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Author Libertun de Duren, N, & Osorio, R. url  doi
openurl 
  Title The Effect of Public Expenditure on the Housing Deficit in Peru at the Municipal Level Type Journal Article
  Year 2020 Publication Housing Policy Debate Abbreviated Journal  
  Volume Issue Pages 1-23  
  Keywords Remote Sensing  
  Abstract What impact does public expenditure on housing have on the deficit in a municipality? This article answers this question for Peru for the period 2001–2013. Municipalities with high expenditure levels saw a reduction in the number of households lacking access to water, sanitation, and electricity. There was no significant change in cohabitation, overcrowding, or lack of documents of ownership. The analysis was based on the empirical association between mineral exploitation and housing deficit at the municipal level. Municipalities that benefited from the mineral boom after 2007 saw housing expenditures increase dramatically, which reduced the housing deficit associated with poor materials to 18% from 33% (the national average). In addition, the housing deficit related to lack of water, sanitation, and electricity decreased from 26% to 22%.  
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  Notes Approved no  
  Call Number IDA @ intern @ Serial (down) 2947  
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Author Zhang, A., Li, W., Wu, J., Lin, J., Chu, J., & Xia, C. url  doi
openurl 
  Title How can the urban landscape affect urban vitality at the street block level? A case study of 15 metropolises in China Type Journal Article
  Year 2020 Publication Environment and Planning B: Urban Analytics and City Science Abbreviated Journal  
  Volume Issue Pages  
  Keywords Remote Sensing  
  Abstract Urban vitality, as a metric, measures the attractiveness and competitiveness of a city and is a driver of development. As the physical and social space of human activities, the urban landscape has close connections with urban vitality according to classical theories. However, limited quantitative criteria for the urban landscape and gaps between macro urban planning and micro design create difficulties when constructing a vibrant city. In this study, we quantitatively examined the relationship between the urban landscape and urban vitality at the street block level using geospatial open data to discover where, how, and to what extent we could improve urban vitality, taking 15 Chinese metropolises as a case study. Results indicate that, among the three aspects of the urban landscape considered, the city plan pattern has the highest effect on stimulating vitality, followed by the land use and the patterns of building form. Specifically, the three-dimensional form of buildings has a greater effect than a two-dimensional form. In addition, convenient transportation, a compact block form, diverse buildings, mixed land use, and high buildings are the main characteristics of vibrant blocks. The results also show that the effects of the urban landscape have spatial variations and obvious diurnal discrepancies. Furthermore, over 20 and 33% of the blocks in these cities are identified as low-vitality blocks during the day and night, respectively, and are then categorized into six different types. The identification of the common characteristics of these low-vitality blocks can be taken as references for designing a vibrant urbanity.  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number IDA @ intern @ Serial (down) 2946  
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Author Zheng, Q.; Weng, Q.; Wang, K. url  doi
openurl 
  Title Correcting the Pixel Blooming Effect (PiBE) of DMSP-OLS nighttime light imagery Type Journal Article
  Year 2020 Publication Remote Sensing of Environment Abbreviated Journal Remote Sensing of Environment  
  Volume 240 Issue Pages 111707  
  Keywords *instrumentation; Remote Sensing  
  Abstract In the last two decades, the advance in nighttime light (NTL) remote sensing has fueled a surge in extensive research towards mapping human footprints. Nevertheless, the full potential of NTL data is largely constrained by the blooming effect. In this study, we propose a new concept, the Pixel Blooming Effect (PiBE), to delineate the mutual influence of lights from a pixel and its neighbors, and an integrated framework to eliminate the PiBE in radiance calibrated DMSP-OLS datasets (DMSPgrc). First, lights from isolated gas flaring sources and a Gaussian model were used to model how the PiBE functions on each pixel through point spread function (PSF). Second, a two-stage deblurring approach (TSDA) was developed to deconvolve DMSPgrc images with Tikhonov regularization to correct the PiBE and reconstruct PiBE-free images. Third, the proposed framework was assessed by synthetic data and VIIRS imagery and by testing the resulting image with two applications. We found that high impervious surface fraction pixels (ISF > 0.6) were impacted by the highest absolute magnitude of PiBE, whereas NTL pattern of low ISF pixels (ISF < 0.2) was more sensitive to the PiBE. By using TSDA the PiBE in DMSPgrc images was effectively corrected which enhanced data variation and suppressed pseudo lights from non-built-up pixels in urban areas. The reconstructed image had the highest similarity to reference data from synthetic image (SSIM = 0.759) and VIIRS image (r = 0.79). TSDA showed an acceptable performance for linear objects (width > 1.5 km) and circular objects (radius > 0.5 km), and for NTL data with different noise levels (<0.6σ). In summary, the proposed framework offers a new opportunity to improve the quality of DMSP-OLS images and subsequently will be conducive to NTL-based applications, such as mapping urban extent, estimating socioeconomic variables, and exploring eco-impact of artificial lights.  
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  Series Volume Series Issue Edition  
  ISSN 0034-4257 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial (down) 2940  
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Author Yeh, C.; Perez, A.; Driscoll, A.; Azzari, G.; Tang, Z.; Lobell, D.; Ermon, S.; Burke, M. url  doi
openurl 
  Title Using publicly available satellite imagery and deep learning to understand economic well-being in Africa Type Journal Article
  Year 2020 Publication Nature Communications Abbreviated Journal Nat Commun  
  Volume 11 Issue 1 Pages 2583  
  Keywords Remote Sensing  
  Abstract Accurate and comprehensive measurements of economic well-being are fundamental inputs into both research and policy, but such measures are unavailable at a local level in many parts of the world. Here we train deep learning models to predict survey-based estimates of asset wealth across ~ 20,000 African villages from publicly-available multispectral satellite imagery. Models can explain 70% of the variation in ground-measured village wealth in countries where the model was not trained, outperforming previous benchmarks from high-resolution imagery, and comparison with independent wealth measurements from censuses suggests that errors in satellite estimates are comparable to errors in existing ground data. Satellite-based estimates can also explain up to 50% of the variation in district-aggregated changes in wealth over time, with daytime imagery particularly useful in this task. We demonstrate the utility of satellite-based estimates for research and policy, and demonstrate their scalability by creating a wealth map for Africa's most populous country.  
  Address National Bureau of Economic Research, 1050 Massachusetts Avenue, Cambridge, MA, 02138-5398, USA. mburke@stanford.edu  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2041-1723 ISBN Medium  
  Area Expedition Conference  
  Notes PMID:32444658 Approved no  
  Call Number GFZ @ kyba @ Serial (down) 2939  
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Author Wang, H.; Li, J.; Gao, M.; Chan, T.-C.; Gao, Z.; Zhang, M.; Li, Y.; Gu, Y.; Chen, A.; Yang, Y.; Ho, H.C. url  doi
openurl 
  Title Spatiotemporal variability in long-term population exposure to PM2.5 and lung cancer mortality attributable to PM2.5 across the Yangtze River Delta (YRD) region over 2010–2016: A multistage approach Type Journal Article
  Year 2020 Publication Chemosphere Abbreviated Journal Chemosphere  
  Volume in press Issue Pages 127153  
  Keywords Remote Sensing  
  Abstract The Yangtze River Delta region (YRD) is one of the most densely populated regions in the world, and is frequently influenced by fine particulate matter (PM2.5). Specifically, lung cancer mortality has been recognized as a major health burden associated with PM2.5. Therefore, this study developed a multistage approach 1) to first create dasymetric population data with moderate resolution (1 km) by using a random forest algorithm, brightness reflectance of nighttime light (NTL) images, a digital elevation model (DEM), and a MODIS-derived normalized difference vegetation index (NDVI), and 2) to apply the improved population dataset with a MODIS-derived PM2.5 dataset to estimate the association between spatiotemporal variability of long-term population exposure to PM2.5 and lung cancer mortality attributable to PM2.5 across YRD during 2010–2016 for microscale planning. The created dasymetric population data derived from a coarse census unit (administrative unit) were fairly matched with census data at a fine spatial scale (street block), with R2 and RMSE of 0.64 and 27,874.5 persons, respectively. Furthermore, a significant urban-rural difference of population exposure was found. Additionally, population exposure in Shanghai was 2.9–8 times higher than the other major cities (7-year average: 192,000 μg·people/m3·km2). More importantly, the relative risks of lung cancer mortality in high-risk areas were 28%–33% higher than in low-risk areas. There were 12,574–14,504 total lung cancer deaths attributable to PM2.5, and lung cancer deaths in each square kilometer of urban areas were 7–13 times higher than for rural areas. These results indicate that moderate-resolution information can help us understand the spatiotemporal variability of population exposure and related health risk in a high-density environment.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0045-6535 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial (down) 2938  
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