Night-Time Light Dynamics during the Iraqi Civil War

Li, Xi; Liu, Shanshan; Jendryke, Michael; Li, Deren; Wu, Chen

doi:10.3390/rs10060858

Cited by 64 publications

(34 citation statements)

References 45 publications

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“…By inter-calibrating DMSP-OLS and VIIRS monthly composites, the NTL dynamics during January 2011 to January 2017 were analyzed, showing a slight recovery of NTL due to the peace agreement between the Syrian Government and the rebel groups [118]. In addition to the Syrian conflict, VIIRS images have also been applied to analyze the civil wars in Yemen [119] and Iraq [120,121], showing that the time series VIIRS images are able to reflect electricity usage during the war.…”

Section: Conflicts and Disastersmentioning

confidence: 99%

Applications of Satellite Remote Sensing of Nighttime Light Observations: Advances, Challenges, and Perspectives

et al. 2019

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Nighttime light observations from remote sensing provide us with a timely and spatially explicit measure of human activities, and therefore enable a host of applications such as tracking urbanization and socioeconomic dynamics, evaluating armed conflicts and disasters, investigating fisheries, assessing greenhouse gas emissions and energy use, and analyzing light pollution and health effects. The new and improved sensors, algorithms, and products for nighttime lights, in association with other Earth observations and ancillary data (e.g., geo-located big data), together offer great potential for a deep understanding of human activities and related environmental consequences in a changing world. This paper reviews the advances of nighttime light sensors and products and examines the contributions of nighttime light remote sensing to perceiving the changing world from two aspects (i.e., human activities and environmental changes). Based on the historical review of the advances in nighttime light remote sensing, we summarize the challenges in current nighttime light remote sensing research and propose four strategic directions, including: Improving nighttime light data; developing a long time series of consistent nighttime light data; integrating nighttime light observations with other data and knowledge; and promoting multidisciplinary and interdisciplinary analyses of nighttime light observations.

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Section: Conflicts and Disastersmentioning

confidence: 99%

Applications of Satellite Remote Sensing of Nighttime Light Observations: Advances, Challenges, and Perspectives

et al. 2019

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“…Numerous studies have demonstrated that the range and intensity of NTL are closely correlated to gross regional products (GRP) [6,[15][16][17], size and density of population [17][18][19], urbanization [2,20,21], electricity consumption [1,6,[22][23][24], light pollution [25][26][27], carbon dioxide (CO 2 ) emissions [28,29], and humanitarian disasters, etc. [30,31].…”

Section: Introductionmentioning

confidence: 99%

Statistical Correlation between Monthly Electric Power Consumption and VIIRS Nighttime Light

Lin

Shi

2020

IJGI

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The nighttime light (NTL) imagery acquired from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) enables feasibility of investigating socioeconomic activities at monthly scale, compared with annual study using nighttime light data acquired from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS). This paper is the first attempt to discuss the quantitative correlation between monthly composite VIIRS DNB NTL data and monthly statistical data of electric power consumption (EPC), using 14 provinces of southern China as study area. Two types of regressions (linear regression and polynomial regression) and nine kinds of NTL with different treatments are employed and compared in experiments. The study demonstrates that: (1) polynomial regressions acquire higher reliability, whose average R square is 0.8816, compared with linear regressions, whose average R square is 0.8727; (2) regressions between denoised NTL with threshold of 0.3 nW/(cm2·sr) and EPC steadily exhibit the strongest reliability among the nine kinds of processed NTL data. In addition, the polynomial regressions for 12 months between denoised NTL with threshold of 0.3 nW/(cm2·sr) and EPC are constructed, whose average values of R square and mean absolute relative error are 0.8906 and 16.02%, respectively. These established optimal regression equations can be used to accurately estimate monthly EPC of each province, produce thematic maps of EPC, and analyze their spatial distribution characteristics.

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“…Using remote sensing images to extract UBD information is also a fast and effective method to make up for the shortcomings of traditional manual mapping methods. Existing studies on UBD tend to use high-resolution remote sensing satellites for research because they are more accurate [11,28,29], but their shortcomings are also obvious, such as complex building analysis, the cumbersome automated extraction process, and a large number of computations.NTL remote sensing is widely used in macroeconomic and social parameter estimation [30][31][32], urban monitoring [33][34][35][36], great event change [37,38], energy consumption [39,40], ecological environment assessment [41,42], and other fields. Due to the low spatial resolution of NTL images, previous studies focused on macroscopic dimensions, such as national or urban scales.…”

mentioning

confidence: 99%

“…NTL remote sensing is widely used in macroeconomic and social parameter estimation [30][31][32], urban monitoring [33][34][35][36], great event change [37,38], energy consumption [39,40], ecological environment assessment [41,42], and other fields. Due to the low spatial resolution of NTL images, previous studies focused on macroscopic dimensions, such as national or urban scales.…”

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confidence: 99%

Correlation Analysis between UBD and LST in Hefei, China, Using Luojia1-01 Night-Time Light Imagery

et al. 2019

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The urban heat island (UHI) is one of the essential phenomena of the modern urban climate. In recent years, urbanization in China has gradually accelerated, and the heat island effect has also intensified as the urban impervious surface area and the number of buildings is increasing. Urban building density (UBD) is one of the main factors affecting UHI, but there is little discussion on the relationship between the two. This paper takes Hefei as the research area, combines UBD data estimated by Luojia1-01 night-time light (NTL) imagery as the research object with land surface temperature (LST) data obtained from Landsat8 images, and carries out spatial correlation analysis on 0.5 × 0.5 km to 2 × 2 km resolution for them, so as to explore the relationship between UBD and UHI. The results show the following: (1) Luojia1-01 data have a good ability to estimate UBD and have fewer errors when compared with the actual UBD data; (2) At the four spatial scales, UBD and LST present a significant positive correlation that increases with the enlargement of the spatial scale; and (3) Moreover, the fitting effect of the Geographically Weighted Regression (GWR) model is better than that of the ordinary least squares (OLS) regression model. Appl. Sci. 2019, 9, 5224 2 of 20 absorbing heat faster and the specific heat capacity being smaller gives rise to limited heat release. In this way, the average LST in the area gradually increases with the spatial distribution of the UHI area to become more continuous and concentrated, forming a high-temperature area centered on artificial buildings in the city [1,9,10]. However, our comprehensive literature research found that past studies focused on the analysis of seasonal, daily, and annual variations of the UHI, which revealed the temporal and spatial variation of the UHI, the distribution characteristics of the horizontal and vertical directions, etc., while there has been less quantitative analysis of the single factors of UHIs, especially discussion of the ubiquitous relationship between impervious surfaces and UHI in the city.As an integral part of the urban impervious surface percentage, the urban building density (UBD) (percentage of built area) can directly reflect the degree of intensification and land-use efficiency in cities to some extent [11]. It is also an essential comprehensive social indicator that can function as an urban planning layout measure [12,13], resource utilization efficiency measure [14,15], and assessment of the urban ecological environment and livability [16][17][18][19]. Some researchers have pointed out that UBD is a crucial indicator to reduce the UHI effect [20] and proved a positive correlation between UBD and LST or UHI [21][22][23]. Additionally, researchers have tried to use a variety of urban design factors to study the relationships of UHIs, including UBD information. For example, Yang studied the summer heat island intensity of three high-rise residential districts in Shanghai, based on the three indices of building layout, density, and greeni...

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Night-Time Light Dynamics during the Iraqi Civil War

Cited by 64 publications

References 45 publications

Applications of Satellite Remote Sensing of Nighttime Light Observations: Advances, Challenges, and Perspectives

Applications of Satellite Remote Sensing of Nighttime Light Observations: Advances, Challenges, and Perspectives

Statistical Correlation between Monthly Electric Power Consumption and VIIRS Nighttime Light

Correlation Analysis between UBD and LST in Hefei, China, Using Luojia1-01 Night-Time Light Imagery

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