Nighttime light imagery offers a unique view of the Earth's surface. In the past, the nighttime light data collected by the DMSP-OLS sensors have been used as an efficient means to correlate regional ...and global socio-economic activities. With the launch of the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite in 2011, the day-night band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard represents a major advancement in nighttime imaging capabilities, because it surpasses its predecessor DMSP-OLS in radiometric accuracy, spatial resolution and geometric quality. In this paper, four variables (total night light, light area, average night light and log average night light) are extracted from nighttime radiance data observed by the VIIRS-DNB composite in 2013 and nighttime digital number (DN) data from the DMSP-OLS stable dataset in 2012, respectively, and correlated with 12 socio-economic parameters at the provincial level in mainland China during the corresponding period. Background noise of DNB composite data is removed using either a masking method or an optimal threshold method. In general, the correlation of these socio-economic data with the total night light and light area of VIIRS-DNB composite data is better than with the DMSP-OLS stable data. The correlations between total night light of denoised DNB composite data and built-up area, gross regional product (GRP) and power consumption are higher than 0.9 and so are the correlations between the light area of denoised DNB composite data and city and town population, built-up area, GRP, power consumption and waste water discharge. However, the correlations of socio-economic data with the average night light and log average night light of VIIRS-DNB composite data are not as good as with the DMSP-OLS stable data. To quantitatively analyze the reasons for the correlation difference, a cubic regression method is developed to correct the saturation effect of the DMSP stable data, and we artificially convert the pixel value of the DNB composite into six bits to match the DMSP stable data format. The correlation results between the processed data and socio-economic data show that the effects of saturation and quantization are two of the reasons for the correlation difference. Additionally, on this basis, we estimate the total night light ratio between saturation-corrected DMSP stable data and finite quantization DNB composite data, and it is found that the ratio is ~11.28 plus or minus 4.02 for China. Therefore, it appears that a different acquisition time is the other reason for the correlation difference.
With the rapid development of rural socio-economic in China, multi-source statistical information is one kind important data to enhance decision-making for government. The rural has become a major ...problem. In this paper, a set of GIS spatial analysis methods of rural social-economic data were proposed and researched on, spatial data and statistical data were integrated to create a comprehensive spatial database to realize data sharing with existent e-government system. On this basis, a GIS based rural socio-economic statistical system is constructed using COM pattern and put into effect in National Bureau of Statistics of China. It is proved that GIS technology applied in rural statistics department, which provides an information platform that manage and analyze statistical data and spatial data, is feasible and efficient.
A concern with the socioeconomic effects of chronic non-malignant pain, as well as the human aspects, inspired a search of the literature for evidence in this area. The review has identified three ...main areas of interest, socioeconomic statistics; pain prevalence in the community, and the quality of life issues. A selection of the literature is reviewed here under these headings, and the conclusion indicates possible areas for further work.
This Africa's pulse newsletter includes the following headings: economic prospects for Sub-Saharan Africa remain strong, but growth is vulnerable to a sharp decline in commodity prices; the region's ...progress on reducing poverty has been slow, hindered by high inequality; and faster reduction in poverty will require growth with equity.
This paper provides empirical evidence regarding the performance of community-based health care financing in terms of (a) social inclusion and (b) financial protection. Five non-standardized ...household surveys were analyzed from India (two samples), Senegal, Rwanda, and Thailand. Common methodology was applied to the five data sets. Logistic regression was used to estimate the determinants of enrolling in a community financing scheme. A two-part model was used to assess the determinants of financial protection: part one used logistic regression to estimate the determinants of the likelihood of visiting a health care provider; part two used ordinary least-squares regression to estimate the determinants of out-of-pocket payments. The research finds: (a) Social inclusion. The findings suggest that community financing can be inclusive of the poorest even in the most economically deprived context. Nevertheless, this targeting outcome is not automatically attributable to the involvement of the community; rather it depends on key design and implementation characteristics of the schemes. (b) Financial protection. Community financing reduces financial barriers to health care as demonstrated by higher utilization and simultaneously lower out-of-pocket expenditure of scheme members controlling for a range of socioeconomic variables. The paper concludes: (a) Social inclusion. Design and implementation characteristics of community financing schemes matter to achieve good targeting outcome-community involvement alone does not guarantee social inclusion. Further research is needed to delineate which design and implementation characteristics allow better inclusion of the poor. (b) Financial protection. Prepayment and risk sharing, even on a small scale, reduce financial access barriers.
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