Generating the Nighttime Light of the Human Settlements by Identifying Periodic Components from DMSP/OLS Satellite Imagery

2015 ◽  
Vol 49 (17) ◽  
pp. 10503-10509 ◽  
Author(s):  
Husi Letu ◽  
Masanao Hara ◽  
Gegen Tana ◽  
Yuhai Bao ◽  
Fumihiko Nishio
Keyword(s):  
Satellite Imagery ◽  
Human Settlements ◽  
Nighttime Light ◽  
Periodic Components

scholarly journals Multi-Level Relationships between Satellite-Derived Nighttime Lighting Signals and Social Media–Derived Human Population Dynamics

2018 ◽  
Vol 10 (7) ◽  
pp. 1128 ◽  
Author(s):  
Ting Ma
Keyword(s):  
Social Media ◽  
Population Dynamics ◽  
Big Data ◽  
Human Activities ◽  
Human Population ◽  
City Size ◽  
Human Settlements ◽  
Good Opportunity ◽  
Nighttime Light ◽  
Multi Level

Satellite-based measurements of the artificial nighttime light brightness (NTL) have been extensively used for studying urbanization and socioeconomic dynamics in a temporally consistent and spatially explicit manner. The increasing availability of geo-located big data detailing human population dynamics provides a good opportunity to explore the association between anthropogenic nocturnal luminosity and corresponding human activities, especially at fine time/space scales. In this study, we used Visible Infrared Imaging Radiometer Suite (VIIRS) day/night band (DNB)–derived nighttime light images and the gridded number of location requests (NLR) from China’s largest social media platform to investigate the quantitative relationship between nighttime light radiances and human population dynamics across China at four levels: the provincial, city, county, and pixel levels. Our results show that the linear relationship between the NTL and NLR might vary with the observation level and magnitude. The dispersion between the two variables likely increases with the observation scale, especially at the pixel level. The effect of spatial autocorrelation and other socioeconomic factors on the relationship should be taken into account for nighttime light-based measurements of human activities. Furthermore, the bivariate relationship between the NTL and NLR was employed to generate a partition of human settlements based on the combined features of nighttime lights and human population dynamics. Cross-regional comparisons of the partitioned results indicate a diverse co-distribution of the NTL and NLR across various types of human settlements, which could be related to the city size/form and urbanization level. Our findings may provide new insights into the multi-level responses of nighttime light signals to human activity and the potential application of nighttime light data in association with geo-located big data for investigating the spatial patterns of human settlement.

scholarly journals Analyzing the Relationship between Developed Land Area and Nighttime Light Emissions of 36 Chinese Cities

2018 ◽  
Vol 11 (1) ◽  
pp. 10 ◽  
Author(s):  
Hui-min Li ◽  
Xiao-gang Li ◽  
Xiao-ying Yang ◽  
Hao Zhang
Keyword(s):  
Structural Equation ◽  
Light Emission ◽  
Land Development ◽  
Equation Model ◽  
Panel Regression ◽  
Land Area ◽  
Human Settlements ◽  
Nighttime Light ◽  
Low Efficiency ◽  
The Relationship

The satellite-observed nighttime light emission (NTLE) data provide a new method for scrutinizing the footprint of human settlements. Changing NTLEs can be attributed to the direct/indirect influences of highly complex factors that are beyond the ability of simple statistical models to distinguish. Besides, the relatively coarse resolution of the NTLE products combined with light from human settlements may produce misleading results, as the relationship between spatiotemporal heterogeneity in the growth of developed land (e.g., urban and rural residences, shopping centers, industrial parks, mining plants, and transportation facilities) and the associated NTLEs has not been adequately analyzed. In this study, we developed a total nighttime brightness index (TotalNTBI) to measure the NTLEs with the defense meteorological satellite program/operational linescan system (DMSP/OLS) nighttime light data enhanced by sharpening the edges of the pixels. Thirty-six key cities in China were selected to investigate the relationship between the total developed land area and the associated TotalNTBI from 2000 to 2013 using panel regression and a simplified structural equation model (SEM). The results show that the overall trend in TotalNTBI agreed well with that of the total developed land area (mean adjusted R2 = 0.799). The panel regression models explained approximately 71.8% of the variance of total developed land area and 92.4% of the variance in TotalNTBI. The SEM revealed both the direct and indirect influences of independent variables on the total developed land area and the associated TotalNTBI. This study may provide useful information for decision-makers and researchers engaged in sustainable land development, urban management, and regional developmental inequality, focusing on recent issues, such as retrospective analysis of human footprint with sharpened nighttime NTLE products, the loss of natural and semi-natural land due to the sprawling developed land area indicated by intensively lit area, and the low efficiency of land development indicated by the anomalies of developed land area and associated NTBIs.

Estimating Provincial Economic Development Level of China Using DMSP/OLS Nighttime Light Satellite Imagery

2013 ◽  
Vol 807-809 ◽  
pp. 1903-1908 ◽  
Author(s):  
Liang Tang ◽  
Hui Cheng ◽  
Ge Qu
Keyword(s):  
Economic Development ◽  
Satellite Imagery ◽  
Regional Economic Development ◽  
Coefficient Of Determination ◽  
Regional Economic ◽  
Development Level ◽  
Nighttime Light Data ◽  
Cubic Model ◽  
Nighttime Light ◽  
Development Levels

How to estimate regional economic development level is important for solving regional inequality problems. Most of previous studies on regional economic development are based on the statistics collected typically in administrative units. This paper has analyzed the defects of traditional studies, and attempted to research regional economic development problems with 10-year DMSP/OLS nighttime light satellite imagery as a new data source. For exploring the relationship between DMSP/OLS nighttime light data and GDP, different types of curve fitting regression models have been tried, the Cubic model has shown the best performance with a coefficient of determination (R2) equal to 0.803. Based on this positive correlation, we have estimated provincial economic development level of China using DMSP/OLS nighttime light data. The research results have indicated that the DMSP/OLS nighttime light data can well reveal provincial economic development levels.

scholarly journals Direct measurement of the contribution of street lighting to satellite observations of nighttime light emissions from urban areas

2020 ◽  
pp. 147715352095846
Author(s):  
CCM Kyba ◽  
A Ruby ◽  
HU Kuechly ◽  
B Kinzey ◽  
N Miller ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Satellite Imagery ◽  
Smart City ◽  
Urban Areas ◽  
Energy Use ◽  
Satellite Observations ◽  
Light Sources ◽  
Street Lighting ◽  
Nighttime Light ◽  
The City

Nighttime light emissions are increasing in most countries worldwide, but which types of lighting are responsible for the increase remains unknown. Also unknown is what fraction of outdoor light emissions and associated energy use are due to public light sources (i.e. streetlights) or various types of private light sources (e.g. advertising). Here we show that it is possible to measure the contribution of street lighting to nighttime satellite imagery using ‘smart city’ lighting infrastructure. The city of Tucson, USA, intentionally altered its streetlight output over 10 days, and we examined the change in emissions observed by satellite. We find that streetlights operated by the city are responsible for only 13% of the total radiance (in the 500–900 nm band) observed from Tucson from space after midnight (95% confidence interval 10–16%). If Tucson did not dim their streetlights after midnight, the contribution would be 18% (95% confidence interval 15–23%). When streetlights operated by other actors are included, the best estimates rise to 16% and 21%, respectively. Existing energy and lighting policy related to the sustainability of outdoor light use has mainly focused on street lighting. These results suggest an urgent need for consideration of other types of light sources in outdoor lighting policy.

scholarly journals The agglomeration and dispersion dichotomy of human settlements on Earth

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emanuele Strano ◽  
Filippo Simini ◽  
Marco De Nadai ◽  
Thomas Esch ◽  
Mattia Marconcini
Keyword(s):  
High Resolution ◽  
Spatial Patterns ◽  
Satellite Imagery ◽  
Ecological Impacts ◽  
Human Settlements ◽  
Cultural Economic ◽  
Historical Processes ◽  
High Resolution Satellite Imagery ◽  
Global Classification

AbstractHuman settlements on Earth are scattered in a multitude of shapes, sizes and spatial arrangements. These patterns are often not random but a result of complex geographical, cultural, economic and historical processes that have profound human and ecological impacts. However, little is known about the global distribution of these patterns and the spatial forces that creates them. This study analyses human settlements from high-resolution satellite imagery and provides a global classification of spatial patterns. We find two emerging classes, namely agglomeration and dispersion. In the former, settlements are fewer than expected based on the predictions of scaling theory, while an unexpectedly high number of settlements characterizes the latter. To explain the observed spatial patterns, we propose a model that combines two agglomeration forces and simulates human settlements’ historical growth. Our results show that our model accurately matches the observed global classification (F1: 0.73), helps to understand and estimate the growth of human settlements and, in turn, the distribution and physical dynamics of all human settlements on Earth, from small villages to cities.

scholarly journals TRACKING DYNAMIC CHANGES AND MONITORING SOCIOECONOMIC PARAMETERS IN ALGERIA BETWEEN 1993 AND 2012, USING NIGHTTIME LIGHT REMOTE SENSING

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1127-1135 ◽  
Author(s):  
B. Faouzi ◽  
P. Washaya
Keyword(s):  
Remote Sensing ◽  
Dynamic Change ◽  
Remote Sensing Data ◽  
Calibration Method ◽  
Gas Production ◽  
Data Availability ◽  
Dynamic Changes ◽  
Human Settlements ◽  
Gas Flaring ◽  
Nighttime Light

This paper is based on using DMSP-OLS data from satellites nighttime light observations to detect both sources of light emissions in Algeria from human settlement areas and gas flaring from oil-extraction and natural gas production. We used the time series of data from DMSP-OLS images to examine the spatial and temporal characteristics of urban development in 48 Algerian provinces from 1993 to 2012. A systematic nighttime light calibration method was used to improve the consistency and comparability of the DSMPOSL images and then a separation is made between light detected from human settlements and light detected from gas flaring in order to allow us to study human settlements without other light emissions and then assess the suitability of using DMSP data in southern Algeria and its ability to monitor gas flaring. Linear regression methods were developed to identify the dynamic change of nighttime light and estimated its growth directions at pixel level. This work is the first to use nighttime light observations to detect and monitor the growth of human settlements in North Africa. In this study, we made use of DMSP-OLS data as a return ticket to the years of crises and we found the most affected provinces during that period. The DMSP-OLS data proved to be an index of growth in the economy during the period of stability in Algeria expressed by positive dynamic changes in the lighted area in all Algerian provinces. We used NTL data as an alternative to annual growth indexes for each province, which are unavailable, and its help as a monitoring system for socioeconomic parameters to fill the gap of data availability. We also proposed nighttime light remote sensing data as a useful tool to control and reduce CO2 emissions in Algeria’s petroleum sector.

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