|   | 
Details
   web
Records
Author (down) Zhao, N.; Samson, E.L.
Title Estimation of virtual water contained in international trade products using nighttime imagery Type Journal Article
Year 2012 Publication International Journal of Applied Earth Observation and Geoinformation Abbreviated Journal International Journal of Applied Earth Observation and Geoinformation
Volume 18 Issue Pages 243-250
Keywords Virtual water; Nighttime imagery; Lit area; Urban population; International trade product; DMSP-OLS; remote sensing; satellite; light at night
Abstract Freshwater that is consumed in the process of producing a commodity is called virtual water – it represents all water use contained in that commodity. In social systems, water resources can flow when commodities are traded from one region to another. Quantitative monitoring and assessing virtual water flow related to international trade products is an important issue to comprehensively understand the balance of global water resources. In this study we tested the potential of the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime images in conjunction with the LandScan population dataset for estimation of virtual water contained in international trade products. Lit area (areal extent of night lights) and urban population were selected as proxies to estimate export virtual water (EVW), import virtual water (IVW), and traded virtual water (TVW) (summed EVW and IVW), respectively, on the national level. The results showed that IVW can be more accurately estimated than EVW regardless of lit area or urban population. Lit area is normally more appropriate for estimation of the virtual water of developed countries than those of developing countries, but urban population is more appropriate for estimation of the virtual water of developing countries than those of developed countries. Urban population is a better proxy than total population for estimations of virtual water. This study makes a negative finding in that there are relatively large underestimations for developed countries. Another negative finding is that neither lit area nor urban population can be used to estimate net import virtual water (NIVW).
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0303-2434 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number IDA @ john @ Serial 224
Permanent link to this record
 

 
Author (down) Zhao, N.; Liu, Y.; Cao, G.; Samson, E.L.; Zhang, J.
Title Forecasting China’s GDP at the pixel level using nighttime lights time series and population images Type Journal Article
Year 2017 Publication GIScience & Remote Sensing Abbreviated Journal GIScience & Remote Sensing
Volume 54 Issue 3 Pages 407-425
Keywords Remote Sensing
Abstract China’s rapid economic development greatly affected not only the global economy but also the entire environment of the Earth. Forecasting China’s economic growth has become a popular and essential issue but at present, such forecasts are nearly all conducted at the national scale. In this study, we use nighttime light images and the gridded Landscan population dataset to disaggregate gross domestic product (GDP) reported at the province scale on a per pixel level for 2000–2013. Using the disaggregated GDP time series data and the statistical tool of Holt–Winters smoothing, we predict changes of GDP at each 1 km × 1 km grid area from 2014 to 2020 and then aggregate the pixel-level GDP to forecast economic growth in 23 major urban agglomerations of China. We elaborate and demonstrate that lit population (brightness of nighttime lights × population) is a better indicator than brightness of nighttime lights to estimate and disaggregate GDP. We also show that our forecast GDP has high agreement with the National Bureau of Statistics of China’s demographic data and the International Monetary Fund’s predictions. Finally, we display uncertainties and analyze potential errors of this disaggregation and forecast method.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1548-1603 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2478
Permanent link to this record
 

 
Author (down) Zhao, N.; Hsu, F.-C.; Cao, G.; Samson, E.L.
Title Improving accuracy of economic estimations with VIIRS DNB image products Type Journal Article
Year 2017 Publication International Journal of Remote Sensing Abbreviated Journal International Journal of Remote Sensing
Volume 38 Issue 21 Pages 5899-5918
Keywords Remote Sensing
Abstract A new-generation of night-time lights (NTL) image products, the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) monthly composites, have been produced and released by the National Oceanic and Atmospheric Administration’s National Centers for Environmental Information. Compared with the last generation NTL image products, the Defense Meteorological Satellite Program’s Operational Linescan System stable light composites, the new NTL image products have finer spatial resolution with compatible radiance values across different month/year images. However, the current defects in VIIRS DNB monthly composites show ephemeral lights, relatively high radiance in winter months, and missing data over the high-latitude regions of the northern hemisphere in summer months. This study presents a method to improve the accuracy of the new NTL image products by statistically modelling the time series VIIRS NTL images and uses the improved imagery to estimate socio-economic factors. In this method, we first estimate radiance for each pixel with ‘no data’ in May, June, July, and August images and then exponentially smooth the monthly time series images to produce a 2014 annual VIIRS DNB image for the contiguous USA. Sum radiance derived from the smoothed annual image shows stronger correlations with gross domestic product at the state level and smaller standard errors of the estimate at the metropolitan and county levels compared with that extracted from the annual image produced by simply averaging the original monthly DNB composites. Such results infer that exponential smoothing effectively improves the quality of the VIIRS DNB images for annual economic estimation.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0143-1161 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number LoNNe @ kyba @ Serial 1692
Permanent link to this record
 

 
Author (down) Zhao, N.; Ghosh, T.; Samson, E.L.
Title Mapping spatio-temporal changes of Chinese electric power consumption using night-time imagery Type Journal Article
Year 2012 Publication International Journal of Remote Sensing Abbreviated Journal International Journal of Remote Sensing
Volume 33 Issue 20 Pages 6304-6320
Keywords DMSP-OLS; LandScan; remote sensing; China; satellite; light at night
Abstract China's rapid economic development in the last 20 years has resulted in increased demand for electricity and ensuing shortages in electric power supply. It is necessary to derive accurate and timely information regarding changing spatio-temporal patterns and trends of electric power consumption to inform future electricity allocation. Night-time annual image composites for 1995–2005 were obtained from the Defense Meteorological Satellite Program's Operational Linescan System and were inter-calibrated. The inter-calibrated night-time image composites were used in conjunction with the LandScan 2008 population data to estimate the amounts of electric power consumption in 1995, 2000 and 2005 for China at the province level. The estimated amounts of electric power consumption were then disaggregated to the pixel level. A pixel-based map was produced to show the spatio-temporal changes of electric power consumption from 1995 to 2005, in which 11 regional agglomerations with large increases of electric power consumption had emerged. During the process of producing this spatio-temporal change map, some errors were generated because of the use of single-year LandScan population data, imperfect reference regions for inter-calibration and a single threshold value for delimiting urban areas. However, we believe these errors are limited and acceptable, so we present this method of estimation and disaggregation to show the increases in electric consumption.
Address Department of Geography , Texas State University-San Marcos , San Marcos , TX , 78666 , USA
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0143-1161 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number IDA @ john @ Serial 223
Permanent link to this record
 

 
Author (down) Zhao, N.; Cao, G.; Zhang, W.; Samson, E.L.
Title Tweets or nighttime lights: Comparison for preeminence in estimating socioeconomic factors Type Journal Article
Year 2018 Publication ISPRS Journal of Photogrammetry and Remote Sensing Abbreviated Journal ISPRS Journal of Photogrammetry and Remote Sensing
Volume 146 Issue Pages 1-10
Keywords Remote Sensing
Abstract Nighttime lights (NTL) imagery is one of the most commonly used tools to quantitatively study socioeconomic systems over large areas. In this study we aim to use location-based social media big data to challenge the primacy of NTL imagery on estimating socioeconomic factors. Geo-tagged tweets posted in the contiguous United States in 2013 were retrieved to produce a tweet image with the same spatial resolution of the NTL imagery (i.e., 0.00833° × 0.00833°). Sum tweet (the total number of tweets) and sum light (summed DN value of the NTL image) of each state or county were obtained from the tweets and the NTL images, respectively, to estimate three important socioeconomic factors: personal income, electric power consumption, and fossil fuel carbon dioxide emissions. Results show that sum tweet is a better measure of personal income and electric power consumption while carbon dioxide emissions can be more accurately estimated by sum light. We further exploited that African-Americans adults are more likely than White seniors to post geotagged tweets in the US, yet did not find any significant correlations between proportions of the subpopulations and the estimation accuracy of the socioeconomic factors. Existence of saturated pixels and blooming effects and failure to remove gas flaring reduce quality of NTL imagery in estimating socioeconomic factors, however, such problems are nonexistent in the tweet images. This study reveals that the number of geo-tagged tweets has great potential to be deemed as a substitute of brightness of NTL to assess socioeconomic factors over large geographic areas.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0924-2716 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 1994
Permanent link to this record