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Author Ma, W.; Li, P. url  doi
openurl 
  Title An Object Similarity-Based Thresholding Method for Urban Area Mapping from Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS DNB) Data Type Journal Article
  Year 2018 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 10 Issue 2 Pages 263  
  Keywords (down) Remote Sensing  
  Abstract Nighttime light data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) provides a unique data source for mapping and monitoring urban areas at regional and global scales. This study proposes an object similarity-based thresholding method using VIIRS DNB data to map urban areas. The threshold for a target potential urban object was determined by comparing its similarity with all reference urban objects with known optimal thresholds derived from Landsat data. The proposed method includes four major steps: potential urban object generation, threshold optimization for reference urban objects, object similarity comparison, and urban area mapping. The proposed method was evaluated using VIIRS DNB data of China and compared with existing mapping methods in terms of threshold estimation and urban area mapping. The results indicated that the proposed method estimated thresholds and mapped urban areas accurately and generally performed better than the cluster-based logistic regression method. The correlation coefficients between the estimated thresholds and the reference thresholds were 0.9201–0.9409 (using Euclidean distance as similarity measure) and 0.9461–0.9523 (using Mahalanobis distance as similarity measure) for the proposed method and 0.9435–0.9503 for the logistic regression method. The average Kappa Coefficients of the urban area maps were 0.58 (Euclidean distance) and 0.57 (Mahalanobis distance) for the proposed method and 0.51 for the logistic regression method. The proposed method shows potential to map urban areas at a regional scale effectively in an economic and convenient way.  
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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 2341  
Permanent link to this record
 

 
Author Ivajnsic, D., & Žiberna, I. url  openurl
  Title Daljinsko zaznavanje svetlobne onesnaženosti v Sloveniji / Remote sensing of light polution in Slovenia Type Journal Article
  Year 2018 Publication Revija za geografijo Abbreviated Journal  
  Volume 13 Issue 1 Pages 113-132  
  Keywords (down) Remote Sensing  
  Abstract Izvleček

Daljinsko zaznavanje svetlobne onesnaženosti v Sloveniji

V članku so predstavljeni rezultati analize svetlobne onesnaženosti na območju Slovenije v obdobju 2013-2017. Podatki so pridobljeni s satelita Suomi NPP, ki snema površje Zemlje tudi v nočnem kanalu. Prikazani so rezultati svetlobne onesnaženosti po občinah in trendi svetlobne onesnaženosti v omenjenem obdobju. Posebej so izpostavljena območja z zelo visokimi in nizkimi vrednostmi svetlobne onesnaženosti.

Abstract

Remote sensing of light pollution in Slovenia

The study deals with the problem of light pollution in Slovenia in the period 2013-2017. Remotely sensed data were obtained from the Suomi NPP satellite, which is scanning the earth's surface at night. The findings and geospatial trends of light pollution in the mentioned time period are discussed on the national and municipal levels. Some areas with very high and low levels of light pollution were exposed.
 
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  Language Slovenian Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number IDA @ intern @ Serial 2343  
Permanent link to this record
 

 
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 (down) 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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  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  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 (down) 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.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Finnish Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  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 (down) 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 Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0034-4257 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2480  
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