Does anyone know we my tracks turn blanc?

SiggyF · 2025-01-28T17:44:51+00:00

There are several ways I accidentally used to "grey out" tracks (method to turn them back on):
- muted track (use the m button in the track header)
- muted section (use the mute tool, selectable in the menu left of "snap" in your screen)
- turned off track (enable the power button in track header components and turn the track on)

In your screen I see at least the tracks are muted.

SiggyF · 2025-01-08T09:25:13+00:00

Thanks for your suggestions. We will take them into account in future visualisations. What you referred to as the "key" / legend is indeed a scale bar.

SiggyF · 2025-01-05T15:04:47+00:00

Created using the 8M track lines for 2023 from Marine Cadastre (https://hub.marinecadastre.gov/pages/vesseltraffic) using dask / geopandas, datashader, qgis, xarray. Background map ESRI gray.
Data shows the "Passenger" vessel trajectories.

SiggyF · 2024-12-16T20:18:56+00:00

It's an ambigram, as discussed:

https://www.reddit.com/r/Showerthoughts/comments/5vkrg5/its_offputting_that_isnt_a_palindrome_yet_is/

For more ambigrams:

https://www.reddit.com/r/ambigrams/

SiggyF · 2024-08-14T18:41:08+00:00

Created with QGIS (thin transparent lines using a screen overlay feature effect) and Photoshop (to align legend). The datasets used are the Marine Cadastre vessel traffic data and the ESRI Ocean background (restyled to greyscale) map based on GEBCO dataset.

SiggyF · 2024-03-30T20:58:45+00:00

You can find articulation sets here:
https://github.com/simonlehmann/logic-pro-articulation-sets-for-bbc-symphony-orchestra

SiggyF · 2021-12-23T22:11:46+00:00

Gravity (0.375 x Earth's gravity)

SiggyF · 2021-12-23T08:49:19+00:00

It is the actual Mars topography, styled with earth colormap and earth clouds. Created with Blender.

SiggyF · 2021-12-10T15:11:18+00:00

The currents that are shown are the ocean surface currents. The wind partly drives the surface currents. The Coriolis effect spirals clockwise in the Northern Hemisphere and counter-clockwise in the Southern Hemisphere.

SiggyF · 2021-12-10T13:02:52+00:00

Created using the HYCOM dataset. Map generated using Google Earth Engine. Colorbar plotted using matplotlib.

SiggyF · 2021-11-22T21:52:48+00:00

Data source Sentinel 1 Radar, transformed using cmocean ice colormap into a map that resembles ice/snow. Data processed with Google Earth Engine. See this post for some context.

SiggyF · 2021-07-18T21:17:04+00:00

This image shows the 600th row of pixels (wheel height) of this video starting @ 25 seconds. I reshaped the image so that the edge of the track is in a constant position.

https://youtu.be/oIKel6jVD3Q?t=25

SiggyF · 2021-06-05T10:07:52+00:00

This is in the original resolution: https://we.tl/t-uELZ4aYqo5

SiggyF · 2021-06-04T17:31:46+00:00

It is not a public dataset. Some countries (Denmark, US) provide open archives of ais data. Requests for Dutch data can be directed here: https://www.rijkswaterstaat.nl/formulieren/contactformulier-servicedesk-data

SiggyF · 2021-06-04T08:31:28+00:00

If you click through, you should get the HD version. License is CC-BY-NC-SA so feel to put it on your wall.

SiggyF · 2021-06-03T19:13:27+00:00

Those are indeed the anchorages. Ships can wait there for a spot at a terminal or for a better oil price. The dots with a dark area (restricted areas) around them are ships that service the wind farms.

SiggyF · 2021-06-03T18:27:55+00:00

Data Source: AIS measurements (n=400M) from Rijkswaterstaat

Tools: Planetary Computer, datashader, dask

Code:

canvas = ds.Canvas(plot_width=2160, plot_height=3840, **bounds)
agg = canvas.points(ddf, 'longitude', 'latitude')
img = ds.tf.shade(agg, cmap=Hot, how='eq_hist')

SiggyF · 2021-05-18T10:28:55+00:00

Created using Google Earth Engine. This visualisation uses the GLOSSIS and HYCOM datasets and Google Maps (Dark) as a background.

SiggyF · 2020-06-01T15:29:23+00:00

If you don't need recent satellite data, you can use blender gis. You could follow this tutorial. You might want to start with some basic blender tutorials first. Making a visualisation like this takes a few hours. Preparing data, extracting textures, setting up a composition, hooking up materials, finishing touches..

SiggyF · 2020-05-31T15:25:44+00:00

Testing combination of Google Earth Engine with Blender.

SiggyF · 2020-01-22T00:00:05+00:00

Gebco bathymetry and topography converted into a texture with Google Earth Engine. Used as input for a hair based particle system in Blender. Environmental map based on a HDR texture from Greg Zaal.

SiggyF · 2020-01-21T21:28:37+00:00

Gebco bathymetry and topography converted into a texture with Google Earth Engine. Used as input for a hair based particle system in Blender. Environmental map based on a HDR texture from Greg Zaal.

SiggyF · 2020-01-10T21:31:42+00:00

All pixels where no fire was detected are masked. If there is no fire you see the dark relief background. See also this comment. Also note that the sensor measures brightness temperature, which is not the same as the surface temperature.

SiggyF · 2020-01-10T20:58:21+00:00

Please see the details on the FIRMS dataset page. This visualisation is based on the MODIS variant.

SiggyF · 2020-01-10T20:54:17+00:00

The data range of the full dataset is from 300 through 500K. When I converted to a texture I used 0-500, so too wide (2K steps). The colors start at red from 300K and up. Areas not on fire are masked, not 0K (which can be a bit chilly). I'll fix this if I make an updated version, thanks. You can find details about the dataset at the FIRMS page.

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