| Records |
| Author |
Li, X.; Chen, X.; Zhao, Y.; Xu, J.; Chen, F.; Li, H. |
| Title |
Automatic intercalibration of night-time light imagery using robust regression |
Type |
Journal Article |
| Year |
2013 |
Publication |
Remote Sensing Letters |
Abbreviated Journal |
Remote Sensing Letters |
| Volume |
4 |
Issue |
1 |
Pages |
45-54 |
| Keywords |
remote sensing; light at night |
| Abstract |
In remote-sensing community, radiometric calibration of night-time light images has long been a problem, hindering change detection of images in different dates. Currently, an intercalibration model is regarded as the unique solution for the problem, but prior knowledge is needed to extract reference pixels with stable lights, which are hard to obtain in most of the applications. This study proposed an automatic algorithm to extract the reference pixels for convenient use of the intercalibration model, with an assumption that there are sufficient pixels with stable night-time lights in the multi-temporal images. To automatically extract the stable pixels from images in two dates, all pixels in the two dates were entered into a linear regression model, and the outliers viewed as suspected changed pixels were discarded iteratively. Consequently, some stable pixels were extracted and the intercalibration model was implemented. Annual night-time light composites in Beijing, China, from 1992 to 2010 were taken as the study material, and the results show that the multi-temporal calibrated night-time light data have higher correlation with gross domestic production (GDP) (R 2 = 0.8734) and urban population (UP) (R 2 = 0.9269) than those of the uncalibrated images (with the R 2 values 0.7963 and 0.8575, respectively). Furthermore, the data inconsistency from different night-time light satellites in the same year was reduced with the proposed algorithm. The results demonstrate that the proposed algorithm is effective in intercalibrating the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) images automatically. |
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2150-704X |
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IDA @ john @ |
Serial |
211 |
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| Author |
Li, X.; Ge, L.; Chen, X. |
| Title |
Detecting Zimbabwe's Decadal Economic Decline Using Nighttime Light Imagery |
Type |
Journal Article |
| Year |
2013 |
Publication |
Remote Sensing |
Abbreviated Journal |
Remote Sensing |
| Volume |
5 |
Issue |
9 |
Pages |
4551-4570 |
| Keywords |
Zimbabwe; economic decline; nighttime light; DMSP-OLS; remote sensing; light at night |
| Abstract |
Zimbabwe’s economy declined between 2000 and 2009. This study detects the economic decline in different regions of Zimbabwe using nighttime light imagery from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS). We found a good correlation (coefficient = 0.7361) between Zimbabwe’s total nighttime light (TNL) and Gross Domestic Product (GDP) for the period 1992 to 2009. Therefore, TNL was used as an indicator of regional economic conditions in Zimbabwe. Nighttime light imagery from 2000 and 2008 was compared at both national and regional scales for four types of regions. At the national scale, we found that nighttime light in more than half of the lit area decreased between 2000 and 2008. Moreover, within the four region types (inland mining towns, inland agricultural towns, border towns and cities) we determined that the mining and agricultural sectors experienced the most severe economic decline. Some of these findings were validated by economic survey data, proving that the nighttime light data is a potential data source for detecting the economic decline in Zimbabwe. |
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2072-4292 |
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IDA @ john @ |
Serial |
212 |
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| Author |
Butt, M.J. |
| Title |
Estimation of Light Pollution Using Satellite Remote Sensing and Geographic Information System Techniques |
Type |
Journal Article |
| Year |
2012 |
Publication |
GIScience & Remote Sensing |
Abbreviated Journal |
GIScience & Remote Sensing |
| Volume |
49 |
Issue |
4 |
Pages |
609-621 |
| Keywords |
DMSP-OLS; remote sensing; light pollution; measurements |
| Abstract |
The primary focus of this research is to estimate light pollution in the urban and suburban regions of Pakistan with the help of satellite remote sensing (SRS) and geographic information system (GIS) techniques. Analog maps and multi-temporal nighttime images of the Defense Meteorological Satellite Program (DMSP) onboard Operational Linescan System (OLS) sensor were used in this study. A series of direct and indirect light pollution maps of the study area were generated and analyzed. The results of the study show that in the urban environment, light pollution is mainly due to artificial nightlight sources. |
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King Abdulaziz University, Jeddah, Saudi Arabia |
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1548-1603 |
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IDA @ john @ |
Serial |
214 |
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Chen, B.; Shi, G.; Wang, B.; Zhao, J.; Tan, S. |
| Title |
Estimation of the anthropogenic heat release distribution in China from 1992 to 2009 |
Type |
Journal Article |
| Year |
2012 |
Publication |
Acta Meteorologica Sinica |
Abbreviated Journal |
Acta Meteorol Sin |
| Volume |
26 |
Issue |
4 |
Pages |
507-515 |
| Keywords |
DMSP/OLS; estimation; distribution; anthropogenic heat flux; China; remote sensing |
| Abstract |
Stable light data from Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) satellites and authoritative energy consumption data distributed by National Bureau of Statistics of China were applied to estimating the distribution of anthropogenic heat release in China from 1992 to 2009. A strong linear relationship was found between DMSP/OLS digital number data and anthropogenic heat flux density (AHFD). The results indicate that anthropogenic heat release in China was geographically concentrated and was fundamentally correlated with economic activities. The anthropogenic heat release in economically developed areas in northern, eastern, and southern China was much larger than other regions, whereas it was very small in northwestern and southwestern China. The mean AHFD in China increased from 0.07 W m−2 in 1978 to 0.28 W m−2 in 2008. The results indicate that in the anthropogenic heat-concentrated regions of Beijing, the Yangtze River Delta, and the Pearl River Delta, the AHFD levels were much higher than the average. The effect of aggravating anthropogenic heat release on climate change deserves further investigation. |
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0894-0525 |
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IDA @ john @ |
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215 |
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| Author |
Elvidge, C.D.; Baugh, K.E.; Anderson, S.J.; Sutton, P.C.; Ghosh, T. |
| Title |
The Lumen Gini Coefficient: a satellite imagery derived human development index |
Type |
Journal Article |
| Year |
2012 |
Publication |
Social Geography Discussions |
Abbreviated Journal |
Soc. Geogr. Discuss. |
| Volume |
8 |
Issue |
1 |
Pages |
27-59 |
| Keywords |
Gini coefficient; light at night; remote sensing; economics; development |
| Abstract |
The “Lumen Gini Coefficient” is a simple, objective, spatially explicit and globally available empirical measurement of human development derived solely from nighttime satellite imagery and population density. There is increasing recognition that the distribution of wealth and income amongst the population in a nation or region correlates strongly with both the overall happiness of that population and the environmental quality of that nation or region. Measuring the distribution of wealth and income at national and regional scales is an interesting and challenging problem. Gini coefficients derived from Lorenz curves are a well-established method of measuring income distribution. Nonetheless, there are many shortcomings of the Gini coefficient as a measure of income or wealth distribution. Gini coefficients are typically calculated using national level data on the distribution of income through the population. Such data are not available for many countries and the results are generally limited to single values representing entire countries. In this paper we develop an alternative measure of the distribution of “human development”, called the “Lumen Gini coefficient”, that is derived without the use of monetary measures of wealth and is capable of providing a spatial depiction of differences in development within countries. |
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NOAA National Geophysical Data Center, Boulder, Colorado, USA |
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1816-1502 |
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IDA @ john @ |
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216 |
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