Analysis of Panamanian DMSP/OLS nightlights corroborates suspicions of inaccurate fiscal data: A natural experiment examining the accuracy of GDP data

Marx, Andrew; Rogers, Melissa

doi:10.1016/j.rsase.2017.08.005

Cited by 9 publications

(6 citation statements)

References 15 publications

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“…The use of nighttime lights (NTL) data to proxy for economic activity is well-established in remote sensing and other disciplines [1][2][3][4][5][6][7][8][9][10]. This proxy enables research when traditional economic activity data, such as Gross Domestic Product (GDP), are either absent or are not trusted because of concerns about either measurement error or manipulation [11][12][13]. Potential advantages of NTL-based economic activity estimates are their timeliness, lower cost, comparability between countries irrespective of statistical capacity, and availability for spatial units below the level at which GDP data are reported.…”

Section: Introductionmentioning

confidence: 99%

Using Multi-Source Nighttime Lights Data to Proxy for County-Level Economic Activity in China from 2012 to 2019

Zhang

Gibson

2022

Remote Sensing

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The use of nighttime lights (NTL) data to proxy for local economic activity is well established in remote sensing and other disciplines. Validation studies comparing NTL data with traditional economic indicators, such as Gross Domestic Product (GDP), underpin this usage in applied studies. Yet the most widely cited validation studies do not use the latest NTL data products, may not distinguish between time-series and cross-sectional uses of NTL data, and usually are for aggregated units, such as nation-states or the first sub-national level, yet applied studies increasingly focus on smaller and lower-level spatial units. To provide more updated and disaggregated validation results, this study examines relationships between GDP and NTL data for 2657 county-level units in China, observed each year from 2012 to 2019. The NTL data used were from three sources: the Defense Meteorological Satellite Program (DMSP), whose time series was recently extended to 2019; and two sets of Visible Infrared Imaging Radiometer Suite (VIIRS) data products. The first set of VIIRS products is the recently released version 2 (V.2 VNL) annual composites, and the second is the NASA Black Marble annual composites. Contrasts were made between cross-sectional predictions for GDP differences between areas and time-series predictions of economic activity changes over time, and also considered different levels of spatial aggregation.

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Section: Introductionmentioning

confidence: 99%

Using Multi-Source Nighttime Lights Data to Proxy for County-Level Economic Activity in China from 2012 to 2019

Zhang

Gibson

2022

Remote Sensing

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“…where, TNL 1 and TNL 2 are the total nighttime lights of the adjacent two years, respectively, p is the number of years. In this paper, GDP [74] and EPC [75] were chosen to conduct a quantitative test on the correction results, since economic development patterns vary with natural environment and geographical location [12], the linear model (Equation (14)), quadratic polynomial model (Equation (15)), and power function model (Equation (16)) were used to uncover the optimal socioeconomic indicator dynamics models using nighttime data among China's different regions over time and then the best fitting equation was chosen to carry out fitting analysis, compare the fitting accuracy after the correction, and verify the accuracy of the correction algorithm.…”

Section: Calibration Results Verificationmentioning

confidence: 99%

“…The result shows that the extended nighttime light data set has good quality and reliable time consistency. Considering that the use of nighttime light data to reflect social and economic development is carried out by constructing the statistical relationship between TNL and socioeconomic parameters [7,9,35,74,75], this paper also evaluates the accuracy of the correction method proposed in this paper in predicting socioeconomic parameters by constructing a regression model between TNL and socioeconomic parameters.…”

Section: Discussionmentioning

confidence: 99%

An Improved Correction Method of Nighttime Light Data Based on EVI and WorldPop Data

et al. 2020

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Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) data has the shortcomings of discontinuous and pixel saturation effect. It was also incompatible with the Soumi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) data. In view those shortcomings, this research put forward the WorldPop and the enhanced vegetation index (EVI) adjusted nighttime light (WEANTL) using EVI and WorldPop data to achieve intercalibration and saturation correction of DMSP/OLS data. A long time series of nighttime light images of china from 2001 to 2018 was constructed by fitting the DMSP/OLS data and NPP/VIIRS data. Corrected nighttime light images were examined to discuss the estimation ability of gross domestic product (GDP) and electric power consumption (EPC) on national and provincial scales, respectively. The results indicated that, (1) after correction, the nighttime light (NTL) data can guarantee the growth trend on national and regional scales, and the interannual volatility of the corrected NTL data is lower than that of the uncorrected NTL data; (2) on the national scale, compared with the established model of NTL data and GDP data (NTL-GDP), the determination coefficient (R2) and the mean absolute relative error (MARE) are 0.981 and 8.518%. The R2 and MARE of the established model of NTL data and EPC data (NTL-EPC) were 0.990 and 4.655%; (3) on the provincial scale, the R2 and MARE of NTL-GDP model under the provincial units are 0.7386 and 38.599%. The R2 value and MARE of NTL-EPC model are 0.8927 and 29.319%; (4) on the provincial scale, the R2 and MARE of NTL-GDP model on time series are 0.9667 and 10.877%. The R2 and MARE of NTL-GDP model on time series are 0.9720 and 6.435%; the established TNL-GDP and TNL-EPC models with 30 provinces data all passed the F-test at the 0.001 level; (5) the prediction accuracy of GDP and EPC on time series was nearly 100%. Therefore, the correction method provided in this research can be applied in estimating the GDP and EPC on multiple scales reliably and accurately.

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“…Elvidge et al [29] used the DMSP/OLS nighttime light for 21 countries and found a strong positive relationship between nighttime light and GDP. Since then, similar studies using DMSP/OLS and NPP-VIIRS nighttime light images were carried out to test and verify the relationships in different regions and different scales [30][31][32][33][34][35][36][37][38]. For most of these studies, the coefficients of determination R 2 between the total nighttime lights and GDP are between 0.5 and 0.9.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Ability of NOAA-20 Monthly Composite Data for Socioeconomic Indicators Estimation and Urban Area Extraction

Song

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The new Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the National Oceanic and Atmospheric Administration-20 satellite (NOAA-20) is capable of imaging the Earth during both daytime and nighttime. The NOAA-20 VIIRS' Day/Night Band (DNB) enables a new generation of nighttime imaging applications. However, few studies investigated the ability of NOAA-20 DNB nighttime light data in modeling socioeconomic indicators (such as the gross domestic product (GDP) and electric power consumption (EPC)) and extracting urban areas. In this study, we first used a simple linear regression model to investigate the potential of NOAA-20 nighttime light data for estimating GDP and EPC at multiple scales; we then extracted urban areas from NOAA-20 nighttime light data by using support vector machines (SVM). Taking mainland China as the study area, we found that the correlation coefficient of determination R 2 between NOAA-20 nighttime light data and GDP/EPC at both provincial and prefectural scales are higher than 0.7. By comparing the results with NPP-VIIRS nighttime light data, similar R 2 values were obtained at both two scales, indicating that NOAA-20 nighttime light data and NPP-VIIRS data are comparable in estimating socioeconomic indicators. Moreover, NOAA-20 also shows a similar detection ability with NPP-VIIRS in extracting urban areas. This study demonstrated that NOAA-20 and NPP-VIIRS are comparable in economic statistics estimation and urban area extraction. The NOAA-20 nighttime light data can be a useful data source for enlightening more applications in the fields of socioeconomic and urban studies.

show abstract

Analysis of Panamanian DMSP/OLS nightlights corroborates suspicions of inaccurate fiscal data: A natural experiment examining the accuracy of GDP data

Cited by 9 publications

References 15 publications

Using Multi-Source Nighttime Lights Data to Proxy for County-Level Economic Activity in China from 2012 to 2019

Using Multi-Source Nighttime Lights Data to Proxy for County-Level Economic Activity in China from 2012 to 2019

An Improved Correction Method of Nighttime Light Data Based on EVI and WorldPop Data

Evaluating the Ability of NOAA-20 Monthly Composite Data for Socioeconomic Indicators Estimation and Urban Area Extraction

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