In Swiss-Style Relief shading, the light comes from North West, which is impossible in the northern hemisphere. This makes sunny south facing slopes shaded and shaded north facing slopes light. Legend says that this was an intentional design decision, because right handed people usually have their desk lighting on the top left of their desk, giving the map a 3D like appearance. Here's an article on the topic (german…
Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning
41–50 of 77 posts
Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning
#42In Swiss-Style Relief shading, the light comes from North West, which is impossible in the northern hemisphere. This makes sunny south facing slopes shaded and shaded north facing slopes light. Legend says that this was an intentional design decision, because right handed people usually have their desk lighting on the top left of their desk, giving the map a 3D like appearance. Here's an article on the topic (german…
Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning
#43In Swiss-Style Relief shading, the light comes from North West, which is impossible in the northern hemisphere. This makes sunny south facing slopes shaded and shaded north facing slopes light. Legend says that this was an intentional design decision, because right handed people usually have their desk lighting on the top left of their desk, giving the map a 3D like appearance. Here's an article on the topic (german…
> In Swiss-Style Relief shading, the light comes from North West I would rather say it comes from the top-left. If you orient your map with the south upwards, it will look ok, as if the relief was shaded in the morning.
Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning
#44In Swiss-Style Relief shading, the light comes from North West, which is impossible in the northern hemisphere. This makes sunny south facing slopes shaded and shaded north facing slopes light. Legend says that this was an intentional design decision, because right handed people usually have their desk lighting on the top left of their desk, giving the map a 3D like appearance. Here's an article on the topic (german…
Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning
#45In Swiss-Style Relief shading, the light comes from North West, which is impossible in the northern hemisphere. This makes sunny south facing slopes shaded and shaded north facing slopes light. Legend says that this was an intentional design decision, because right handed people usually have their desk lighting on the top left of their desk, giving the map a 3D like appearance. Here's an article on the topic (german…
Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning
#46Earlier quoted context omitted.
> In Swiss-Style Relief shading, the light comes from North West I would rather say it comes from the top-left. If you orient your map with the south upwards, it will look ok, as if the relief was shaded in the morning.
well, no, the light source would still come from the north-west.
A more universal solution is to orient your maps with east up (which is a common convention), and light them from wherever the sun is. Then the morning light in the rendered maps will always come from the top (in the equator), top-right (northern hemisphere) and top-left (southern hemisphere).
Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning
#47In Swiss-Style Relief shading, the light comes from North West, which is impossible in the northern hemisphere. This makes sunny south facing slopes shaded and shaded north facing slopes light. Legend says that this was an intentional design decision, because right handed people usually have their desk lighting on the top left of their desk, giving the map a 3D like appearance. Here's an article on the topic (german…
that is technically not correct, in the summer for sufficiently high latitudes, the sun sets in the northwest.
Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning
#48I'm facing the issue on how to aesthetically visualize my hiking and skiing GPS tracks in mountainous terrain (similar to the OP, I live in Switzerland, so it's either up or down). I've decided to go directly the 3D route using Babylon.js, see here for an example: https://cubetrek.com/view/6338 Within Switzerland, it also uses Swiss-style maps as texture, outside of Switzerland a visually similar map style. I'm looki…
Looks fun. I just tried to sign up, but the link I received by email redirected to http://localhost:8080
Seems to be some problem in redirecting to the "success page", your email should be verified in any case. I need to look into that.
Edit: seems to be some issue with my Nginx setup.
Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning
#49In Swiss-Style Relief shading, the light comes from North West, which is impossible in the northern hemisphere. This makes sunny south facing slopes shaded and shaded north facing slopes light. Legend says that this was an intentional design decision, because right handed people usually have their desk lighting on the top left of their desk, giving the map a 3D like appearance. Here's an article on the topic (german…
> the light comes from North West, which is impossible in the northern hemisphere that is technically not correct, in the summer for sufficiently high latitudes, the sun sets in the northwest.
Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning
#50Earlier quoted context omitted.
> an art form Which is why the linked Daniel Huffman's technique employed the convincing results of Blender.
The biggest thing that I'm seeing that Singh has over Huffman is the adjustable detail-preserving terrain smoothing. Detail-preserving blur algorithms don't generalize well. Application-specific NN solutions tend to excel at this problem, by having a model of what details are important vs incidental. I would like to see a combination of the two, with the terrain pre-processed before being used in Blender.
I'd say this is a context in which "the problem of Transparency" becomes evident: we would like to "see why", to come to learn a perfected deterministic algorithm from the implicit model that the NN developed.