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Author Roberts, T.S.
Title (up) A Lapland Longspur Tragedy: Being an Account of a Great Destruction of These Birds during a Storm in Southwestern Minnesota and Northwestern Iowa in March, 1904 Type Journal Article
Year 1907 Publication The Auk Abbreviated Journal The Auk
Volume 24 Issue 4 Pages 369-377
Keywords Animals
Abstract
Address
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 0004-8038 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2417
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Author Zhang, D.; Jones, R.R.; Powell-Wiley, T.M.; Jia, P.; James, P.; Xiao, Q.
Title (up) A large prospective investigation of outdoor light at night and obesity in the NIH-AARP Diet and Health Study Type Journal Article
Year 2020 Publication Environmental Health : a Global Access Science Source Abbreviated Journal Environ Health
Volume 19 Issue 1 Pages 74
Keywords Human Health; Remote Sensing; Circadian rhythms; Light at night; Light pollution; Obesity
Abstract BACKGROUND: Research has suggested that artificial light at night (LAN) may disrupt circadian rhythms, sleep, and contribute to the development of obesity. However, almost all previous studies are cross-sectional, thus, there is a need for prospective investigations of the association between LAN and obesity risk. The goal of our current study was to examine the association between baseline LAN and the development of obesity over follow-up in a large cohort of American adults. METHODS: The study included a sample of 239,781 men and women (aged 50-71) from the NIH-AARP Diet and Health Study who were not obese at baseline (1995-1996). We used multiple logistic regression to examine whether LAN at baseline was associated with the odds of developing obesity at follow-up (2004-2006). Outdoor LAN exposure was estimated from satellite imagery and obesity was measured based on self-reported weight and height. RESULTS: We found that higher outdoor LAN at baseline was associated with higher odds of developing obesity over 10 years. Compared with the lowest quintile of LAN, the highest quintile was associated with 12% and 19% higher odds of developing obesity at follow-up in men (OR (95% CI) = 1.12 (1.00, 1.250)) and women (1.19 (1.04, 1.36)), respectively. CONCLUSIONS: Our findings suggest that high LAN exposure could predict a higher risk of developing obesity in middle-to-older aged American adults.
Address Department of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1476-069X ISBN Medium
Area Expedition Conference
Notes PMID:32611430; PMCID:PMC7329409 Approved no
Call Number GFZ @ kyba @ Serial 3029
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Author Li, C.; Li, G.; Zhu, Y.; Ge, Y.; Kung, H.-te; Wu, Y.
Title (up) A likelihood-based spatial statistical transformation model (LBSSTM) of regional economic development using DMSP/OLS time series and nighttime light imagery Type Journal Article
Year 2017 Publication Spatial Statistics Abbreviated Journal Spatial Statistics
Volume 21 Issue B Pages 421-439
Keywords Remote Sensing
Abstract In a regional economy, the central city of a metropolitan area has a radiative effect and an accumulative effect on its surrounding cities. Considering the limitations of traditional data sources (e.g., its subjectivity) and the advantages of nighttime light data, including its objectivity, availability and cyclicity, this paper proposes a likelihood spatial statistical transformation model (LBSSTM) to invert for the gross domestic product (GDP) of the surrounding cities, using time series of Sum of Lights (SOL) data covering the central city and taking advantage of the economic and spatial association between the central city and the surrounding cities within a metropolitan area and the correlation between SOL and GDP. The Wuhan Metropolitan Area is chosen to verify the model using time series analysis and exploratory spatial data analysis (ESDA). The experimental results show the feasibility of the proposed LBSSTM. The prediction accuracy of our model is verified by cross-validation using data from 1998, 2004 and 2011, based on the 3σ rule. This model can quantitatively express the agglomeration and diffusion effect of the central city and reveal the spatial pattern of this effect. The results of this work are potentially useful in making spatio-temporal economic projections and filling in missing data from some regions, as well as gaining a deeper quantitative and spatio-temporal understanding of the laws underlying regional economic development.
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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 2211-6753 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number LoNNe @ kyba @ Serial 1644
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Author Min, M.; Zheng, J.; Zhang, P.; Hu, X.; Chen, L.; Li, X.; Huang, Y.; Zhu, L.
Title (up) A low-light radiative transfer model for satellite observations of moonlight and earth surface light at night Type Journal Article
Year 2020 Publication Journal of Quantitative Spectroscopy and Radiative Transfer Abbreviated Journal Journal of Quantitative Spectroscopy and Radiative Transfer
Volume in press Issue Pages 106954
Keywords Remote Sensing; Instrumentation
Abstract Lunar sun-reflected light can be effectively measured through a low-light band or a day/night band (DNB) implemented on space-based optical sensors. Based on moonlight, nocturnal observations for artificial light sources at night can be achieved. However, to date, an open-sourced and mature Low-Light Radiative Transfer Model (LLRTM) for the further understanding of the radiative transfer problem at night is still unavailable. Therefore, this study develops a new LLRTM at night with the correction of the lunar and active surface light sources. First, the radiative transfer equations with an active surface light source are derived for the calculation based on the lunar spectral irradiance (LSI) model. The simulation from this new LLRTM shows a minimal bias when compared with the discrete ordinates radiative transfer (DISORT) model. The simulated results of radiance and reflectance at the top of the atmosphere (TOA) also show that the surface light source has a remarkable impact on the radiative transfer process. In contrast, the change in the lunar phase angle has minimal influence. Also, comparing with space-based DNB radiance observations, LLRTM shows the potential to simulate space-based low-light imager observations under an effective surface light source condition during the night.
Address
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 0022-4073 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2850
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Author Sun, L.; Tang, L.; Shao, G.; Qiu, Q.; Lan, T.; Shao, J.
Title (up) A Machine Learning-Based Classification System for Urban Built-Up Areas Using Multiple Classifiers and Data Sources Type Journal Article
Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 12 Issue 1 Pages 91
Keywords Remote Sensing
Abstract Information about urban built-up areas is important for urban planning and management. However, obtaining accurate information about urban built-up areas is a challenge. This study developed a general-purpose built-up area intelligent classification (BAIC) system that supports various types of data and classifiers. All of the steps in the BAIC were implemented using Python modules including Numpy, Pandas, matplotlib, and scikit-learn. We used the BAIC to conduct a classification experiment that involved seven types of input data; namely, Point of Interest (POI), Road Network (RN), nighttime light (NTL), a combination of POI and RN data (POIRN), a combination of POI and NTL data (POINTL), a combination of RN and NTL data (RNNTL), and a combination of POI, RN, and NTL data (POIRNNTL), and five classifiers, namely, Logistic Regression (LR), Decision Tree (DT), Random Forests (RF), Gradient Boosted Decision Trees (GBDT), and AdaBoost. The results show the following: (1) among the 35 combinations of the five classifiers and seven types of input data, the overall accuracy (OA) ranged from 76 to 89%, F1 values ranged from 0.73 to 0.86, and the area under the receiver operating characteristic (ROC) curve (AUC) ranged from 0.83 to 0.95. The largest F1 value and OA were obtained using the POIRNNTL data and AdaBoost, while the largest AUC was obtained using POIRNNTL and POINTL data against AdaBoost, LR, and RF; and (2) the advantages of the BAIC include its support for multi-source input data, its objective accuracy assessment, and its robust classifiers. The BAIC can quickly and efficiently realize the automatic classification of urban built-up areas at a reasonably low cost and can be readily applied to other urban areas in the world where any kind of POI, RN, or NTL data coverage is available. The results of this study are expected to provide timely and effective reference information for urban planning and urban management departments, and could also potentially be used to develop large-scale maps of urban built-up areas in the future.
Address
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 2800
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