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Cao, C.; Shao, X.; Uprety, S. |
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Title |
Detecting Light Outages After Severe Storms Using the S-NPP/VIIRS Day/Night Band Radiances |
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2013 |
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IEEE Geoscience and Remote Sensing Letters |
Abbreviated Journal |
IEEE Geosci. Remote Sensing Lett. |
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10 |
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6 |
Pages |
1582-1586 |
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Remote Sensing |
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Abstract |
Power outages after a major storm affect the lives of millions of people and cause massive light outages. The launch of the Suomi National Polar-orbiting Partnership satellite with the Visible Infrared Imaging Radiometer Suite (VIIRS) significantly enhances our capability to monitor and detect light outages with the well-calibrated day/night band (DNB) and to use light loss signatures as indication of regional power outages. This study explores the use of the DNB in quantifying light outages due to the derecho storm in the Washington DC metropolitan area in June 2012 and Hurricane Sandy at the end of October 2012 on the East Coast of U.S. The results show that the DNB data are very useful in detecting power outages by quantifying light loss, but it also has some challenges due to clouds, lunar illumination, and straylight effect. Comparison of light outage and recovery trend determined from DNB data with power company survey shows reasonable agreement, demonstrating the usefulness of DNB in independently verifying and complementing the statistics from power companies. |
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1545-598X |
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GFZ @ kyba @ |
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2040 |
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Cao, X.; Chen, J.; Imura, H.; Higashi, O. |
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Title |
A SVM-based method to extract urban areas from DMSP-OLS and SPOT VGT data |
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Journal Article |
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2009 |
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Remote Sensing of Environment |
Abbreviated Journal |
Remote Sensing of Environment |
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113 |
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10 |
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2205-2209 |
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Remote Sensing |
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Mapping urban areas at regional and global scales has become an urgent task because of the increasing pressures from rapid urbanization and associated environmental problems. Satellite imaging of stable anthropogenic lights from DMSP-OLS provides an accurate, economical, and straightforward way to map the global distribution of urban areas. To address problems in the thresholding methods that use empirical strategies or manual trial-and-error procedures, we proposed a support vector machine (SVM)-based region-growing algorithm to semi-automatically extract urban areas from DMSP-OLS and SPOT NDVI data. Several simple criteria were used to select SVM training sets of urban and non-urban pixels, and an iterative classification and training procedure was adopted to identify the urban pixels through region growing. The new method was validated using the extents of 25 Chinese cities, as classified by Landsat ETM+ images, and then compared with two common thresholding methods. The results showed that the SVM-based algorithm could not only achieve comparable results to the local-optimized threshold method, but also avoid its tedious trial-and-error procedure, suggesting that the new method is an easy and simple alternative for extracting urban extent from DMSP-OLS and SPOT NDVI data. |
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0034-4257 |
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GFZ @ kyba @ |
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2041 |
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Shi, K.; Yu, B.; Huang, Y.; Hu, Y.; Yin, B.; Chen, Z.; Chen, L.; Wu, J. |
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Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data |
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Journal Article |
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2014 |
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Remote Sensing |
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Remote Sensing |
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6 |
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2 |
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1705-1724 |
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Remote Sensing |
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The nighttime light data records artificial light on the Earth’s surface and can be used to estimate the spatial distribution of the gross domestic product (GDP) and the electric power consumption (EPC). In early 2013, the first global NPP-VIIRS nighttime light data were released by the Earth Observation Group of National Oceanic and Atmospheric Administration’s National Geophysical Data Center (NOAA/NGDC). As new-generation data, NPP-VIIRS data have a higher spatial resolution and a wider radiometric detection range than the traditional DMSP-OLS nighttime light data. This study aims to investigate the potential of NPP-VIIRS data in modeling GDP and EPC at multiple scales through a case study of China. A series of preprocessing procedures are proposed to reduce the background noise of original data and to generate corrected NPP-VIIRS nighttime light images. Subsequently, linear regression is used to fit the correlation between the total nighttime light (TNL) (which is extracted from corrected NPP-VIIRS data and DMSP-OLS data) and the GDP and EPC (which is from the country’s statistical data) at provincial- and prefectural-level divisions of mainland China. The result of the linear regression shows that R2 values of TNL from NPP-VIIRS with GDP and EPC at multiple scales are all higher than those from DMSP-OLS data. This study reveals that the NPP-VIIRS data can be a powerful tool for modeling socioeconomic indicators; such as GDP and EPC. |
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2072-4292 |
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GFZ @ kyba @ |
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2042 |
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Pulgar, J.; Zeballos, D.; Vargas, J.; Aldana, M.; Manriquez, P.; Manriquez, K.; Quijon, P.A.; Widdicombe, S.; Anguita, C.; Quintanilla, D.; Duarte, C. |
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Endogenous cycles, activity patterns and energy expenditure of an intertidal fish is modified by artificial light pollution at night (ALAN) |
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Journal Article |
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2018 |
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Environmental Pollution (Barking, Essex : 1987) |
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Environ Pollut |
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244 |
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361-366 |
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Animals |
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The increase of global light emissions in recent years has highlighted the need for urgent evaluation of their impacts on the behaviour, ecology and physiology of organisms. Numerous species exhibit daily cycles or strong scototaxic behaviours that could potentially be influenced if natural lighting conditions or cycles are disrupted. Artificial Light Pollution at Night (ALAN) stands for situations where artificial light alters natural light-dark cycles, as well as light intensities and wavelengths. ALAN is increasingly recognized as a potential threat to biodiversity, mainly because a growing number of studies are demonstrating its influence on animal behaviour, migration, reproduction and biological interactions. Most of these studies have focused on terrestrial organisms and ecosystems with studies on the effects of ALAN on marine ecosystems being more occasional. However, with the increasing human use and development of the coastal zone, organisms that inhabit shallow coastal or intertidal systems could be at increasing risk from ALAN. In this study we measured the levels of artificial light intensity in the field and used these levels to conduct experimental trials to determine the impact of ALAN on an intertidal fish. Specifically, we measured ALAN effects on physiological performance (oxygen consumption) and behaviour (activity patterns) of “Baunco” the rockfish Girella laevifrons, one of the most abundant and ecologically important intertidal fish in the Southeastern Pacific littoral. Our results indicated that individuals exposed to ALAN exhibited increased oxygen consumption and activity when compared with control animals. Moreover, those fish exposed to ALAN stopped displaying the natural (circatidal and circadian) activity cycles that were observed in control fish throughout the experiment. These changes in physiological function and behaviour could have serious implications for the long-term sustainability of fish populations and indirect impacts on intertidal communities in areas affected by ALAN. |
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Departamento de Ecologia & Biodiversidad, Facultad de Ciencia de la Vida, Universidad Andres Bello, Chile; Center for the Study of Multiple-Drivers on Marine Socio-Ecological Systems (MUSELS), Universidad de Concepcion, Concepcion, Chile |
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0269-7491 |
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PMID:30352350 |
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GFZ @ kyba @ |
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2043 |
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Ashford, O.M. |
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A portable cloud searchlight |
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1947 |
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Weather |
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2 |
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103-104 |
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Remote Sensing |
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GFZ @ kyba @ |
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2044 |
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