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Author Chen, X. url  doi
openurl 
  Title Nighttime Lights and Population Migration: Revisiting Classic Demographic Perspectives with an Analysis of Recent European Data Type Journal Article
  Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 12 Issue 1 Pages 169  
  Keywords Remote Sensing  
  Abstract This study examines whether the Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime lights can be used to predict population migration in small areas in European Union (EU) countries. The analysis uses the most current data measured at the smallest administrative unit in 18 EU countries provided by the European Commission. The ordinary least squares regression model shows that, compared to population size and gross domestic product (GDP), lights data are another useful predictor. The predicting power of lights is similar to population but it is much stronger than GDP per capita. For most countries, regression models with lights can explain 50–90% of variances in small area migrations. The results also show that the annual VIIRS lights (2015–2016) are slightly better predictors for migration population than averaged monthly VIIRS lights (2014–2017), and their differences are more pronounced in high latitude countries. Further, analysis of quadratic models, models with interaction effects and spatial lag, shows the significant effect of lights on migration in the European region. The study concludes that VIIRS nighttime lights hold great potential for studying human migration flow, and further open the door for more widespread application of remote sensing information in studying dynamic demographic processes.  
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  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2072-4292 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2794  
Permanent link to this record
 

 
Author Andrade-Núñez, M.J.; Aide, T.M. url  doi
openurl 
  Title The Socio-Economic and Environmental Variables Associated with Hotspots of Infrastructure Expansion in South America Type Journal Article
  Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 12 Issue 1 Pages 116  
  Keywords Remote Sensing  
  Abstract The built environment, defined as all human-made infrastructure, is increasing to fulfill the demand for human settlements, productive systems, mining, and industries. Due to the profound direct and indirect impacts that the built environment produces on natural ecosystems, it is considered a major driver of land change and biodiversity loss, and a major component of global environmental change. In South America, a global producer of minerals and agricultural commodities, and a region with many biodiversity hotspots, infrastructure expanded considerably between 2001 and 2011. This expansion occurred mainly in rural areas, towns, and sprawling suburban areas that were not previously developed. Herein, we characterized the areas of major infrastructure expansion between 2001 and 2011 in South America. We used nighttime light data, land use maps, and socio-economic and environmental variables to answer the following questions: (1) Where are the hotspots of infrastructure expansion located? and (2) What combination of socio-economic and environmental variables are associated with infrastructure expansion? Hotspots of infrastructure expansion encompass 70% (337,310 km2) of the total infrastructure expansion occurring between 2001 and 2011 across South America. Urban population and economic growth, mean elevation, and mean road density were the main variables associated with the hotspots, grouping them into eight clusters. Furthermore, within the hotspots, woody vegetation increased around various urban centers, and several areas showed a large increase in agriculture. Investments in large scale infrastructure projects, and the expansion and intensification of productive systems (e.g., agriculture and meat production) play a dominant role in the increase of infrastructure across South America. We expect that under the current trends of globalization and land changes, infrastructure will continue increasing and expanding into no-development areas and remote places. Therefore, to fully understand the direct and indirect impacts of land use change in natural ecosystems studies of infrastructure need to expand to areas beyond cities. This will provide better land management alternatives for the conservation of biodiversity as well as peri-urban areas across South America.  
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  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 2072-4292 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2798  
Permanent link to this record
 

 
Author Chang, Y.; Wang, S.; Zhou, Y.; Wang, L.; Wang, F. url  doi
openurl 
  Title A Novel Method of Evaluating Highway Traffic Prosperity Based on Nighttime Light Remote Sensing Type Journal Article
  Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 12 Issue 1 Pages 102  
  Keywords Remote Sensing  
  Abstract As the backbone and arteries of a comprehensive transportation network, highways play an important role in improving people’s living standards and promoting economic growth. However, globally, there is limited quantifiable data evaluating the highway traffic state, characteristics, and performance. From the 1960s to the present, remote sensing has been regarded as the most effective technology for long-term and large-scale monitoring of surface information. However, how to reflect the dynamic “flow” information of traffic with a static remote sensing image has always been a difficult problem that is hard to solve in the field. This study aims to construct a method of evaluating highway traffic prosperity using nighttime remote sensing. First, based on nighttime light data that indicate social and economic activities, a highway-oriented method was proposed to extract highway nighttime light data from 2015 annual nighttime light data of the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite sensor (SNPP-VIIRS). Subsequently, Pearson correlation analysis was used to fit the relationship between freeway traffic flow volume and freeway nighttime light at the provincial level. The results showed that Pearson Correlation Coefficient of freeway nighttime light and freeway traffic flow volume for coach and truck are 0.905 and 0.731, respectively, which are higher than between freeway traffic flow volume for coach and truck and total nighttime light (0.593 and 0.516, respectively). A new index—Highway Nighttime Traffic Prosperity Index (HNTPI)—was proposed to evaluate highway traffic across China. The results showed that HNTPI has a strong correspondence with socio-economic parameters. The Pearson Correlation Coefficient of HNTPI and gross domestic product (GDP) per capita, consumption per capita, and population are 0.772, 0.895, and 0.968, respectively. There is a huge spatial heterogeneity in China nighttime traffic, the prosperity degree of highway traffic in developed coastal areas is obviously higher than that inland. The national general highway is the most prosperous highway at night and the national general highway nighttime prosperity of Shanghai reached 22.34%. This research provides basic data for the long-term monitoring and evaluation of regional traffic operation at night and research on the correlation between regional highway construction and the economy.  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2072-4292 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2801  
Permanent link to this record
 

 
Author Chen, X.; Nordhaus, W.D. url  doi
openurl 
  Title VIIRS Nighttime Lights in the Estimation of Cross-Sectional and Time-Series GDP Type Journal Article
  Year 2019 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 11 Issue 9 Pages 1057  
  Keywords Remote Sensing  
  Abstract This study extends previous applications of DMSP OLS nighttime lights data to examine the usefulness of newer VIIRS lights in the estimation of economic activity. Focusing on both US states and metropolitan statistical areas (MSAs), we found that the VIIRS lights are more useful in predicting cross-sectional GDP than predicting time-series GDP data. This result is similar to previous findings for DMSP OLS nighttime lights. Additionally, the present analysis shows that high-resolution VIIRS lights provide a better prediction for MSA GDP than for state GDP, which suggests that lights may be more closely related to urban sectors than rural sectors. The results also indicate the importance of considering biases that may arise from different aggregations (the modifiable areal unit problems, MAUP) in applications of nighttime lights in understanding socioeconomic phenomenon.  
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  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 2072-4292 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2495  
Permanent link to this record
 

 
Author Liu, A.; Wei, Y.; Yu, B.; Song, W. url  doi
openurl 
  Title Estimation of Cargo Handling Capacity of Coastal Ports in China Based on Panel Model and DMSP-OLS Nighttime Light Data Type Journal Article
  Year 2019 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 11 Issue 5 Pages 582  
  Keywords Remote Sensing  
  Abstract The cargo handling capacity of a port is the most basic and important indicator of port size. Based on the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) nighttime light data and panel model, this study attempts to estimate the cargo handling capacity of 28 coastal ports in China using satellite remote sensing. The study confirmed that there is a very close correlation between DMSP-OLS nighttime light data and the cargo handling capacity of the ports. Based on this correlation, the panel data model was established for remote sensing-based estimation of cargo handling capacity at the port and port group scales. The test results confirm that the nighttime light data can be used to accurately estimate the cargo handling capacity of Chinese ports, especially for the Yangtze River Delta Port Group, Pearl River Delta Port Group, Southeast Coastal Port Group, and Southwest Coastal Port Group that possess huge cargo handling capacities. The high accuracy of the model reveals that the remote sensing analysis method can make up for the lack of statistical data to a certain extent, which helps to scientifically analyze the spatiotemporal dynamic changes of coastal ports, provides a strong basis for decision-making regarding port development, and more importantly provides a convenient estimation method for areas that have long lacked statistical data on cargo handling capacity.  
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  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 2072-4292 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2337  
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