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Author Singhal, R. K., Kumar, M., & Bose, B. url  doi
openurl 
  Title Ecophysiological Responses of Artificial Night Light Pollution in Plants Type Journal Article
  Year 2018 Publication Russian Journal of Plant Physiology Abbreviated Journal  
  Volume Issue Pages  
  Keywords Plants  
  Abstract Early in the 20th century, disparate human developmental processes culminate excess artificial light during night time and distort the phenological, physiological and ecological responses, which are sustained in the plants, animals and microorganism from millions of years. Earlier studies regarding artificial light (AL) during the night predominantly covered the drastic effects on animal systems. Although, drastic effects of AL during night time are enormous; therefore, the present topic is focused on the physiological and ecological consequences of artificial night light pollution (ANLP) on plant systems. In these consequences, most of the plant processes under ANLP are affected intensely and cause compelling changes in plant life cycle from germination to maturity. However, severe effects were observed in the case of pollination, photoreceptor signalling, flowering and microhabitats of plants. Along with drastic effects on ecology and environments, its relevance to human developmental processes cannot be avoided. Therefore, we need to equipoise between sustainable environment and steadily human development processes. Further, selection of plant/crop species, which are more responsive to ANLP, can minimize the ecological consequences of night light pollution. Likewise, changing artificial nightscape with the implication of new LEDs (Light Emitting Diodes) lightening policies like UJALA (www.ujala.gov.in), which are low cost, more durable, eco-friendly and less emitter of CO2, have potential to overcome the biodiversity threats, which arise due to old artificial lightening technology from decades. Hence, adopting new advance artificial lightening technology and understanding its impact on plant ecosystem will be a future challenge for plant biologist.  
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  Notes Approved no  
  Call Number IDA @ intern @ Serial 2352  
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Author Zhao, N., Zhang, W., Liu, Y., Samson, E. L., Chen, Y., & Cao, G. url  doi
openurl 
  Title Improving Nighttime Light Imagery With Location-Based Social Media Data Type Journal Article
  Year 2018 Publication IEEE Transactions on Geoscience and Remote Sensing Abbreviated Journal  
  Volume 57 Issue 4 Pages  
  Keywords Remote Sensing  
  Abstract Location-based social media have been extensively utilized in the concept of “social sensing” to exploit dynamic information about human activities, yet joint uses of social sensing and remote sensing images are underdeveloped at present. In this paper, the close relationship between the number of Twitter users and brightness of nighttime lights (NTL) over the contiguous United States is calculated and geotagged tweets are then used to upsample a stable light image for 2013. An associated outcome of the upsampling process is the solution of two major problems existing in the NTL image, pixel saturation, and blooming effects. Compared with the original stable light image, digital number (DN) values of the upsampled stable light image have larger correlation coefficients with gridded population (0.47 versus 0.09) and DN values of the new generation NTL image product (0.56 versus 0.52), i.e., the Visible Infrared Imaging Radiometer Suite day/night band image composite. In addition, total personal incomes of states are disaggregated to each pixel in proportion to the DN value of the pixel in the NTL images and then aggregate by counties. Personal incomes distributed by the upsampled NTL image are closer to the official demographic data than those distributed by the original stable light image. All of these results explore the potential of geotagged tweets to improve the quality of NTL images for more accurately estimating or mapping socioeconomic factors.  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number IDA @ intern @ Serial 2353  
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Author Hiltunen, A. P., Kumpula, T., &Tykkyläinen, M. url  openurl
  Title Yövalaistuksen ja valopäästöjen alueellinen jakautuminen Type Journal Article
  Year 2018 Publication Geoinformatiikka Yhteiskunnassa Abbreviated Journal  
  Volume 130 Issue 4 Pages  
  Keywords Remote Sensing  
  Abstract Remotely-sensed night-time lights (NTL) reveal the occurrence of human development while excessive light emissions cause ecological impacts and may create human health hazards. The aim of this research is to find out the factors affecting the quantity of remotely-sensed NTLs in Finland at 2015. We also aim to unveil how much NTLs have changed in Finland from 1993 to 2012 and what is the share of NTLs for different land use types in Finland in 2015. Answers to these questions are achieved with satellite radiance data and data on spatial structure, multiple linear regression (MLR), and change-detection methods. National and regional MLR models were produced to explain NTL and to compare the suitability of this modelling approach in different regions. Radiance is explained by population density, industrial building density, and lit roads density. Surprisingly, the brightest areas in Finland seem to be in Närpiö, a rural area with low population density but where greenhouse farming is common. Based on change-detection, new light sources have emerged because of the expansion of mining and tourism industries.  
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  Language Finnish Summary Language Original Title  
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  Notes Approved no  
  Call Number IDA @ intern @ Serial 2354  
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Author Wang, L.; Wang, S.; Zhou, Y.; Liu, W.; Hou, Y.; Zhu, J.; Wang, F. url  doi
openurl 
  Title Mapping population density in China between 1990 and 2010 using remote sensing Type Journal Article
  Year 2018 Publication Remote Sensing of Environment Abbreviated Journal Remote Sensing of Environment  
  Volume 210 Issue Pages 269-281  
  Keywords Remote Sensing  
  Abstract Knowledge of the spatial distribution of populations at finer spatial scales is of significant value and fundamental to many applications such as environmental change, urbanization, regional planning, public health, and disaster management. However, detailed assessment of the population distribution data of countries that have large populations (such as China) and significant variation in distribution requires improved data processing methods and spatialization models. This paper described the construction of a novel population spatialization method by combining land use/cover data and night-light data. Based on the analysis of data characteristics, the method used partial correlation analysis and geographically weighted regression to improve the distribution accuracy and reduce regional errors. China's census data for the years 1990, 2000, and 2010 were assessed. The results showed that the method was better at population spatialization than methods that use only night-light data or land use/cover data and global linear regression. Evaluation of overall accuracies revealed that the coefficient of correlation R-square was >0.90 and increased by >0.13 in the years 1990, 2000, and 2010. Moreover, the local R-square of over 90% of the samples (counties) was higher than the adjusted R-square of the general linear regression model. Furthermore, the gridded population density datasets obtained by this method can be used to analyse spatial-temporal patterns of population density and provide population distribution information with increased accuracy and precision compared to conventional models.  
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  Series Volume Series Issue Edition  
  ISSN 0034-4257 ISBN Medium  
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  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2480  
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Author Tan, M.; Li, X.; Li, S.; Xin, L.; Wang, X.; Li, Q.; Li, W.; Li, Y.; Xiang, W. url  doi
openurl 
  Title Modeling population density based on nighttime light images and land use data in China Type Journal Article
  Year 2018 Publication Applied Geography Abbreviated Journal Applied Geography  
  Volume 90 Issue Pages 239-247  
  Keywords Remote Sensing  
  Abstract Population change is a key variable that influences climate change, ecological construction, soil and water use, and economic growth. Census data are always point data, whereas planar data are often required in scientific research. By using nighttime light (NTL) images and land use data, combined with the fifth and sixth census data of China at the county level, we carried out spatial matching on the population of each county, respectively, and established population density diagrams of China for 2000 and 2010, which had a spatial resolution of 1 × 1 km. The method proposed in this paper is relatively simple and has a high simulation precision. The results showed that during the first ten years of the 21st century, there are some remarkable characteristics in Chinese population spatial pattern change: 1) the “disappearance” of intermediate-density regions; namely, areas with a population density between 500 and 1500 persons/km2 have decreased by 41% during the ten years; 2) continuous growth of high-density regions; namely, areas with a population density of more than 1500 persons/km2 have increased by 76%; 3) an expansion tendency of low-density regions similar to high-density regions.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0143-6228 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2481  
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