Map enthusiast by day, archaeologist by night. Into teaching GIS, building geospatial data collections, doing landscape archaeology, exploring post-medieval Greece, and (of course) making maps.
Geospatial Information Librarian at UMass Amherst, Co-Director of the CARTography Project, and soon-to-be Co-Director of the Southern Mani Archaeological Project.
She/her.
#qgis2web announcement!
The qgis2web repository has moved. It is now no longer in my Github account, but under a new qgis2web organization. This should be largely transparent, but take care if you have a local clone - check your upstream repo.
https://github.com/qgis2web/qgis2web
Also, Andrea has released v3.17.1! https://github.com/qgis2web/qgis2web/releases/tag/v3.17.1
Going for an ascii art look. Jan Mayen, data from Norwegian Polar Institute. Done in :qgis:
Did a D8 flow pointer in #whiteboxtools. This quantizes downslope aspect to 8 directions
Create grid in #qgis. Sample the d8 raster and original dem. Style with 8 different SVG arrow markers rotated around center, using thicker arrows for SE-facing to simulate hillshade. Filter out all the points with 0 elevation to mask out the sea.
For teaching Coordinate Reference Systems in my GIS/cartography intro course, I made this simple app that can show the current GPS location in two different coordinate systems. It supports all CRS supported by Proj4JS (more than five thousand).
(Yes there is a ton of "coordinate converter" apps out there, but their UI is far too overloaded for my purposes.)
Source code is available at https://github.com/floledermann/coordinates
Introducing lonboard: the fastest way to visualize large geospatial vector data from Python.
Here's 3 million points rendered with a unique color and radius per point, in two seconds.
https://developmentseed.org/blog/2023-10-23-lonboard
https://ds.io/lonboard
One more week until the start of the #30DayMapChallenge 😍
This year I am diving for the first time into 3D maps, here is some work in progress.
Anyone else here already preparing and wants to share some work in progress? 😄
#gischat
Gaza Strip in maps by BBC: https://www.bbc.co.uk/news/world-middle-east-20415675
Always nice to see a focus on #GIS and maps. The 3D population density map is particularly interesting and slightly unusual.
I've seen a few instances of similar maps, and would assume it would need something extra on top of usual GIS programs e.g. Blender? Something that could be piped from #qgis?
#gischat
The themes for the upcoming #30DayMapChallenge 2023 have been published and… I will safely not do it this year 🙂.
Doing it in 2022 was an incredible experience (https://bbecquet.net/articles/2022/12/30-day-map-challenge/), but I mostly remember how exhausted I was at the end. This year I'm already doing some Inktober, I'm still making engraved maps on my own, I don't work in web cartography anymore, I have less free time… a lot of reasons to just sit and watch other people do great things. Good luck to all who will participate!
#30DayMapChallenge themes are here. Make (and publish) a map each day of November around a specific prompt. More info on GitHub and https://30daymapchallenge.com/
Make a map. Send it to me. If I like it, I'll print it and you'll get a commission if it sells.
The entire NW-facing side of the Mont Blanc massif (from Aiguille du Tour on the left to the Dômes de Miage on the right), seen from Prarion. #mountains #alps #frenchalps #chamonix #montblanc #glaciers #geology
Visualising the scale of the Solar System at human scale using #qgis, a map of #edinburgh copyright #openstreetmap contributors.
This map shows the scaled down orbits of Mercury, Venus, Earth and Mars.
Imagine the Earth is the size of a snooker ball, 5cm across. With the Sun just outside the Balmoral hotel, a 6m diameter ball of fire.
Imagine holding the Earth as a billiard ball in your hand. And walk briskly. At this scale, you're walking at the speed of light. 😮
@ianturton Whenever I'm helping a student with ArcGIS, if we have time at the end, I do like to add a quick "And here's how much more easily we could do the same thing in QGIS..."
@kgjenkins @ianturton 🤯 and here I was running <3.24 and missing out on all the good stuff!
@ianturton @kgjenkins ha, I usually default to QGIS, too… but in that case you might need to create a .csvt file instead.
TIL about rasterio, a #Python library for working with #rasters that's a lot easier to install than GDAL. Total gamechanger!
I needed to find out the CRS of a GeoTIFF that #ArcGIS wasn't reading correctly. It was a simple as running this code:
```
import rasterio as rs
dataset = rs.open(‘file.tif')
print(dataset.crs)
```
Documentation: https://rasterio.readthedocs.io/en/stable/
And shout-out to this article that pointed me to it: https://towardsdatascience.com/reading-and-visualizing-geotiff-images-with-python-8dcca7a74510
30 minutes isochrone, drawn from Montpellier City Hall.
(isochrone = geographical area drawn from the same travel distance from a source point)
From left to right:
- IGN / geoportail.gouv.fr
- OpenStreetMap / commutetimemap.com / geoapify.com
- Google Maps.
Not sure which one is better, pretty clear which one is worst.
Encountered this real treasure just now via HackerNews: https://www.fieggen.com/shoelace/ianknothistory.htm
EXIF image metadata has the craziest way to store lat/lon coordinates that I've ever seen... a sequence of 3 (degrees, minutes, seconds) values stored as rational64u numeric types
