General Astronomy > Light Pollution Topics

New Light Pollution Atlas w/o Snow Cover

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chionewssesu:
I'm sure most of us have used the World Atlas of the Artificial Night Sky Brightness to help us gauge the quality of our skies and to help locate new sites for observing. This atlas is based on Defense Meteorological Satellite Program (DMSP) satellite measurements of light sources on the earth's surface and a model of how these light sources affect the amount of light scattered downward to an observer's eyes (see here for more detail). While the maps are imperfect, they are nevertheless an excellent resource for finding dark skies, particularly for gauging the <em class="bbc">relative brightness of sites.This post concerns the possible effect of snow cover on this light pollution atlas. The idea is not new--the authors of the atlas themselves have pointed out the potential impacts of snow cover, as has Tony Flanders in his blog. The satellite measurements used to make the sky atlas were taken in the following three time periods:1. March 16-23 1996, 2. January 5-14 1997, 3. February 3-12 1997 (from Elvidge,C.D., Baugh, K.E., Dietz, J.B., Bland, T., Sutton, P.C., Kroehl, H.W. 1999. Radiance Calibration of DMSP-OLS Low-light Imaging Data of Human Settlements. Remote Sensing of Environment 68(1), pp. 77-88.)Snow cover data is available from the National Snow and Ice Data Center (NSIDC) on a weekly basis here. The three weeks that correspond most closely to the three time periods above are:1. March 18-24 1996, 2. January 6-12 1997, 3. February 3-9 1997The attached figure shows the number of weeks with snow cover on the ground from the NSIDC data. 100% means that all three weeks had snow cover, 67% means 2 out of three weeks had snow cover, etc. As you can see, much of the northern third of the US had snow cover during the entire period when the light data was taken. This snow cover will dramatically increase the amount of light sensed by the satellite and will thus make the light pollution atlas brighter than it would otherwise be. How much of an effect does snow cover have on the atlas? It turns out there is additional DMSP satellite data taken from September - November 2001. Except for a relatively small amount of snow centered over northern Wyoming and western South Dakota during the November new moon, this entire period was snow free. (This new data is only available online for the lower 48 states, unfortunately.) In the posts below, I calculate a new light pollution atlas using this 2001 data. First, I try to re-calculate the current atlas with the original 1996/1997 data to make sure the new atlas is a fair comparison.

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notaslasof:
Here I briefly describe where I obtained the data/model to re-calculate the night sky atlas and how my re-calculated version compares with the original atlas:The "radiance-calibrated" DMSP satellite data for 1996/1997 are available online here. This DMSP data is special because it includes some observations taken when the satellite's gain setting is reduced so that urban cores are not saturated.

The light pollution model used by Cinzano et al was derived by Roy Garstang in the following two articles:

-Garstang, RH: Model for artificial night-sky illumination, Publications of the Astronomical Society of the Pacific, 98 (601): 364-375, Mar 1986
-Garstang, RH: Night-sky brightness at observatories and sites, Publications of the Astronomical Society of the Pacific, 101 (637): 306-329, Mar 1989

I programmed the Garstang model myself using the parameters given in another Cinzano paper.A comparison of the original atlas (top) with the atlas re-calculated by me (bottom) is shown in the attached figure. A higher resolution version of my figure can be found here and a higher resolution version of Cinzano's atlas is here. There's very good agreement between the two, but if you look closely you can see differences. I've looked over my code many times and I do not think I made an error. I give some possible reasons for the discrepancy here. Anyway, the differences in these plots are well within the uncertainties involving the assumptions of the model.

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John Daniels:
The new radiance calibrated satellite data is available here. Like the 1996/1997 data, this data also includes some observations taken when the satellite's gain setting is reduced so that urban cores are not saturated. This data is only available on a map projection that includes the lower 48 states and some surrounding areas (for example, areas in south-central Canada are included but Vancouver, B.C. is cut off).I used the same model in the previous post to calculate a new Atlas of Artificial Night Sky Brightness for the lower 48 states (see attached). The atlas calculated using the original data is on top, while the new atlas calculated using data from Fall 2001 is on the bottom. (As before, higher resolution versions are available here.)Looking at the areas from Virginia south along the Atlantic Coast to Florida and then west along the Gulf coast, you see fairly good agreement in the light pollution derived from these two datasets. If you look in the northern US and Canada, on the other hand, the differences are dramatic. For example, in Minnesota, Wisconsin, Quebec and northern New England you tend to be a full light pollution "zone" darker in the 2001 data. In the 1996/1997 dataset, the only area black in the eastern US is a tiny area in the Boundary Waters Canoe Area in northern Minnesota. In the new dataset, this Minnesota region expands and new black regions appear in upper peninsula of Michigan and northern Maine. The black regions in Montana and Idaho are also much bigger. (You can't compare the maps in northwest Washington because Vancouver is not included in the Fall 2001 data.)

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Chad Shepard:
To better see the differences between the 1996/1997 and 2001 atlases, you could divide the brightness in 2001 by the brightness in 1996/1997. This plot is very noisy. Therefore I have smoothed the results before dividing (and also compare logarithms). The steps are:1) For each atlas, take the logarithm base 3 of the brightness values (except for the black/gray transition, the boundary between all color zones in the Cinzano Atlas is a power of three).2) Smooth the "maps" from (1) (I use a Gaussian kernel with a "standard deviation" of about 18 pixels).3) Subtract the 1996/1997 smoothed "map" from the 2001 smoothed "map".The resulting map is attached. Because I take the difference of log base 3, the maps given the change in light pollution "zone" in going from the 1996/1997 to the 2001 atlas. A value of -1 means that you are about one light pollution "zone" (or "color") darker in the 2001 atlas, while a value of +1 means that you are about one light pollution "zone" (or "color") brighter.As you can see, in Canada and in the northern part of the US, the 2001 map is about one "zone" darker than the 1996/1997 map. Across the southern portion of the US, there tends to be relatively little change in the light pollution "zone". The change in light pollution zone is broadly similar to the snow cover map I showed in the first post, which suggests that snow cover is playing an important role. The differences between the snow and change in zone could be due to any number of things: 1) increase in number of lights over 4-5 years, 2) More foliage on trees in Fall 2001 than Winter 1996 and 1997 (1 and 2 might tend to offset each other), 3) we do not know which of the three periods in 1996/1997 the DSMP satellite had a cloud free overpass (did the satellite 'miss' the week with snow or not?) 4) depth or age of snow (deep and/or new snow is more reflective than a dusting/old snow) 5) growth in natural gas production (for example, western and southwestern Wyoming), 6) inter-calibration issues with the satellites (see here). The last effect would have a uniform effect across the entire map, I believe. Therefore, it cannot account for the huge differences in space that we are seeing.So...Once again, the high resolution maps can be found here. If anyone wants the actual brightness data plotted on the maps, let me know. Thanks for reading and I hope you enjoy the new atlas!-Dave

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Marlon Hilzer:
Very, very interesting, important work.In addition to eliminating snow, you have produced two maps separated in time by 4 years, which may be enough to detect changes due to population and streetlight growth. Have you looked at it from that angle?It's also very helpful to have a map without boundaries overlaid. Most major population centers are on coasts, so the boundaries in Cinzano's released maps tend to blot out most of the interesting detail in places where many of us actually live.Is any data available after 2001?

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