Hacker News Reader

Comment by micro_cam | Hacker News Reader

Cool. I hope they do it separately for winter and summer so as to give an idea of typical snow/ice cover.

Author here.

We’re doing almost the opposite – as little non-permanent snow and ice as we can manage. The reason is simply that we want to make this as useful as possible as a general-purpose base layer, and people usually want to see spring/summer growth. It looks subjectively right even in regions where it’s only around for a minority of the year.

If you’re interested in seasonal dynamics, I recommend Blue Marble[0]. It’s really good work – we’re in touch with some of the people who made it, and they’re sharp folks. But it’s half the resolution that we’re aiming for, and has some areas of distracting interpolation artifacts. Our main goal is accuracy, but we’re also going for aesthetics in a way that Blue Marble wasn’t.

0. http://earthobservatory.nasa.gov/Features/BlueMarble/

Thanks for response.

I think what you are doing makes sense for most purposes and I look forward to seeing the final layers.

I'm especially interested in snow cover because of a side project of mine (hillmap.com) that is targeted at backcountry travelers (ski tourers, hikers etc...especially winter travelers since it does things like avalanche terrain analysis in a canvas overlay).

Blue marble is cool and there are some overlays from NOAA etc but winter satellite photos good enough to answer questions like "is this typically an open snow field or heinous bushwhack" or "does this lake freeze over" would be really useful for planing trips in winter or colder climates.

If you guys (or someone) hosted the daily datasets it would be possible to do the processing client side in a canvas for a user defined time periods which would be an awesome tool.

Hmm. I don’t know of any specific product that does what you need (high resolution and near-realtime is usually an expensive combination), but I would definitely look through the National Snow and Ice Data Center’s projects: http://nsidc.org

Hillmap.com is a very cool project. Thanks for sharing.

This was what I was curious about -- let's say, as you work your way up a mountain, the bottom never has snow, the middle has snow 50% of the time, and the top has snow 100% of the time.

How do you decide where the border is? You're going to have a snow cap of some size -- what size is it, and how do you get to look both realistic, and consistent-looking, without artificial-looking borders?

I do like your idea of it being summer everywhere, though, hemisphere be damned! :)

In the current draft, exactly 81.7%. No kidding.

In the article you say you took the pixels without clouds. Just looking at how white it is, or something more complex?

This is too interesting a topic to get into right now – I’ll have to do another blog post or something. For now I’ll say: looking at whiteness alone gets you like 80% of the way there. It’s kind of amazing how effective it is by itself.

I suspect you could also factor in the variance between data samples. If a pixel is occasionally lighter in shade, you can assume that the lighter samples are due to cloud cover.

One possible naive approach could be to simply dispose of the lightest 90% of samples and average the remainder. You could reduce noise by blurring the pixels before applying statistical sampling.

looks amazing !

Will this be open-sourced one day ? Or maybe integrated into TileMill ?

Reply on news.ycombinator.com