Results from time series analysis are encouraging in potentially being able to detect anomalies in the DNB calibration. The study also suggests that accurate ground based active lights, when properly designed and installed, can be used to monitor the stability of the VIIRS DNB calibration at near the specified minimum radiances (3 nW∙cm−2∙sr−1), and potentially can be used to monitor the environmental changes as well. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle Evaluating Saturation Correction Methods for DMSP/OLS Nighttime Light Data: A Case Study from China’s Cities
Remote Sens. 2014, 6(10), 9853-9872; doi:10.3390/rs6109853
Received: 30 June 2014 / Revised: 26 September 2014 / Accepted: 1 October 2014 / Published: 16 October 2014
Cited by 5 | PDF Full-text (3971 KB) | HTML Full-text | XML Full-text
Abstract
Remotely sensed nighttime lights (NTL) datasets derived from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) have been identified as a good indicator of the urbanization process and have been widely used to study such demographic and economic variables as population [...] Read more.
Remotely sensed nighttime lights (NTL) datasets derived from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) have been identified as a good indicator of the urbanization process and have been widely used to study such demographic and economic variables as population distribution and density, electricity consumption, and carbon emission. However, one issue must be considered in the application of NTL data, i.e., saturation in the bright cores of urban centers. In this study, we evaluate four correction methods in China’s cities: the linear regression model and the cubic regression model at the regional level, and the Human Settlement Index (HSI) and the Vegetation Adjusted NTL Urban Index (VANUI) at a pixel level. The results suggest that both correction methods at the regional level improve the correlation between NTL data and socioeconomic variables. However, since the methods can only be used on saturated pixels, the correction effects are limited, as the saturated area in Chinese cities is rather small. HSI and VANUI increase the inter-urban variability within certain cities, especially when their vegetation health and abundance is negatively correlated with NTL. However, the indices may induce bias when applied in a large region with a diverse natural environment and vegetation, and the application of HSI with a relatively high sensitivity of HSI to NDVI may be limited as NTL approaches maximum. Proper methods for reducing saturation effects should thus vary with different study areas and research purposes. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle Tracking Electrification in Vietnam Using Nighttime Lights
Remote Sens. 2014, 6(10), 9511-9529; doi:10.3390/rs6109511
Received: 30 June 2014 / Revised: 17 September 2014 / Accepted: 24 September 2014 / Published: 9 October 2014
PDF Full-text (1666 KB) | HTML Full-text | XML Full-text
Abstract
We report on a systematic ground-based validation of DMSP-OLS night lights imagery to detect rural electrification in Vietnam. Based on an original survey of village-level units in Vietnam, this study compares nighttime light output from the U.S. Air Force Defense Meteorological Satellite [...] Read more.
We report on a systematic ground-based validation of DMSP-OLS night lights imagery to detect rural electrification in Vietnam. Based on an original survey of village-level units in Vietnam, this study compares nighttime light output from the U.S. Air Force Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) against ground-based survey data on electrical infrastructure and electricity use in 200 electrified villages. Monthly and annual composites record a one-point increase in brightness along DMSP-OLS’s 63-point brightness scale for every 60–70 additional streetlights or 240–270 electrified homes. Using a time series of 90 nightly images, the data show a one-point increase in brightness for every 125–200 additional streetlights, or 550–700 additional electrified homes. The results highlight the potential to use night lights imagery to support efforts to connect the 1.2 billion people who lack electricity around the world. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle The Integrated Use of DMSP-OLS Nighttime Light and MODIS Data for Monitoring Large-Scale Impervious Surface Dynamics: A Case Study in the Yangtze River Delta
Remote Sens. 2014, 6(10), 9359-9378; doi:10.3390/rs6109359
Received: 9 June 2014 / Revised: 16 August 2014 / Accepted: 17 September 2014 / Published: 29 September 2014
Cited by 12 | PDF Full-text (2901 KB) | HTML Full-text | XML Full-text
Abstract
The timely and reliable estimation of imperviousness is essential for the scientific understanding of human-Earth interactions. Due to the unique capacity of capturing artificial light luminosity and long-term data records, the Defense Meteorological Satellite Program (DMSP)’s Operational Line-scan System (OLS) nighttime light [...] Read more.
The timely and reliable estimation of imperviousness is essential for the scientific understanding of human-Earth interactions. Due to the unique capacity of capturing artificial light luminosity and long-term data records, the Defense Meteorological Satellite Program (DMSP)’s Operational Line-scan System (OLS) nighttime light (NTL) imagery offers an appealing opportunity for continuously characterizing impervious surface area (ISA) at regional and continental scales. Although different levels of success have been achieved, critical challenges still remain in the literature. ISA results generated by DMSP-OLS NTL alone suffer from limitations due to systemic defects of the sensor. Moreover, the majority of developed methodologies seldom consider spatial heterogeneity, which is a key issue in coarse imagery applications. In this study, we proposed a novel method for multi-temporal ISA estimation. This method is based on a linear regression model developed between the sub-pixel ISA fraction and a multi-source index with the integrated use of DMSP-OLS NTL and MODIS NDVI. In contrast with traditional regression analysis, we incorporated spatial information to the regression model for obtaining spatially adaptive coefficients at the per-pixel level. To produce multi-temporal ISA maps using a mono-temporal reference dataset, temporally stable samples were extracted for model training and validation. We tested the proposed method in the Yangtze River Delta and generated annual ISA fraction maps for the decade 2000–2009. According to our assessments, the proposed method exhibited substantial improvements compared with the standard linear regression model and provided a feasible way to monitor large-scale impervious surface dynamics. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle Comparative Estimation of Urban Development in China’s Cities Using Socioeconomic and DMSP/OLS Night Light Data
Remote Sens. 2014, 6(8), 7840-7856; doi:10.3390/rs6087840
Received: 24 June 2014 / Revised: 29 July 2014 / Accepted: 12 August 2014 / Published: 22 August 2014
Cited by 7 | PDF Full-text (5321 KB) | HTML Full-text | XML Full-text
Abstract
China has been undergoing a remarkably rapid urbanization process in the last several decades. Urbanization is a complicated phenomenon involving imbalanced transformation processes, such as population migrations, economic advancements and human activity dynamics. It is important to evaluate the imbalances between transformation [...] Read more.
China has been undergoing a remarkably rapid urbanization process in the last several decades. Urbanization is a complicated phenomenon involving imbalanced transformation processes, such as population migrations, economic advancements and human activity dynamics. It is important to evaluate the imbalances between transformation processes to support policy making in the realms of environmental management and urban planning. The Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) nighttime lights time series imagery provides a consistent and timely measure to estimate socioeconomic dynamics and changes in human activity. In this study, we jointly compared the annual ranks of three variables: the population, the gross domestic product (GDP) and the sum of weighted DMSP/OLS nighttime lights to estimate spatial and temporal imbalances in the urbanization processes of 226 cities in China between 1994 and 2011. We used ternary plots and a Euclidean distance-based method to quantitatively estimate the spatial and temporal imbalances between cities and to classify diverse urban development patterns in China. Our results suggest that, from 1994 to 2011, the imbalances of urbanization processes observed in the eastern, western and middle cities decreased, respectively, by 35.26%, 29.04% and 25.84%; however, imbalances in the northeast increased by 33.29%. The average decrement in imbalances across all urbanization processes in the 226 cities was 17.58%. Cities in the eastern region displayed relatively strong attractions to population, more rapid economic development processes and lower imbalances between socioeconomic and anthropogenic dynamics than cities in other regions. Several types of urban development patterns can be identified by comparing the morphological characteristics of temporal ternary plots of the 226 cities in China. More than one third (35.40%) of the 226 cities presented balanced states during the period studied; however, the remainder showed alternative urban development patterns. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle Characterizing Spatio-Temporal Dynamics of Urbanization in China Using Time Series of DMSP/OLS Night Light Data
Remote Sens. 2014, 6(8), 7708-7731; doi:10.3390/rs6087708
Received: 24 June 2014 / Revised: 21 July 2014 / Accepted: 12 August 2014 / Published: 20 August 2014
Cited by 5 | PDF Full-text (10606 KB) | HTML Full-text | XML Full-text
Abstract
Stable nighttime light (NTL) data, derived from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS), are typically considered a proxy measure of the dynamics of human settlements and have been extensively used to quantitative estimates of demographic variables, economic activity, and [...] Read more.
Stable nighttime light (NTL) data, derived from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS), are typically considered a proxy measure of the dynamics of human settlements and have been extensively used to quantitative estimates of demographic variables, economic activity, and land-use change in previous studies at both regional and global scales. The utility of DMSP data for characterizing spatio-temporal trends in urban development at a local scale, however, has received less attention. In this study, we utilize a time series of DMSP data to examine the spatio-temporal characteristics of urban development in 285 Chinese cities from 1992 to 2009, at both the local and national levels. We compare linear models and piecewise linear models to identify the turning points of nighttime lights and calculate the trends in nighttime light growth at the pixel level. An unsupervised classification is applied to identify the patterns in the nighttime light time series quantitatively. Our results indicate that nighttime light brightness in most areas of China exhibit a positive, multi-stage process over the last two decades; however, the average trends in nighttime light growth differ significantly. Through the piecewise linear model, we identify the saturation of nighttime light brightness in the urban center and significant increases in suburban areas. The maps of turning points indicate the greater the distance to the city center or sub-center, the later the turning point occurs. Six patterns derived from the classification illustrate the various characteristics of the nighttime light time series from the local to the national level. The results portray spatially explicit patterns and conspicuous temporal trends of urbanization dynamics for individual Chinese cities from 1992 to 2009. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle Industrial Wastewater Discharge Retrieval Based on Stable Nighttime Light Imagery in China from 1992 to 2010
Remote Sens. 2014, 6(8), 7566-7579; doi:10.3390/rs6087566
Received: 14 May 2014 / Revised: 8 August 2014 / Accepted: 11 August 2014 / Published: 14 August 2014
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Abstract
Industrial wastewater (IW) discharge, which is a known point source of pollution, is a major water pollution source. Increasing IW discharge has imposed considerable pressure on regional or global water environments. It is important to estimate the IW distribution in grid units [...] Read more.
Industrial wastewater (IW) discharge, which is a known point source of pollution, is a major water pollution source. Increasing IW discharge has imposed considerable pressure on regional or global water environments. It is important to estimate the IW distribution in grid units to improve basin-scale hydrological processes and water quality modeling. For the first time, we use the nighttime light imagery produced by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) to estimate the spatial and temporal variations in the IW distribution from 1992 to 2010 in China. The digital number values per unit area (DNP) of each stable light image were calculated using nighttime light imagery and were regressed against the IW per unit area (IWP) to estimate the total industrial wastewater (TIW) for each province. The results indicated strong positive correlations between the DNP and the IWP for each province during different years. The fitted linear regression models were used to estimate IW discharge in China with reliable accuracy. The IW estimation using the satellite data was consistent with the statistical results. The results also revealed that the IW discharge coverage expanded, whereas the IW discharge intensity decreased from 1992 to 2010 in China. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle Estimation of Gross Domestic Product Using Multi-Sensor Remote Sensing Data: A Case Study in Zhejiang Province, East China
Remote Sens. 2014, 6(8), 7260-7275; doi:10.3390/rs6087260
Received: 30 June 2014 / Revised: 28 July 2014 / Accepted: 29 July 2014 / Published: 4 August 2014
Cited by 5 | PDF Full-text (7323 KB) | HTML Full-text | XML Full-text
Abstract
There exists a spatial mismatch between socioeconomic data, such as Gross Domestic Product (GDP), and physical and environmental datasets. This study provides a dasymetric approach for GDP estimation at a fine scale by combining the Defense Meteorological Satellite Program Operational Linescan System [...] Read more.
There exists a spatial mismatch between socioeconomic data, such as Gross Domestic Product (GDP), and physical and environmental datasets. This study provides a dasymetric approach for GDP estimation at a fine scale by combining the Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) nighttime imagery, enhanced vegetation index (EVI), and land cover data. Despite the advantages of DMSP/OLS nighttime imagery in estimating human activities, its drawbacks, including coarse resolution, overglow, and saturation effects, limit its application. Hence, high-resolution EVI data were integrated with DMSP/OLS in this study to create a Human Settlement Index (HSI) for estimating the GDP of secondary and tertiary industries. The GDP of the primary industry was then estimated on the basis of land cover data, and the area with the GDP of the primary industry was classified by a threshold technique (DN ≤ 8). The regression model for GDP distribution estimation was implemented in Zhejiang Province in southeast China, and a GDP density map was generated at a resolution of 250 m × 250 m. Compared with the outcome of taking DMSP/OLS as a unique parameter, estimation errors obviously decreased. This study offers a low-cost and accurate approach for rapidly estimating high-resolution GDP distribution to construct an important database for the government when formulating developmental strategies. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Open AccessArticle Monitoring Trends in Light Pollution in China Based on Nighttime Satellite Imagery
Remote Sens. 2014, 6(6), 5541-5558; doi:10.3390/rs6065541
Received: 4 March 2014 / Revised: 19 May 2014 / Accepted: 20 May 2014 / Published: 16 June 2014
Cited by 8 | PDF Full-text (5333 KB) | HTML Full-text | XML Full-text
Abstract
China is the largest developing country worldwide, with rapid economic growth and the highest population. Light pollution is an environmental factor that significantly influences the quality and health of wildlife, as well as the people of any country. The objective of this [...] Read more.
China is the largest developing country worldwide, with rapid economic growth and the highest population. Light pollution is an environmental factor that significantly influences the quality and health of wildlife, as well as the people of any country. The objective of this study is to model the light pollution spatial pattern, and monitor changes in trends of spatial distribution from 1992 to 2012 in China using nighttime light imagery from the Defense Meteorological Satellite Program Operational Linescan System. Based on the intercalibration of nighttime light imageries of the study area from 1992 to 2012, this study obtained the change trends map. This result shows an increase in light pollution of the study area; light pollution in the spatial scale increased from 2.08% in the period from 1992–1996 to 2000–2004, to 5.64% in the period from 2000–2004 to 2008–2012. However, light pollution change trends presented varying styles in different regions and times. In the 1990s, the increasing trend in light pollution regions mostly occurred in larger urban cities, which are mainly located in eastern and coastal areas, whereas the decreasing trend areas were chiefly industrial and mining cities rich in mineral resources, in addition to the central parts of large cities. Similarly, the increasing trend regions dominated urban cities of the study area, and the expanded direction changed from larger cities to small and middle-sized cities and towns in the 2000s. The percentages of regions where light pollution transformed to severe and slight were 5.64% and 0.39%, respectively. The results can inform and help identify how local economic and environmental decisions influence our global nighttime environment, and assist government agencies in creating environmental protection measures. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
Open AccessArticle Modeling In-Use Steel Stock in China’s Buildings and Civil Engineering Infrastructure Using Time-Series of DMSP/OLS Nighttime Lights
Remote Sens. 2014, 6(6), 4780-4800; doi:10.3390/rs6064780
Received: 19 March 2014 / Revised: 16 May 2014 / Accepted: 19 May 2014 / Published: 27 May 2014
Cited by 7 | PDF Full-text (1441 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
China’s rapid urbanization has led to increasing steel consumption for buildings and civil engineering infrastructure. The in-use steel stock in the same is considered to be closely related to social welfare and urban metabolism. Traditional approaches for determining the in-use steel stock [...] Read more.
China’s rapid urbanization has led to increasing steel consumption for buildings and civil engineering infrastructure. The in-use steel stock in the same is considered to be closely related to social welfare and urban metabolism. Traditional approaches for determining the in-use steel stock are labor-intensive and time-consuming processes and always hindered by the availability of statistical data. To address this issue, this study proposed the use of long-term nighttime lights as a proxy to effectively estimate in-use steel stock for buildings (IUSSB) and civil engineering infrastructure (IUSSCE) at the provincial level in China. Significant relationships between nighttime lights versus IUSSB and IUSSCE were observed for provincial variables in a single year, as well as for time series variables of a single province. However, these relationships were found to differ among provinces (referred to as “inter-individual differences”) and with time (referred to as “temporal differences”). Panel regression models were therefore proposed to estimate IUSSB and IUSSCE in consideration of the temporal and inter-individual differences based on a dataset covering 1992–2007. These models were validated using data for 2008, and the results showed good estimation for both IUSSB and IUSSCE. The proposed approach can be used to easily monitor the dynamic of IUSSB and IUSSCE in China. This should be critical in providing valuable information for policy making regarding regional development of buildings and infrastructure, sustainable urban resource management, and cross-boundary material recycling. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
Open AccessArticle 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
Remote Sens. 2014, 6(2), 1705-1724; doi:10.3390/rs6021705
Received: 9 December 2013 / Revised: 5 February 2014 / Accepted: 14 February 2014 / Published: 20 February 2014
Cited by 38 | PDF Full-text (986 KB) | HTML Full-text | XML Full-text
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)

Review

Jump to: Research, Other

Open AccessReview Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review
Remote Sens. 2014, 6(8), 6844-6866; doi:10.3390/rs6086844
Received: 14 June 2014 / Revised: 18 July 2014 / Accepted: 18 July 2014 / Published: 25 July 2014
Cited by 15 | PDF Full-text (1308 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Since the release of the digital archives of Defense Meteorological Satellite Program Operational Line Scanner (DMSP/OLS) nighttime light data in 1992, a variety of datasets based on this database have been produced and applied to monitor and analyze human activities and natural [...] Read more.
Since the release of the digital archives of Defense Meteorological Satellite Program Operational Line Scanner (DMSP/OLS) nighttime light data in 1992, a variety of datasets based on this database have been produced and applied to monitor and analyze human activities and natural phenomena. However, differences among these datasets and how they have been applied may potentially confuse researchers working with these data. In this paper, we review the ways in which data from DMSP/OLS nighttime light images have been applied over the past two decades, focusing on differences in data processing, research trends, and the methods used among the different application areas. Five main datasets extracted from this database have led to many studies in various research areas over the last 20 years, and each dataset has its own strengths and limitations. The number of publications based on this database and the diversity of authors and institutions involved have shown promising growth. In addition, researchers have accumulated vast experience retrieving data on the spatial and temporal dynamics of settlement, demographics, and socioeconomic parameters, which are “hotspot” applications in this field. Researchers continue to develop novel ways to extract more information from the DMSP/OLS database and apply the data to interdisciplinary research topics. We believe that DMSP/OLS nighttime light data will play an important role in monitoring and analyzing human activities and natural phenomena from space in the future, particularly over the long term. A transparent platform that encourages data sharing, communication, and discussion of extraction methods and synthesis activities will benefit researchers as well as public and political stakeholders. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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Other

Jump to: Research, Review

Open AccessLetter Dynamics of Urbanization Levels in China from 1992 to 2012: Perspective from DMSP/OLS Nighttime Light Data
Remote Sens. 2015, 7(2), 1721-1735; doi:10.3390/rs70201721
Received: 10 November 2014 / Revised: 22 December 2014 / Accepted: 27 January 2015 / Published: 5 February 2015
Cited by 5 | PDF Full-text (20265 KB) | HTML Full-text | XML Full-text
Abstract
The authenticity and reliability of urbanization levels measured by different indicators in China have not reached a consensus, which may impede our understanding of the process of urbanization and its impacts on the environment. The objective of this study was to describe [...] Read more.
The authenticity and reliability of urbanization levels measured by different indicators in China have not reached a consensus, which may impede our understanding of the process of urbanization and its impacts on the environment. The objective of this study was to describe a reliable method of estimating urbanization level based on the Operational Line-scan System (OLS) on the Defense Meteorological Satellite Program (DMSP) nighttime light data and to analyze the dynamics of urbanization levels in China from 1992 to 2012. We calculated the comprehensive urbanization level at the national, provincial, and county scales using a compounded night light index (CNLI) and compared the change rate of CNLI with those of the other two conventional urbanization level indicators, proportion of the nonagricultural population and proportion of built-up area. Our results showed that CNLI derived from the DMSP/OLS data set provided a relatively reliable and accurate measure of the comprehensive urbanization level in China. During the last two decades, China has experienced continued and rapid urbanization with large regional variations. The CNLI increased 3.12 times, from 1.72 × 10−3 to 7.09 × 10−3. The annual increases of CNLI in eastern provinces were much faster than those in western provinces. In addition, we found that the rates of change in these three indicators were consistent for most provinces with the exception of the four municipalities (Beijing, Tianjin, Shanghai, and Chongqing) and a few eastern coastal provinces (Jiangsu, Zhejiang, Fujian, and Guangdong). Because the imbalance among population growth, urban expansion and socioeconomic development may affect cities’ sustainable development, we should pay more attention to these regions with large disparities between different indicators. Full article
(This article belongs to the Special Issue Remote Sensing with Nighttime Lights)
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