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Author Qiang, Y.; Huang, Q.; Xu, J. url  doi
openurl 
  Title Observing Community Resilience from Space: Using Nighttime Lights to Model Economic Disturbance and Recovery Pattern in Natural Disaster Type Journal Article
  Year 2020 Publication Sustainable Cities and Society Abbreviated Journal Sustainable Cities and Society  
  Volume in press Issue Pages  
  Keywords Remote Sensing  
  Abstract (up) A major challenge for measuring community resilience is the lack of empirical observation in disasters. As an effective tool for observing human activities on the earth surface, night-time light (NTL) remote sensing images can fill the gap of empirical data for measuring community resilience in natural disasters. This study introduces a quantitative framework to model the recovery pattern of economic activity in a natural disaster using the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) images. The utility of the framework is demonstrated in a case study of Hurricane Katrina, which uncovered the great economic impact of Katrina and spatial variation of the disturbance and recovery pattern of economic activity. Environmental and socio-economic factors that potentially influence the economic recovery were explored in statistical analyses. Instead of a static and holistic index, the framework measures resilience as a dynamic process. The analysis results provide actionable information for prompting resilience in diverse communities and in different phases of a disaster. In addition to Hurricane Katrina, the resilience modeling framework is applicable for other disaster types. The introduced approaches and findings increase our understanding about the complexity of community resilience and provide support for developing resilient and sustainable communities.  
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  Series Volume Series Issue Edition  
  ISSN 2210-6707 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2833  
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Author Garstang, R.H. url  doi
openurl 
  Title Model for Artificial Night-Sky Illumination. Type Journal Article
  Year 1986 Publication Publ Astron Soc Pac Abbreviated Journal  
  Volume 98 Issue 601 Pages 364-375  
  Keywords Skyglow  
  Abstract (up) A model has been constructed to allow calculation of the night-sky brightness caused by a city at its center and outside the city, and at arbitrary zenith distances. A circular city of uniform brightness is assumed, with the total brightness proportional to the population. Molecular scattering and aerosol scattering are included, with the amount of aerosols being an adjustable parameter, and different scale heights being adopted for molecules and aerosols. The reflectivity of the ground and the fraction of light radiated above the horizontal are taken as parameters. Applications are given to several cities, to the general population-distance relations, to brightness-distance relations, and to the city center brightness-population relations  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number LoNNe @ kagoburian @ Serial 560  
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Author Garstang, R.H. url  doi
openurl 
  Title Night-sky brightness at observatories and sites. Type Journal Article
  Year 1989 Publication Publ Astron Soc Pac Abbreviated Journal  
  Volume 101 Issue Pages 306-329  
  Keywords Skyglow  
  Abstract (up) A model previously constructed for night-sky brightness calculations has been modified to allow for the curvature of the earth. The model has been applied to calculate the brightness at the following observatories: Mount Wilson, Lick, Mount Palomar, Kitt Peak, Sacramento Peak, Mauna Kea, McDonald, San Pedro Martir, Mount Hopkins, Mount Lemmon, Lowell (Mars Hill), Lowell (Anderson Mesa), Fick, Iowa, Van Vleck, David Dunlap, Anglo-Australian, Haute Provence, and Cerro Tololo. Calculations have also been carried out for the following prospective observatory sites: Junipero Serra, Mount Graham, Charleston Peak, Wheeler Peak, Miller Peak, San Benito Mountain, Lowell (Hutch Mountain), Lowell (Saddle Mountain), and South Baldy (New Mexico). The model is extended to calculate magnitudes in the B photometric band.  
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  Notes Approved no  
  Call Number LoNNe @ kagoburian @ Serial 559  
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Author Stone, J.E.; Phillips, A.J.K.; Ftouni, S.; Magee, M.; Howard, M.; Lockley, S.W.; Sletten, T.L.; Anderson, C.; Rajaratnam, S.M.W.; Postnova, S. url  doi
openurl 
  Title Generalizability of A Neural Network Model for Circadian Phase Prediction in Real-World Conditions Type Journal Article
  Year 2019 Publication Scientific Reports Abbreviated Journal Sci Rep  
  Volume 9 Issue 1 Pages 11001  
  Keywords Human Health; Instrumentation  
  Abstract (up) A neural network model was previously developed to predict melatonin rhythms accurately from blue light and skin temperature recordings in individuals on a fixed sleep schedule. This study aimed to test the generalizability of the model to other sleep schedules, including rotating shift work. Ambulatory wrist blue light irradiance and skin temperature data were collected in 16 healthy individuals on fixed and habitual sleep schedules, and 28 rotating shift workers. Artificial neural network models were trained to predict the circadian rhythm of (i) salivary melatonin on a fixed sleep schedule; (ii) urinary aMT6s on both fixed and habitual sleep schedules, including shift workers on a diurnal schedule; and (iii) urinary aMT6s in rotating shift workers on a night shift schedule. To determine predicted circadian phase, center of gravity of the fitted bimodal skewed baseline cosine curve was used for melatonin, and acrophase of the cosine curve for aMT6s. On a fixed sleep schedule, the model predicted melatonin phase to within +/- 1 hour in 67% and +/- 1.5 hours in 100% of participants, with mean absolute error of 41 +/- 32 minutes. On diurnal schedules, including shift workers, the model predicted aMT6s acrophase to within +/- 1 hour in 66% and +/- 2 hours in 87% of participants, with mean absolute error of 63 +/- 67 minutes. On night shift schedules, the model predicted aMT6s acrophase to within +/- 1 hour in 42% and +/- 2 hours in 53% of participants, with mean absolute error of 143 +/- 155 minutes. Prediction accuracy was similar when using either 1 (wrist) or 11 skin temperature sensor inputs. These findings demonstrate that the model can predict circadian timing to within +/- 2 hours for the vast majority of individuals on diurnal schedules, using blue light and a single temperature sensor. However, this approach did not generalize to night shift conditions.  
  Address School of Physics, University of Sydney, Sydney, New South Wales, Australia  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2045-2322 ISBN Medium  
  Area Expedition Conference  
  Notes PMID:31358781; PMCID:PMC6662750 Approved no  
  Call Number GFZ @ kyba @ Serial 2667  
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Author Roman, M.O.; Stokes, E.C.; Shrestha, R.; Wang, Z.; Schultz, L.; Carlo, E.A.S.; Sun, Q.; Bell, J.; Molthan, A.; Kalb, V.; Ji, C.; Seto, K.C.; McClain, S.N.; Enenkel, M. url  doi
openurl 
  Title Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria Type Journal Article
  Year 2019 Publication PloS one Abbreviated Journal PLoS One  
  Volume 14 Issue 6 Pages e0218883  
  Keywords Remote Sensing  
  Abstract (up) A real-time understanding of the distribution and duration of power outages after a major disaster is a precursor to minimizing their harmful consequences. Here, we develop an approach for using daily satellite nighttime lights data to create spatially disaggregated power outage estimates, tracking electricity restoration efforts after disasters strike. In contrast to existing utility data, these estimates are independent, open, and publicly-available, consistently measured across regions that may be serviced by several different power companies, and inclusive of distributed power supply (off-grid systems). We apply the methodology in Puerto Rico following Hurricane Maria, which caused the longest blackout in US history. Within all of the island's settlements, we track outages and recovery times, and link these measures to census-based demographic characteristics of residents. Our results show an 80% decrease in lights, in total, immediately after Hurricane Maria. During the recovery, a disproportionate share of long-duration power failures (> 120 days) occurred in rural municipalities (41% of rural municipalities vs. 29% of urban municipalities), and in the northern and eastern districts. Unexpectedly, we also identify large disparities in electricity recovery between neighborhoods within the same urban area, based primarily on the density of housing. For many urban areas, poor residents, the most vulnerable to increased mortality and morbidity risks from power losses, shouldered the longest outages because they lived in less dense, detached housing where electricity restoration lagged. The approach developed in this study demonstrates the potential of satellite-based estimates of power recovery to improve the real-time monitoring of disaster impacts, globally, at a spatial resolution that is actionable for the disaster response community.  
  Address Harvard Humanitarian Initiative, Cambridge, Massachusetts, United States of America  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 1932-6203 ISBN Medium  
  Area Expedition Conference  
  Notes PMID:31251791 Approved no  
  Call Number GFZ @ kyba @ Serial 2564  
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