A Comparison of High and Low Gain DMSP/OLS Satellite Images for the Study of Socio-Economic Metrics

Roychowdhury, Koel; Jones, Simon; Arrowsmith, Colin; Reinke, Karin

doi:10.1109/jstars.2010.2053022

Cited by 18 publications

(16 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A number of studies have indicated that the nighttime light has a very high correlation with the national and regional economic volume [11,12]. Compared to the census approach, the mapping of nighttime light can help to investigate the economics on a large scale with very low cost; thus, the nighttime light imagery has been used to investigate the regional economics in many countries [13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China

et al. 2013

View full text Add to dashboard Cite

Historically, the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) was the unique satellite sensor used to collect the nighttime light, which is an efficient means to map the global economic activities. Since it was launched in October 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) Satellite has become a new satellite used to monitor nighttime light. This study performed the first evaluation on the NPP-VIIRS nighttime light imagery in modeling economy, analyzing 31 provincial regions and 393 county regions in China. For each region, the total nighttime light (TNL) and gross regional product (GRP) around the year of 2010 were derived, and a linear regression model was applied on the data. Through the regression, the TNL from NPP-VIIRS were found to exhibit R 2 values of 0.8699 and 0.8544 with the provincial GRP and county GRP, respectively, which are significantly stronger than the relationship between the TNL from DMSP-OLS (F16 and F18 satellites) and GRP. Using the regression models, the GRP was predicted from the TNL for each region, and we found that the NPP-VIIRS data is more predictable for the GRP than those of the DMSP-OLS data. This study demonstrates that the recently released NPP-VIIRS nighttime light imagery has a stronger capacity in modeling regional economy than those of the DMSP-OLS data. These findings provide a foundation OPEN ACCESSRemote Sens. 2013, 5 3058 to model the global and regional economy with the recently availability of the NPP-VIIRS data, especially in the regions where economic census data is difficult to access.

show abstract

Section: Introductionmentioning

confidence: 99%

Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China

et al. 2013

View full text Add to dashboard Cite

show abstract

“…The sharp contrast between the lit-up areas and the dark background of the NTL images opens up a panorama of socioeconomic activities of the earth in the night-time [16]. NTL data has been widely applied in various aspects of social science research such as socioeconomic development [9,12,17], energy consumption [11,18,19], light pollution [20], forest fire monitoring [21][22][23], snow cover detection [24], war studies [25], etc.…”

Section: Introductionmentioning

confidence: 99%

Estimating Land Development Time Lags in China Using DMSP/OLS Nighttime Light Image

Zhang

Wang

2015

Remote Sensing

View full text Add to dashboard Cite

Abstract:The Chinese real estate industry has experienced rapid growth since China's economic reform. Along with a booming industry, a third of purchased lands were left undeveloped in the last decade. Knowledge of real estate development time lags between land being purchased and property being occupied can enable policymakers to produce more effective policies and regulations to guide the real estate industry and sustain economic development and social welfare. This paper presents an innovative method to estimate provincial land development time lags in China using DMSP/OLS NTL imagery and real estate statistical data. The results showed that real estate development time lag was common in China during 2000-2010. More than half of the study sites showed development time lags of three years or longer. An Increment of Developed Pixels (IDP) index was established to outline yearly land development completions in China between 2000 and 2010. A Comprehensive Real Estate Price Index (CREPI) was created to explore the causes of the time lags. A strong and positive correlation was found between the real estate development time lags and CREPI values (with r = 0.619, n = 31, p < 0.0005). The results indicated that the land development time lag during the study period was positively correlated to the activity of the local real estate market, the price trend of land and housing properties, and the local economic situation. The results also proved that with the support of statistical data the

show abstract

“…As a result, the overall radiance and stable lights captured by nighttime images over these states are comparatively low when compared to the Mumbai and Delhi conurbations. Therefore, the model adjusted r 2 values, though significant, are low compared to other parts of the country, as observed by the authors in their previous publications [6,7,18,20]. Furthermore, the health data was calculated on a sample population from the districts.…”

Section: Modelsmentioning

confidence: 93%

“…The first global map of the GDP purchasing power parity (GDP-PPP) [14] and gas flares [15] used radiance calibrated DMSP-OLS data to map urban and suburban extent around cities [16,17]. At the smaller spatial scale, the DMSP-OLS dataset was used to estimate population and other socio-economic metrics for the state of Maharashtra in India [7,[18][19][20][21] and GDP estimates [22].…”

Section: Data Usedmentioning

confidence: 99%

“…The information from two nighttime satellite images were used along with these data to propose models. Unlike previous works by the authors [6,7], this research takes into account the development indicators along with the information from satellite images as predictor variables to prepare the models. The models successfully predict the health indicators with high accuracy (less than 7%-10% error).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Nexus of Health and Development: Modelling Crude Birth Rate and Maternal Mortality Ratio Using Nighttime Satellite Images

Roychowdhury

Jones

2014

IJGI

Self Cite

View full text Add to dashboard Cite

Health and development are intricately related. Although India has made significant progress in the last few decades in the health sector and overall growth in GDP, there are still large regional differences in both health and development. The main objective of this paper is to develop techniques for the prediction of health indicators for all the districts of India and examine the correlations between health and development. The level of electrification and district domestic product (DDP) are considered as two fundamental indicators of development in this research. These data, along with health metrics and the information from two nighttime satellite images, were used to propose the models. These successfully predicted the health indicators with less than a 7%-10% error. The chosen health metrics, such as crude birth rate (CBR) and maternal mortality rate (MMR), were mapped for the whole country at the district level. These metrics showed very strong correlation with development indicators (correlation coefficients ranging from 0.92 to 0.99 at the 99% confidence interval). This is the first attempt to use Visible Infrared Imaging Radiometer Suite (VIIRS) (satellite) imagery in a socio-economic study. This paper endorses the observation that areas with a higher DDP and level of electrification have overall better health conditions.

show abstract

A Comparison of High and Low Gain DMSP/OLS Satellite Images for the Study of Socio-Economic Metrics

Cited by 18 publications

References 14 publications

Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China

Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China

Estimating Land Development Time Lags in China Using DMSP/OLS Nighttime Light Image

Nexus of Health and Development: Modelling Crude Birth Rate and Maternal Mortality Ratio Using Nighttime Satellite Images

Contact Info

Product

Resources

About