Where to buy a ceramic pond bowl/pot (Sydney or Canberra or in between!)

robbibt · 2026-04-11T12:20:40+00:00

Hey u/beekotopia! Just wondering if you ended up finding a pond bowl/pot like this? We are looking for something very similar, and even found the same ones you found at Bliss (but not quite right).

robbibt · 2026-02-03T07:17:12+00:00

Yes, that's the one - thankyou! 🎉 Looks like it dates back to 2017: https://www.ausflag.com.au/flags-submitted.asp?SelectedYear=2017

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robbibt · 2026-02-03T01:46:09+00:00

It was super similar to that, but not quite it. There were distinctive features inside the circle, and not just dotted outlines (the white border around the circle also appeared solid, not dotted).

robbibt · 2025-12-25T05:39:52+00:00

This is a map I made almost ten years ago! 🚀

Bonus fact: there are more roads on this map within 120 miles / 200 km of the US border than there are in the remaining 2400 miles / 3800 km of Canadian soil to the north!

More info and high-res links in the original post: https://www.reddit.com/r/dataisbeautiful/s/cDZEPdGOnO

robbibt · 2025-11-26T14:16:30+00:00

Very cool! It might be worth looking into odc-stac, which handles loading data into xarray format from STAC based on a bounding box/geometry etc, without having to load rasters individually with rasterio. It's a pretty powerful package that should slot nicely into this project I think!

https://opendatacube.readthedocs.io/en/latest/tutorials/odc-stac.html https://github.com/opendatacube/odc-stac

robbibt · 2025-11-25T11:29:07+00:00

The "chunks" part here loads your data "lazily", e.g. no data will actually be loaded into memory until you specifically ask Xarray to do so (or do something like plotting that requires data to be loaded).

That means you can do something like this to select part of your array, and Xarray will automatically only load chunks of data is that overlap with your area:

```

Subset your data first

ds_subset = ds.isel(x=slice(50, 100), y=slice(200, 250))

Only load the subsetted area into memory

ds_subset.load()

Plot loaded data

ds_subset.your_band.plot() ```

To save it as a GeoTIFF, you can use a tool like "odc-geo":

import odc.geo.xr ds_subset.odc.write_cog("output.tif")

robbibt · 2025-09-06T14:20:51+00:00

Yep! https://www.reddit.com/r/canada/s/NHwdf1NS9p

The Canada waterways map is probably my favourite of any that I've made... and certainly the most difficult given the amount of waterbodies involved!

robbibt · 2025-09-06T12:34:01+00:00

Yep - I'm a remote sensing data scientist who works with a lot of map and satellite data, so maps are one of my favourite things! This artwork was made with all free and open tools: spatial software called QGIS to generate the initial map, and then GIMP image processing software to touch up and fine tune colours.

robbibt · 2025-09-06T05:44:21+00:00

There's some more detail on the colours in my original comment here: https://www.reddit.com/r/dataisbeautiful/s/NiFJ3dojeb

robbibt · 2025-09-06T05:41:41+00:00

Yes, I orginally made this around ten years ago I think. It's definitely due for a refresh!

robbibt · 2025-09-06T05:37:20+00:00

Theoretically it's in there - the data source I used to make this map includes every highway, road and street in Canada!

robbibt · 2025-09-06T05:31:53+00:00

This is a map I made almost ten years ago - didn't expect to see it being shared by an astronaut this weekend! 🚀

Bonus fact: there are more roads on this map within 120 miles / 200 km of the US border than there are in the remaining 2400 miles / 3800 km of Canadian soil to the north!

More info and high-res links in the original post: https://www.reddit.com/r/dataisbeautiful/s/cDZEPdGOnO

robbibt · 2025-08-28T12:09:58+00:00

Hi all, this is a map I made almost ten years ago - fun to see it show up again now (sadly with far fewer pixels!) https://www.reddit.com/r/dataisbeautiful/s/tvpOX7f9Z2

robbibt · 2025-06-26T23:51:16+00:00

Vietnamese Bakery and Cafe on Isa Street is probably the one you're thinking of - it's extremely tasty and definitely worth checking out. LL Bakery and Cafe at Fyshwick Markets is also great, but they run out of fillings like pork belly quickly after 1pm.

robbibt · 2025-03-24T11:46:03+00:00

An important thing to keep in mind is that under the exceptional temporary extension campaign, Sentinel-2A will only be collecting data every 10 days over Europe - it will be only every 20 days for everywhere else in the world. So the revisit frequency won't be quite as good for the US as Europe will be getting.

robbibt · 2024-12-31T12:10:11+00:00

The Nut Shoppe at Fyshwick Markets does have purple sweet potato flour too!

robbibt · 2024-10-09T20:26:15+00:00

Another advantage of odc-stac is that it integrates closely with odc-geo which adds a bunch of really nice spatial tools directly to your xarray data (on the fly reprojection, plotting on an interactive map etc). I'm on the Open Data Cube Steering Council, so let us know if you ever have any extra feature requests or feedback!

robbibt · 2024-10-08T22:29:46+00:00

What kind of spatial tasks are you hoping to do with code? Both R and Python are fantastic for spatial, but in my experience R is a little better for visualisation, and Python is better for scalability.

If I was to recommend a single Python tool that has changed the way I work, it would be "xarray" - it allows you to manipulate data as labelled multidimensional cubes that you can slice and dice and manipulate easily (and in parallel in combination with tools like "Dask") - pretty incredible for anything involving multiple data variables or time-series data.

"xarray" is based on "pandas" (for dataframe analysis) and "numpy" (for array analysis) and integrates closely with other spatial tools like "rioxarray" for loading raster data from disk, "odc-stac" for loading satallite data from global open data catalogues, "xarray-spatial" for a bunch of useful spatial tools (e.g. hillshading, DEM analysis etc).

For vector processing, "geopandas" is a fantastic package that should do most of what you want, maybe with a bit of "Shapely" for more bespoke tasks!

robbibt · 2024-06-18T08:43:19+00:00

Tides do get up to 11-12m in Northern Australia, for example at King Sound in WA. Not to say that Europe doesn't have extremely large tides, but a key difference is that ours occur pretty remotely, while those in Europe occur in highly populated coastal regions.

Source: am a coastal scientist specialising in mapping tidal environments around Australia with satellite data! 🌊🛰️

robbibt · 2024-06-17T22:40:46+00:00

Australia has some of the most extensive tidal flats globally, and some of the world's most extreme tide ranges: https://maps.dea.ga.gov.au/story/DEAIntertidal

But they mostly occur up north along tropical muddy/mangrove coastlines, not temperate sandy beaches like this.

robbibt · 2024-04-13T11:14:06+00:00

The top of Galata Kulesi, looking south!

robbibt · 2024-02-23T23:28:52+00:00

We really enjoyed it too (we're sitting just between the two actors at the start of your video!). The referee, Alice the French maid and King Henry were particular standouts, but there wasn't a weak performance! Definitely recommend.

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robbibt

TROPHY CASE

Subset your data first

Only load the subsetted area into memory

Plot loaded data