Global & Free Shadow Map: Need 3D buildings and complete tree data (Starting in Seville & Bollullos de la Mitación)

Help and support
, , , , ,
1

Hi everyone,

I am developing a shadow map project to help people find shade during heatwaves. The platform is completely free, open to everyone, and works globally. You can check it out here: manolitoaire.com

The web simulator reads data directly from OpenStreetMap. Although the tool can be used anywhere in the world, I am currently focusing on Seville and Bollullos de la Mitación (Spain), where we are still missing a lot of data.

We need help adding these elements with as much detail as possible:

  • Buildings: Adding the number of floors (building:levels) or height (height).
  • Trees (natural=tree): Please make it as complete as possible. If you know the tree type, please add the genus (genus), species (species), and its Wikipedia article (wikipedia).

If you want to help us test and map this area, or even start mapping your own hometown to use the tool there, you are more than welcome! Every single building and detailed tree added to OSM makes this global map perfect for everyone.

Thank you!

2

these almost always should go to taxon:wikipedia / species:wikipedia / genus:wikipedia (and linking wikidata is also popular, maybe more)

wikipedia= should be used only if article is specifically about given tree which is rare

3

Once you add wikipedia, wikidata comes automatically

4

That depends on the editor/plugins[1] used.

  1. where aplicable ↩︎

5

Hi Sandro. We can import the Spanish cadastre data, which includes building parts, giving you an accurate 3D building representation. You can view the import guide here ES:Catastro español/Importación de edificios - OpenStreetMap Wiki. However, the import must only be done by expert mappers, and it is very tedious. That is why only a small part of Spain has been imported so far.

6

Thank you so much for such a detailed response!

It would be wonderful if this integration could be automated in the future using a well-trained AI, which would greatly simplify the process and ease the workload for expert mappers.

:woman_dancing: