Stephan Paukner :: syslog

Recently I took my first star trail images with my DSLR. There finally was no moon and clear sky, so I took my photo backpack and my tripod with me and drove at 2.00am a few kilometers outside the small town where we were staying that weekend. It was located in the Waldviertel (“Woodquarter”), a rather sparsely populated region at the north of Austria, and so I expected best conditions for taking pictures of a starry night. Indeed, the Milky Way was clearly visible. I pointed my camera northwards to capture the sky rotation, and although it was really dark, I was a little surprised that the trees silhouetted against the sky. And a long time exposure unveiled a faint orange glow at the horizon, although the next populated spot in that direction was a small village a few kilometers away.

This finally raised the question to me: How should I find the sparsest populated place within a certain radius? What data would I need to find that out? A set of coordinates of towns plus their number of inhabitants? Use that to compute an image and blur it? Or rather, is it possible to use data collected in the course of the light pollution issue?

By some research I was finally able to find

1. the darkest place near the Waldviertel and
2. the darkest place in Austria.

Recently I wondered why Google Earth stopped working on my 64-bit Debian machine when I upgraded Google’s app to version 4.3. It claimed to find no internet connection (“Error code: 29”), although everything was working fine before. The web finally unveiled the solution: The app needs the lib32nss-mdns package. Installed that, problem resolved!