Continued on my urban tree mapping kick from the last few months - it's continued to be a good way to stress test other projects of mine [3]. I've given it a new shiny landing page [1] so I can work on SEO a bit, I'll need to do a facelift on the data explorer to bring it in line stylistically.
I'm pivoting from adding more sources to data quality - as I've tried to vet some of the city sources I'm finding fun things (Cambridge, MA, USA merges in trees from Harvard, and some are straight duplicates with slight offsets, lots of places have trees in the middle of the road, many locations are address level instead of tree level). Now trying to leverage aerial photography to drive some QA, which has been a fun area to explore!
I'm pivoting from adding more sources to data quality - as I've tried to vet some of the city sources I'm finding fun things (Cambridge, MA, USA merges in trees from Harvard, and some are straight duplicates with slight offsets, lots of places have trees in the middle of the road, many locations are address level instead of tree level). Now trying to leverage aerial photography to drive some QA, which has been a fun area to explore!
[1]: https://arborary.world/ [2]: https://greenmtnboy.github.io/tree_reporting [3]: https://github.com/trilogy-data/pytrilogy