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Author Priyatikanto, R.; Mayangsari, L.; Prihandoko, R.A.; Admiranto, A.G. url  doi
openurl 
  Title Classification of Continuous Sky Brightness Data Using Random Forest Type Journal Article
  Year 2020 Publication Advances in Astronomy Abbreviated Journal Advances in Astronomy  
  Volume 2020 Issue Pages 1-11  
  Keywords Skyglow  
  Abstract Sky brightness measuring and monitoring are required to mitigate the negative effect of light pollution as a byproduct of modern civilization. Good handling of a pile of sky brightness data includes evaluation and classification of the data according to its quality and characteristics such that further analysis and inference can be conducted properly. This study aims to develop a classification model based on Random Forest algorithm and to evaluate its performance. Using sky brightness data from 1250 nights with minute temporal resolution acquired at eight different stations in Indonesia, datasets consisting of 15 features were created to train and test the model. Those features were extracted from the observation time, the global statistics of nightly sky brightness, or the light curve characteristics. Among those features, 10 are considered to be the most important for the classification task. The model was trained to classify the data into six classes (1: peculiar data, 2: overcast, 3: cloudy, 4: clear, 5: moonlit-cloudy, and 6: moonlit-clear) and then tested to achieve high accuracy (92%) and scores (F-score = 84% and G-mean = 84%). Some misclassifications exist, but the classification results are considerably good as indicated by posterior distributions of the sky brightness as a function of classes. Data classified as class-4 have sharp distribution with typical full width at half maximum of 1.5 mag/arcsec2, while distributions of class-2 and -3 are left skewed with the latter having lighter tail. Due to the moonlight, distributions of class-5 and -6 data are more smeared or have larger spread. These results demonstrate that the established classification model is reasonably good and consistent.  
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  ISSN 1687-7969 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2878  
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Author Kii, M., Kronprasert, N., & Satayopas, B. url  doi
openurl 
  Title ESTIMATION OF TRANSPORT DEMAND USING SATELLITE IMAGE: CASE STUDY OF CHIANG MAI, THAILAND Type Journal Article
  Year 2020 Publication International Journal of GEOMATE Abbreviated Journal  
  Volume 18 Issue 69 Pages 111-117  
  Keywords Remote Sensing  
  Abstract Transport demand is one of the essential datasets for urban / transport planning and policy development. However, the full size of travel demand survey requires large amount of cost, therefore the survey is merely conducted in developing countries. Their policy decision might be based on the old and limited datasets. In this study we propose a new approach to estimate transport demand using the night-time light satellite image based on the correlation of these two factors. Taking the case of Chiang Mai Metropolitan area, we found a soft relationship between the night-time light intensity and trip generation/trip attraction. Transport survey data is provided by Chiang Mai University for the year 2016. NOAA provides cloud free monthly composite of night-time light satellite image (VIIRS-DNB) by Suomi-NPP satellite of which resolution is 15 arc-second (about 500m by 500m at equator). It is spatially more precise than zones of travel demand survey and monthly frequency. Applying the relationship between transport demand and night-time light intensity, we propose a method to update the transport demand with higher spatial resolution.  
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  Notes Approved no  
  Call Number IDA @ intern @ Serial 2963  
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Author Windle, A. E., Hooley, D. S., & Johnston, D. W. url  doi
openurl 
  Title Robotic Vehicles Enable High-Resolution Light Pollution Sampling of Sea Turtle Nesting Beaches Type Journal Article
  Year 2018 Publication Frontiers in Marine Science Abbreviated Journal  
  Volume 5 Issue 493 Pages  
  Keywords Instrumentation; Animals; Skyglow  
  Abstract Nesting sea turtles appear to avoid brightly lit beaches and often turn back to sea prematurely when exposed to artificial light. Observations and experiments have noted that nesting turtles prefer darker areas where buildings and high dunes act as light barriers. As a result, sea turtles often nest on darker beaches, creating spatial concentrations of nests. Artificial nighttime light, or light pollution, has been quantified using a variety of methods. However, it has proven challenging to make accurate measurements of ambient light at fine scales and on smaller nesting beaches. Additionally, light has traditionally been measured from stationary tripods perpendicular to beach vegetation, disregarding the point of view of a nesting sea turtle. In the present study, nighttime ambient light conditions were assessed on three beaches in central North Carolina: a developed coastline of a barrier island, a nearby State Park on the same barrier island comprised of protected and undeveloped land, and a completely uninhabited wilderness on an adjacent barrier island in the Cape Lookout National Seashore. Using an autonomous terrestrial rover, high resolution light measurements (mag/arcsec2) were collected every minute with two ambient light sensors along transects on each beach. Spatial comparisons between ambient light and nesting density at and between these locations reveal that highest densities of nests occur in regions with lowest light levels, supporting the hypothesis that light pollution from coastal development may influence turtle nesting distribution. These results can be used to support ongoing management strategies to mitigate this pressing conservation issue.  
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  Notes Approved no  
  Call Number IDA @ intern @ Serial 2315  
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Author Alessandro Manfrin, Gabriel Singer, Stefano Larsen, Nadine Weiss, Roy H. A. van Grunsven, Nina-Sophie Weiss, Stefanie Wohlfahrt, Michael T. Monaghan and Franz Hölker url  doi
openurl 
  Title Artificial light at night affects organism flux across ecosystem boundaries and drives community structure in the recipient ecosystem Type Journal Article
  Year 2017 Publication Frontiers in Environmental Science Abbreviated Journal  
  Volume 5 Issue 61 Pages  
  Keywords Animals; Ecology  
  Abstract Artificial light at night (ALAN) is a widespread alteration of the natural environment that can affect the functioning of ecosystems. ALAN can change the movement patterns of freshwater animals that move into the adjacent riparian and terrestrial ecosystems, but the implications for local riparian consumers that rely on these subsidies are still unexplored. We conducted a two-year field experiment to quantify changes of freshwater-terrestrial linkages by installing streetlights in a previously light-native riparian area adjacent to an agricultural drainage ditch. We compared the abundance and community composition of emerging aquatic insects, flying insects, and ground-dwelling arthropods with an unlit control site. Comparisons were made within and between years using generalized least squares and a BACI design (Before-After Control-Impact). Aquatic insect emergence, the proportion of flying insects that were aquatic in origin, and the total abundance of flying insects all increased in the ALAN-illuminated area. The abundance of several night-active ground-dwelling predators (Pachygnatha clercki, Trochosa sp., Opiliones) increased under ALAN and their activity was extended into the day. Conversely, the abundance of nocturnal ground beetles (Carabidae) decreased under ALAN. The changes in composition of riparian predator and scavenger communities suggest that the increase in aquatic-to-terrestrial subsidy flux may cascade through the riparian food web. The work is among the first studies to experimentally manipulate ALAN using a large-scale field experiment, and provides evidence that ALAN can affect processes that link adjacent ecosystems. Given the large number of streetlights that are installed along shorelines of freshwater bodies throughout the globe, the effects could be widespread and represent an underestimated source of impairment for both aquatic and riparian systems.  
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  Call Number LoNNe @ kyba @ Serial 1746  
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Author Brauckhoff, M.; Wahlberg, M.; Haga, J.Å.R.; Karlsen, H.E.; Wilson, M. url  doi
openurl 
  Title Embracing Their Prey at That Dark Hour: Common Cuttlefish (Sepia officinalis) Can Hunt in Nighttime Light Conditions Type Journal Article
  Year 2020 Publication Frontiers in Physiology Abbreviated Journal Front. Physiol.  
  Volume 11 Issue Pages in press  
  Keywords Animals  
  Abstract Cuttlefish are highly efficient predators, which strongly rely on their anterior binocular visual field for hunting and prey capture. Their complex eyes possess adaptations for low light conditions. Recently, it was discovered that they display camouflaging behavior at night, perhaps to avoid detection by predators, or to increase their nighttime hunting success. This raises the question whether cuttlefish are capable of foraging during nighttime. In the present study, prey capture of the common cuttlefish (Sepiaofficinalis) was filmed with a high-speed video camera in different light conditions.Experiments were performed in daylight and with near-infrared light sources in two simulated nightlight conditions, as well as in darkness. The body of the common cuttlefish maintained a velocity of less than 0.1 m/s during prey capture, while the tentacles during the seizing phase reached velocities of up to 2.5 m/s and accelerations reached more than 450 m/s2 for single individuals. There was no significant difference between the day and nighttime trials, respectively. In complete darkness, the common cuttlefish was unable to catch any prey. Our results show that the common cuttlefish are capable of catching prey during day- and nighttime light conditions. The common cuttlefish employ similar sensory motor systems and prey capturing techniques during both day- and nighttime conditions.  
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  Series Volume Series Issue Edition  
  ISSN 1664-042X ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 3021  
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