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Spatial Analysis of Light Pollution Dynamics Around Bosscha Observatory and ITERA Lampung Astronomical Observatory Based on VIIRS-DNB Satellite Images H A Prastyo 1 , D Herdiwijaya 2 1 Master Program in Astronomy, Faculty of Mathematics and Natural Sciences, ITB, Bandung, Indonesia 2 Astronomy Research Group and Bosscha Observatory, Faculty of Mathematics and Natural Sciences, ITB, Bandung, Indonesia

Outlines Introduction Methodology Result and Discussion Conclusion References

Introduction Bosscha Observatory is one of the observatory in Indonesia that still actively conducting astronomical research since 1928. Bosscha Observatory was initially very suitable for observing astronomical objects because of its ideal night sky conditions. However, in the 1980s the quality of the night sky at Bosscha Observatory has decreased along with the development of urban areas around the observatory. Urban development correlates with the use of artificial outdoor light and causes light pollution. Light pollution is one form of pollution caused by excessive light outside the room released into the sky, causing an increase in brightness of the night sky and produces a light dome above the cities around the Bosscha Observatory

Introduction The problem of light pollution around the Bosscha Observatory is a spatial problem, so to overcome it, it is necessary to analyze the dynamics of light pollution spatially, one of them is by using VIIRS-DNB satellite imagery. As a comparison, a similar study was carried out around the ITERA Lampung Astronomical Observatory (OAIL).

Methodology The object of this research is light pollution around Bosscha Observatory and ITERA Lampung Astronomical Observatory with 20 km radius from the observatory. The data used in this study is VIIRS-DNB night time satellite imagery data in 2013-2017. The classification of light pollution levels is divided into 5 classes (very low, low, medium, high, and very high). The classification process from VIIRS-DNB night time satellite data uses two classification methods, unsupervised and supervised classification method. The unsupervised classification method used for mapping the level of light pollution around Bosscha Observatory and the supervised classification method for mapping the level of light pollution around ITERA Lampung Astronomical Observatory. VIIRS-DNB night time satellite imagery data in 2017, located in Western part of Java Island

Result and Discussion Light Pollution Map Around Bosscha Observatory (2013-2017)

Result and Discussion Area Changes in Each Class of Light Pollution Around Bosscha Observatory

Result and Discussion Years Class 1 Class 2 Class 3 Class 4 Class 5 2013 856.80 256.51 120.56 22.23 3.54 2014 859.07 168.59 148.37 67.21 16.85 2015 705.78 258.75 170.05 105.02 19.95 2016 836.71 190.74 164.29 59.45 8.52 2017 691.81 280.07 181.10 94.35 11.96 The Rate of Average Change Area (km 2 /years) -41.25 5.89 15.13 18.03 2.10 The Rate of Average Change Area Around Bosscha Observatory

Result and Discussion Light Pollution Map Around ITERA Lampung Astronomical Observatory (2013-2017)

Result and Discussion Area Changes in Each Class of Light Pollution Around ITERA Lampung Astronomical Observatory

Result and Discussion Years Class 1 Class 2 Class 3 Class 4 Class 5 2013 952.82 184.45 74.25 37.44 10.64 2014 806.02 320.19 81.27 38.72 13.4 2015 795.81 328.49 75.95 50.63 8.72 2016 705.23 421.46 75.31 46.59 11.01 2017 716.65 406.57 81.06 44.68 10.64 The Rate of Average Change Area (km 2 /years) -59.04 55.53 10.90 8.51 0.00 The Rate of Average Change Area Around ITERA Lampung Astronomical Observatory

Conclusion The level of light pollution for the very low and low class is mostly located in the northern region of Bosscha Observatory (270-90 degrees azimuth), while the level of light pollution for the medium, high, and very high class is mostly in the southern region of Bosscha Observatory (90-270 degrees azimuth). Agglomeration of light pollution around the Bosscha Observatory is strongly influenced by its geographical conditions. The northern region of Bosscha Observatory is a mountainous and hilly area, while the southern region of Bosscha Observatory is a basin area and is an urban area. The average change in area of each class shows that the very low class relatively decreased every year. This shows that the ITERA Lampung Astronomical Observatory area is still relatively ideal as an observatory location, but only for observing 150-360 degrees azimuth sky area. However, the development of the northeast area of the ITERA Lampung Astronomical Observatory needs to be monitored periodically, especially in the 0-150 degrees azimuth range. This is because the development of the area in the northeast of the ITERA Lampung Astronomical Observatory is predicted to grow further with the development of Bandar Lampung City. If the development of the region in the northeast is not controlled, then the possibility of the condition of the northeast sky at the ITERA Lampung Astronomical Observatory will experience a very significant increase in light pollution.

References Hu, Z. et al., (2018). Association between nighttime artificial light pollution and sea turtle nest density along Florida coast: A geospatial study using VIIRS remote sensing data. Environmental Pollution, 239 , 30-42. Wu, B., and Wong, H., (2012). Visualization and Analysis of Light Pollution: A Case Study in Hong Kong. ISPRS Annals of the Photogrametry , Remote Sensing and Spatial Information Sciences, (I-2) , 171-176. Aubé , M., and Roby, J., (2014). Sky Brightness Levels Before and After the Creation of the First International Dark Sky Reserve, Mont- Mégantic Observatory, Québec, Canada. Journal of Quantitative Spectroscopy & Radiative Transfer, 139 , 52–63. Pun, C. S. J. et al., (2014). Contributions of artificial lighting sources on light pollution in Hong Kong measured through a night sky brightness monitoring network. Journal of Quantitative Spectroscopy & Radiative Transfer, 139 , 90–108. Gallaway , T. et al., (2010). The economics of global light pollution. Ecological Economics, 69 , 658–665 Elsahragty , M., and Kim, J., (2015). Assessment and Strategies to Reduce Light Pollution using Geographic Information Systems. Procedia Engineering, 118 , 479-488. Duriscoe , D. M. et al., (2018). A simplified model of all-sky artificial sky glow derived from VIIRS Day/Night band data. Journal of Quantitative Spectroscopy & Radiative Transfer, 214 , 133–145. Cao, C., and Bai, Y., (2014). Quantitative Analysis of VIIRS DNB Nightlight Point Source for Light Power Estimation and Stability Monitoring. Remote Sensing, 6 , 11915-11935. Falchi, F. Et al ., (2016). The new world atlas of artificial night sky brightness. Science Advances, 2:e1600377 , 1-25. Mather P M and Tso B 2009 Classification Methods for Remotely Sensed Data CRC Press Boca Raton 2 54

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