scholarly journals Identifying and Correcting Signal Shift in DMSP-OLS Data

2020 ◽  
Vol 12 (14) ◽  
pp. 2219
Author(s):  
Konstantin Ash ◽  
Kevin Mazur
Keyword(s):  
Recent Analysis ◽  
Control Points ◽  
Public Goods Provision ◽  
Defense Meteorological Satellite Program ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
Social Scientific ◽  
The Relationship ◽  
Meteorological Satellite ◽  
Scientific Fields

Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) nighttime light data has become a key tool of the environmental and social scientific fields, but suffers from several validity problems. We highlight one such problem—shifts in the digital number position in DMSP-OLS composites in the same satellite. We present techniques for identifying the problem, using moving window raster correlation and visual inspection, and for solving the problem, by assigning control points and manually shifting raster positions. To illustrate the importance of accounting for signal shift, we re-examine a recent analysis of the relationship between public goods provision and patterns of violence in the 2011 Syrian uprising and ensuing civil war. We find the statistical results change considerably when correcting for signal shift. We attribute this change to the systematic undercounting of light intensity in heavily populated areas. We close by identifying the types of research that would most benefit from our correction and suggest future refinements to our technique through automation.

Measuring the regional non-observed economy in China with nighttime lights

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Menggen Chen ◽  
Shuai Zhang
Keyword(s):  
Design Methodology ◽  
Eastern Region ◽  
Middle Region ◽  
Content Type ◽  
Nighttime Lights ◽  
Defense Meteorological Satellite Program ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
Average Size ◽  
Meteorological Satellite

PurposeThe non-observed economy (NOE) is a pervasive phenomenon worldwide, especially in developing countries, but the size of the NOE and its contributions to the overall economy are usually unknown. This paper presents an estimation of the average size of the NOE for the 31 provincial regions in China between 1992 and 2013.Design/methodology/approachThis study uses the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data combined with 11 existing surveys on or measurements of NOE for 191 countries or regions throughout the world, to measure the size of the NOE.FindingsThe results show that the NOE share is unevenly distributed among China's provincial regions, with the smallest being 3.19% for Beijing and the largest being 69.71% for Ningxia. The national average is 43.11%, while the figures for the eastern region, middle region, northeastern region and western region are 39.3%, 47.6%, 44.7% and 43.6%, respectively. The NOE estimates are negatively correlated with the measured gross domestic product (GDP) and GDP per capita, which suggests that developed regions tend to have less NOE.Originality/valueThe nighttime lights are used to measure the NOE for China's provincial regions. Compared with traditional databases, one of the prominent features of nighttime lights is its objectivity, as there is little human interference; therefore, it can be used to achieve more accurate results.

Assessing nighttime lights for mapping the urban areas of 50 cities across the globe

2018 ◽  
Vol 46 (6) ◽  
pp. 1097-1114
Author(s):  
Hasi Bagan ◽  
Habura Borjigin ◽  
Yoshiki Yamagata
Keyword(s):  
Urban Areas ◽  
Comprehensive Evaluation ◽  
Grid Cell ◽  
Small Cities ◽  
Large Cities ◽  
Nighttime Lights ◽  
Defense Meteorological Satellite Program ◽  
Nighttime Light ◽  
The Relationship ◽  
Meteorological Satellite

Nighttime data from the Defense Meteorological Satellite Program Operational Linescan System have been widely used to map urban/built-up areas (hereafter referred to as “built-up area”), but to date there has not been a geographically comprehensive evaluation of the effectiveness of using nighttime lights data to map urban areas. We created accurate, convenient, and scalable grid cells based on Defense Meteorological Satellite Program/Operational Linescan System nighttime light pixels. We then calculated the density of Landsat-derived built-up areas within each grid cell. We explored the relationship between Defense Meteorological Satellite Program/Operational Linescan System nighttime lights data and the density of built-up areas to assess the utility of nighttime lights for mapping urban areas in 50 cities across the globe. We found that the brightness of nighttime lights was only in moderate agreement with the density of built-up areas; moreover, correlations between nighttime lights and Landsat-derived built-up areas were weak. Even in relatively sparsely populated urban regions (where the density of the built-up area is less than 20%), the highest correlation coefficient ( R2) was only 0.4. Furthermore, nighttime lights showed lighted areas that extended beyond the area of large cities, and nighttime lights reduced the area of small cities. The results suggest that it is difficult to use the regression model to calibrate the Defense Meteorological Satellite Program/Operational Linescan System nighttime lights to fit urban built up areas.

Political Dynasties and Economic Development: Evidence using Nighttime Light in the Philippines

2021 ◽  
Vol 41 (3) ◽  
pp. 215-261
Author(s):  
Ludigil Garces ◽  
Karl Jandoc ◽  
Mary Grace Lu
Keyword(s):  
Economic Development ◽  
Political Competition ◽  
The Philippines ◽  
Economic Effects ◽  
Checks And Balances ◽  
Weak Institutions ◽  
Defense Meteorological Satellite Program ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
Relationship Of

Abstract Political dynasties, by limiting political competition, are thought to exacerbate corruption, poverty, and abuse of power. This paper examines the economic effects of the presence of political dynasties in Philippine cities and municipalities, taking into account possible channels in the local dynastic cycle – the framework in which politicians try to balance their goals to perform well for their constituents, to divert resources for personal gain, and to continue to be in power. Due to the lack of extensive income accounts or other economic indicators in finer geographical units (i.e., city or municipality level), we use the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) nighttime light data as our proxy for economic activity. Using a panel of Philippine municipalities and cities, we find that, in general, the relationship of political dynasties on economic performance is weak. However, we find that a higher share of economic expenditures leads to lower economic development in municipalities where the mayor, governor, and congressman belong to the same clan. We see this as an indication of weak institutions of checks and balances in localities with dynasties.

scholarly journals Influence of Industry-University Cooperation on Economic Development: A Mathematical Statistical Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xiaodi Xu ◽  
Yongfeng Zhu ◽  
Liuyang Xu ◽  
Zilong Wang
Keyword(s):  
Economic Development ◽  
Technological Innovation ◽  
Measurement Model ◽  
Technical Innovation ◽  
Nighttime Light Data ◽  
Important Means ◽  
Nighttime Light ◽  
University Cooperation ◽  
The Relationship ◽  
Positive Effect

Technical innovation is an important means to achieve sustainable development. Industry-university cooperation is a new form of technological innovation. Most of the existing researches on industry-university cooperation focus on the analysis of industry-university cooperation models, but there are few researches on the examination of the relationship between industry-university cooperation and economic development. Using the spatial autocorrelation and spatial measurement model, the relationship between China’s industry-university cooperation and economic development was empirically investigated. The results indicate that, first, the nighttime light data could be used as a proxy variable for GDP data to characterize China’s economic development. Second, industry-university cooperation had a positive effect on China’s economic development. Third, industry-university cooperation affected China’s economic development through technological innovation.

Explaining the pitfalls of quantifying population in riverine floodplains using Nighttime Light

2020 ◽  
Author(s):  
Lisa Verschuren ◽  
Fernando Nardi ◽  
Jeremy Bricker ◽  
Olivier Hoes ◽  
Serena Ceola ◽  
...  
Keyword(s):  
Flood Risk ◽  
Population Data ◽  
Flood Frequency ◽  
Nighttime Light Data ◽  
Flood Exposure ◽  
Nighttime Light ◽  
Socio Economic Variables ◽  
Floodplain Development ◽  
Near Future ◽  
The Relationship

<p>Flooding is globally one of the most damaging natural hazards. Flood risk will most likely increase in the near future due to increases in flood frequency attributed to climate change and growth in population and wealth in flood prone areas. This growth in wealth and population is increasingly considered as a major driver for the increase in flood losses in the last decades. Floodplains are susceptible to floods, but historically people have always been settling in floodplains. The growth of population in floodplains, which is a substantial cause for increased flood risk, is essential to consider for decision making in floodplain development, as improper development increases flood exposure and aggravates flood risk. The science of socio-hydrology tries to capture the interaction between humans and floods in the floodplain, but it is necessary to identify these mechanisms on a broader scale. A way of doing this, is to look at the development of floodplain population density over the years, but population data is not available on a long temporal scale. Therefore, Nighttime light data was used to model the gaps in the availability of population data. Nighttime light data captures the illumination on earth and is available on a large temporal and spatial scale. It also has a high correlation with population data. However, the relationship between Nighttime light data and population data is not straightforward. This study tries to model a population proxy using Nighttime light data and explains when and why it does or does not work. Validation of the model shows that in some regions the predicted data is relatively precise, but ultimately, due to the lack of data, the accuracy is unknown. This study shows that understanding the behavior of NTL is valuable, because it has the potential to map Socio-Economic variables in data-scarce areas.</p>

scholarly journals Night on South Korea: Unraveling the Relationship between Urban Development Patterns and DMSP-OLS Night-Time Lights

2019 ◽  
Vol 11 (18) ◽  
pp. 2140 ◽  
Author(s):  
Mingyu Kang ◽  
Meen Jung
Keyword(s):  
South Korea ◽  
Urban Development ◽  
Landscape Metrics ◽  
Night Time ◽  
Aggregation Index ◽  
Development Patterns ◽  
Defense Meteorological Satellite Program ◽  
Heterogeneous Datasets ◽  
The Relationship ◽  
Meteorological Satellite

Using artificial light data measured from satellites has the potential to change research methods in geography and urban planning. The Defense Meteorological Satellite Program Optical Linescan System (DMSP-OLS) night-time light datasets provided consistent and valuable data sources for investigating urbanization processes. This study intends to empirically investigate the relationship between night-time lights, population, and urban development patterns. A novel protocol was developed to integrate heterogeneous datasets into a standardized unit of analysis. Multivariate mixed-effects models were applied to detect correlations within and between provinces in South Korea. To capture physical variations of urban development, four landscape metrics were used and tested in the analyses. Diminishing returns of night-time lights to population were found in all models. In single landscape metric models, all coefficients of landscape metrics were positively related to night-time lights. In combination models, the aggregation index (AI) was no longer statistically significant. The protocol developed in this study provides an effective way to create analytical units for integrating heterogeneous forms of data. Creating standardized units of analyses will make it possible for researchers to compare their results with other studies. Landscape metrics used in this study for capturing the composition and configuration of urban development patterns will enrich the discussion in the future.

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