The impact of seasonal changes on observed nighttime brightness from 2014 to 2015 monthly VIIRS DNB composites

Remote Sensing of Environment

Volumn 193, Issue , 2017, Pages 150-164

  Levin, Noam ^a  

^a HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

Albedo; NDVI; Night lights; North America; Seasonality; Snow cover; Urban areas; VIIRS

Indexed keywords

LIGHT EMISSION; REMOTE SENSING; SNOW; SOLAR RADIATION;

ALBEDO; NDVI; NIGHT LIGHTS; NORTH AMERICA; SEASONALITY; SNOW COVERS; URBAN AREAS; VIIRS;

LUMINANCE;

ALBEDO; CORRELATION; DIURNAL VARIATION; LAND COVER; NDVI; OPTICAL INSTRUMENT; REMOTE SENSING; SEASONALITY; SENSOR; SNOW COVER; SPATIOTEMPORAL ANALYSIS; URBAN AREA; VIIRS; VISIBILITY;

CENTRAL AMERICA; NORTH AMERICA;

EID: 85015430243     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2017.03.003     Document Type: Article

References (71)

1. Akasofu, S.I., A study of auroral displays photographed from the DMSP-2 satellite and from the Alaska meridian chain of stations. Space Sci. Rev. 16:5–6 (1974), 617–725.
2. Akasofu, S.I., Auroral morphology: a historical account and major auroral features during auroral substorms. Auroral Phenomenology and Magnetospheric Processes: Earth and Other Planets, 2012, 29–38.
3. Aubrecht, C., León Torres, J.A., Evaluating multi-sensor nighttime earth observation data for identification of mixed vs. residential use in urban areas. Remote Sens., 8(2), 2016, 114.
4. Bennie, J., Davies, T.W., Duffy, J.P., Inger, R., Gaston, K.J., Contrasting trends in light pollution across Europe based on satellite observed night time lights. Sci. Rep., 4, 2014, 3789, 10.1038/srep03789.
5. Bennie, J., Duffy, J.P., Davies, T.W., Correa-Cano, M.E., Gaston, K.J., Global trends in exposure to light pollution in natural terrestrial ecosystems. Remote Sens. 7:3 (2015), 2715–2730.
6. Bhaduri, B., Bright, E., Coleman, P., Dobson, J., LandScan: locating people is what matters. Geoinformatics 5 (2002), 34–37.
7. Brest, C.L., Seasonal albedo of an urban/rural landscape from satellite observations. J. Clim. Appl. Meteorol. 26:9 (1987), 1169–1187.
8. Campbell, J.L., Mitchell, M.J., Groffman, P.M., Christenson, L.M., Hardy, J.P., Winter in northeastern North America: a critical period for ecological processes. Front. Ecol. Environ. 3:6 (2005), 314–322.
9. Carbary, J.F., A Kp-based model of auroral boundaries. Space Weather, 3(10), 2005, 10.1029/2005SW000162.
10. Chand, T.K., Badarinath, K.V.S., Elvidge, C.D., Tuttle, B.T., Spatial characterization of electrical power consumption patterns over India using temporal DMSP-OLS night-time satellite data. Int. J. Remote Sens. 30:3 (2009), 647–661.
11. Cinzano, P., Falchi, F., Elvidge, C.D., Baugh, K.E., The artificial night sky brightness mapped from DMSP satellite Operational Linescan System measurements. Mon. Not. R. Astron. Soc. 318:3 (2000), 641–657.
12. Croft, T.A., Nighttime images of the earth from space. Sci. Am. 239 (1978), 86–89.
13. Davies, T.W., Bennie, J., Inger, R., Gaston, K.J., Artificial light alters natural regimes of night-time sky brightness. Sci. Rep., 3, 2013, 1722, 10.1038/srep01722.
14. Didan, K., MOD13C2 MODIS/Terra Vegetation Indices Monthly L3 Global 0.05Deg CMG V006. NASA EOSDIS Land Processes DAAC. 2015, 10.5067/MODIS/MOD13C2.006.
15. Dobler, G., Ghandehari, M., Koonin, S.E., Nazari, R., Patrinos, A., Sharma, M.S.,.. Wurtele, J.S., Dynamics of the urban lightscape. Inf. Syst. 54 (2015), 115–126.
16. Doll, C.N.H., CIESIN Thematic Guide to Night-time Light Remote Sensing and Its Applications. 2008, Center for International Earth Science Information Network of Columbia University Available online at, Palisades, NY http://sedac.ciesin.columbia.edu/tg/.
17. Dye, D.G., Tucker, C.J., Seasonality and trends of snow-cover, vegetation index, and temperature in northern Eurasia. Geophys. Res. Lett. 30:7 (2003), 58-1–58-4.
18. Eastman, R.J., Sangermano, F., Ghimire, B., Zhu, H., Chen, H., Neeti, N.,.. Crema, S.C., Seasonal trend analysis of image time series. Int. J. Remote Sens. 30:10 (2009), 2721–2726.
19. Elvidge, C.D., Baugh, K.E., Kihn, E.A., Kroehl, H.W., Davis, E.R., Mapping city lights with nighttime data from the DMSP Operational Linescan System. Photogramm. Eng. Remote. Sens. 63:6 (1997), 727–734.
20. Elvidge, C.D., Baugh, K.E., Kihn, E.A., Kroehl, H.W., Davis, E.R., Davis, C.W., Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumption. Int. J. Remote Sens. 18:6 (1997), 1373–1379.
21. Elvidge, C.D., Imhoff, M.L., Baugh, K.E., Hobson, V.R., Nelson, I., Safran, J.,.. Tuttle, B.T., Night-time lights of the world: 1994–1995. ISPRS J. Photogramm. Remote Sens. 56:2 (2001), 81–99.
22. Elvidge, C.D., Baugh, K.E., Zhizhin, M., Hsu, F.C., Why VIIRS data are superior to DMSP for mapping nighttime lights. Proceedings of the Asia-Pacific Advanced Network, vol. 35, 2013, 62–69.
23. Falchi, F., Cinzano, P., Elvidge, C.D., Keith, D.M., Haim, A., Limiting the impact of light pollution on human health, environment and stellar visibility. J. Environ. Manag. 92:10 (2011), 2714–2722.
24. Falchi, F., Cinzano, P., Duriscoe, D., Kyba, C.C., Elvidge, C.D., Baugh, K.,.. Furgoni, R., The new world atlas of artificial night sky brightness. Sci. Adv., 2(6), 2016, e1600377.
25. Feldstein, Y.I., Vorobjev, V.G., Zverev, V.L., Förster, M., Investigations of the auroral luminosity distribution and the dynamics of discrete auroral forms in a historical retrospective. Hist. Geo Space Sci. 5:1 (2014), 81–134.
26. Fryberger, S.G., Dean, G., Dune Forms and Wind Regime. A Study of Global Sand Seas. vol. 1052, 1979, 137–169.
27. GSFC JPSS CMO, Joint Polar Satellite System (JPSS) VIIRS Imagery Products Algorithm Theoretical Basis Document (ATBD). (REF Y2466) (D43767 Rev B) CDRL No. A032. vol. 90278, 2014, Northrop Grumman Space & Mission Systems Corporation, One Space Park Redondo Beach, California.
28. Hall, D.K., Riggs, G.A., Accuracy assessment of the MODIS snow products. Hydrol. Process. 21:12 (2007), 1534–1547.
29. Hall, D.K., Riggs, G.A., Salomonson, V.V., MODIS/Terra Snow Cover Monthly L3 Global 0.05Deg CMG V005, [Jan 2014–Dec 2015]. 2006, National Snow and Ice Data Center. Digital media, Boulder, Colorado USA.
30. Homer, C.G., Dewitz, J.A., Yang, L., Jin, S., Danielson, P., Xian, G., Coulston, J., Herold, N.D., Wickham, J.D., Megown, K., Completion of the 2011 National Land Cover Database for the conterminous United States - representing a decade of land cover change information. Photogramm. Eng. Remote. Sens. 81 (2015), 345–354.
31. Imhoff, M.L., Zhang, P., Wolfe, R.E., Bounoua, L., Remote sensing of the urban heat island effect across biomes in the continental USA. Remote Sens. Environ. 114:3 (2010), 504–513.
32. Katz, Y., Levin, N., Quantifying urban light pollution—a comparison between field measurements and EROS-B imagery. Remote Sens. Environ. 177 (2016), 65–77.
33. Kohiyama, M., Hayashi, H., Maki, N., Higashida, M., Kroehl, H.W., Elvidge, C.D., Hobson, V.R., Early damaged area estimation system using DMSP-OLS night-time imagery. Int. J. Remote Sens. 25:11 (2004), 2015–2036.
34. Kyba, C.C., Ruhtz, T., Fischer, J., Hölker, F., Cloud coverage acts as an amplifier for ecological light pollution in urban ecosystems. PLoS One, 6(3), 2011, e17307.
35. Kyba, C.C.M., Ruhtz, T., Fischer, J., Hölker, F., Red is the new black: how the colour of urban skyglow varies with cloud cover. Mon. Not. R. Astron. Soc. 425:1 (2012), 701–708.
36. Lambin, E.F., Change detection at multiple temporal scales: seasonal and annual variations in landscape variables. Photogramm. Eng. Remote. Sens. 62:8 (1996), 931–938.
37. Lee, T.E., Miller, S.D., Turk, F.J., Schueler, C., The NPOESS VIIRS day/night visible sensor. Bull. Am. Meteorol. Soc., 87(2), 2006, 191.
38. Letu, H., Hara, M., Tana, G., Bao, Y., Nishio, F., Generating the nighttime light of the human settlements by identifying periodic components from DMSP/OLS satellite imagery. Environ. Sci. Technol. 49:17 (2015), 10503–10509.
39. Levin, N., Duke, Y., High spatial resolution night-time light images for demographic and socio-economic studies. Remote Sens. Environ. 119 (2012), 1–10.
40. Levin, N., Johansen, K., Hacker, J.M., Phinn, S., A new source for high spatial resolution night time images—The EROS-B commercial satellite. Remote Sens. Environ. 149 (2014), 1–12.
41. Levin, N., Zhang, Q., A global analysis of factors controlling VIIRS nighttime light levels from densely populated areas. Remote Sens. Environ. 190 (2017), 366–382.
42. Li, X., Li, D., Can night-time light images play a role in evaluating the Syrian Crisis?. Int. J. Remote Sens. 35:18 (2014), 6648–6661.
43. Li, X., Zhang, R., Huang, C., Li, D., Detecting 2014 northern Iraq insurgency using night-time light imagery. Int. J. Remote Sens. 36:13 (2015), 3446–3458.
44. Ljung, G.M., Box, G.E., On a measure of lack of fit in time series models. Biometrika 65:2 (1978), 297–303.
45. Longcore, T., Rich, C., Ecological light pollution. Front. Ecol. Environ. 2:4 (2004), 191–198.
46. Luginbuhl, C.B., Using DMSP night-time imagery to evaluate lighting practice in the American southwest. Preserving the Astronomical Sky, 196, 2001, 103–106.
47. Luginbuhl, C.B., Duriscoe, D.M., Moore, C.W., Richman, A., Lockwood, G.W., Davis, D.R., From the ground up II: Sky glow and near-ground artificial light propagation in Flagstaff, Arizona. Publ. Astron. Soc. Pac., 121(876), 2009, 204.
48. Ma, T., Zhou, C., Pei, T., Haynie, S., Fan, J., Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data: a comparative case study from China's cities. Remote Sens. Environ. 124 (2012), 99–107.
49. Miller, S.D., Straka, W., Mills, S.P., Elvidge, C.D., Lee, T.F., Solbrig, J.,.. Weiss, S.C., Illuminating the capabilities of the suomi national polar-orbiting partnership (NPP) visible infrared imaging radiometer suite (VIIRS) day/night band. Remote Sens. 5:12 (2013), 6717–6766.
50. Mills, S., Weiss, S., Liang, C., VIIRS day/night band (DNB) stray light characterization and correction. SPIE Optical Engineering + Applications, 2013, International Society for Optics and Photonics, 88661P.
51. Olson, D.M., Dinerstein, E., Wikramanayake, E.D., Burgess, N.D., Powell, G.V., Underwood, E.C.,.. Loucks, C.J., Terrestrial ecoregions of the world: a new map of life on earth a new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. Bioscience 51:11 (2001), 933–938.
52. Puschnig, J., Posch, T., Uttenthaler, S., Night sky photometry and spectroscopy performed at the Vienna University Observatory. J. Quant. Spectrosc. Radiat. Transf. 139 (2014), 64–75.
53. Quijano, M.G., De La Cruz, A., Mielewczyk, M., Cerra, D., Assessing Refugee Movement During the Israel–Lebanon Crisis of 2006 Using DMSP Imagery. Our Common Borders – Safety, Security, and the Environment Through Remote Sensing, October 28 – November 1, 2007. Ottawa, Ontario, Canada. 2007.
54. Rau, R., Seasonality in Human Mortality: A Demographic Approach. 2006, Springer Science & Business Media.
55. Rechid, D., Raddatz, T.J., Jacob, D., Parameterization of snow-free land surface albedo as a function of vegetation phenology based on MODIS data and applied in climate modelling. Theor. Appl. Climatol. 95:3–4 (2009), 245–255.
56. Riegel, K.W., Light pollution outdoor lighting is a growing threat to astronomy. Science 179:4080 (1973), 1285–1291.
57. Robinson, D.A., Kukla, G., Maximum surface albedo of seasonally snow-covered lands in the Northern Hemisphere. J. Clim. Appl. Meteorol. 24:5 (1985), 402–411.
58. Román, M.O., Stokes, E.C., Holidays in lights: tracking cultural patterns in demand for energy services. Earth's Future 3:6 (2015), 182–205.
59. Shi, K., Huang, C., Yu, B., Yin, B., Huang, Y., Wu, J., Evaluation of NPP-VIIRS night-time light composite data for extracting built-up urban areas. Remote Sens. Lett. 5:4 (2014), 358–366.
60. Shi, K., Yu, B., Huang, Y., Hu, Y., Yin, B., Chen, Z.,.. Wu, J., 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. Remote Sens. 6:2 (2014), 1705–1724.
61. Small, C., Multitemporal analysis of urban reflectance. Remote Sens. Environ. 81:2 (2002), 427–442.
62. Small, C., Pozzi, F., Elvidge, C.D., Spatial analysis of global urban extent from DMSP-OLS night lights. Remote Sens. Environ. 96:3 (2005), 277–291.
63. Sprague, G.C., Visual studies of the aurora. Sky and Telescope, 35, 1968, 346.
64. Verbesselt, J., Hyndman, R., Newnham, G., Culvenor, D., Detecting trend and seasonal changes in satellite image time series. Remote Sens. Environ. 114:1 (2010), 106–115.
65. Wei, Y., Liu, H., Song, W., Yu, B., Xiu, C., Normalization of time series DMSP-OLS nighttime light images for urban growth analysis with pseudo invariant features. Landsc. Urban Plan. 128 (2014), 1–13.
66. Witmer, F.D., O'Loughlin, J., Detecting the effects of wars in the Caucasus regions of Russia and Georgia using radiometrically normalized DMSP-OLS nighttime lights imagery. GIScience Remote Sens. 48:4 (2011), 478–500.
67. Wu, J., Wang, Z., Li, W., Peng, J., Exploring factors affecting the relationship between light consumption and GDP based on DMSP/OLS nighttime satellite imagery. Remote Sens. Environ. 134 (2013), 111–119.
68. Wu, J., He, S., Peng, J., Li, W., Zhong, X., Intercalibration of DMSP-OLS night-time light data by the invariant region method. Int. J. Remote Sens. 34:20 (2013), 7356–7368.
69. Zhao, N., Ghosh, T., Samson, E.L., Mapping spatio-temporal changes of Chinese electric power consumption using night-time imagery. Int. J. Remote Sens. 33:20 (2012), 6304–6320.
70. Zhang, Q., Seto, K.C., Mapping urbanization dynamics at regional and global scales using multi-temporal DMSP/OLS nighttime light data. Remote Sens. Environ. 115:9 (2011), 2320–2329.
71. Zhang, Q., Levin, N., Chalkias, C., Letu, H., Nighttime light remote sensing – monitoring human societies from outer space. Thenkabail, P.S., (eds.) Chapter 26 in Remote Sensing Handbook, vol. 3, 2015, Taylor and Francis, 289–310.