4 ms·

It would be great if you could take a pic of a tree leaf, and i will capture the geoloc of the pic as well and plot where that tree is on the map - and start tr

by phlux 15y ago

It would be great if you could take a pic of a tree leaf, and i will capture the geoloc of the pic as well and plot where that tree is on the map - and start tracking where all types of trees live.

lsb 15y ago
Even greater to use hi-res satnav for that! We can assess water health that way, it'd be fascinating to do similarly for forests.
- phlux 15y ago
  Get kids/students to participate in snapping a pic of a leaf any opportunity they get to feed the data into the system. Reward them somehow. Ask one simple question with each pic take "How many trees of this type would you estimate are in your vacinity, that you can see" Map those trees all over and compare with climate/weather. The estimates just increase the size of the circle on the map that shows where those trees live. Eventually you'll get a very clear idea of what trees thrive/live where.
apu 15y ago
This is exactly what we are doing. We're working with botanists at the Smithsonian Institution in DC who are very interested in this kind of data.
- andrewgleave 15y ago
  Great app. Next week I'm releasing a project for the Isle of Man which crowdsources the recording of location and health of Elm trees (via iPhone and Android app). The Island is one of the very few locations in the UK which still have a healthy population but has recently suffered funding cuts meaning Gov. surveys are no longer being done, and hence the need for a public solution. If the app could recognise more species of elm (English and American seem to be there, but no Wych or Dutch for example), would be a valuable tool for users trying to contribute to the project. The source for the Django app and PhoneGap-based mobile app will be up on GitHub next week, and the data is publicly available via our CouchOne instance (http://redrobot.couchone.com/_utils/database.html?openelm http://redrobot.couchone.com/_utils/database.html?openelm) – the project isn't live yet so there's only a small amount of data.

by phlux 15y ago

It would be great if you could take a pic of a tree leaf, and i will capture the geoloc of the pic as well and plot where that tree is on the map - and start tracking where all types of trees live.

lsb 15y ago

Even greater to use hi-res satnav for that! We can assess water health that way, it'd be fascinating to do similarly for forests.

phlux 15y ago
Get kids/students to participate in snapping a pic of a leaf any opportunity they get to feed the data into the system. Reward them somehow. Ask one simple question with each pic take "How many trees of this type would you estimate are in your vacinity, that you can see" Map those trees all over and compare with climate/weather. The estimates just increase the size of the circle on the map that shows where those trees live. Eventually you'll get a very clear idea of what trees thrive/live where.

apu 15y ago

This is exactly what we are doing. We're working with botanists at the Smithsonian Institution in DC who are very interested in this kind of data.

andrewgleave 15y ago
Great app. Next week I'm releasing a project for the Isle of Man which crowdsources the recording of location and health of Elm trees (via iPhone and Android app). The Island is one of the very few locations in the UK which still have a healthy population but has recently suffered funding cuts meaning Gov. surveys are no longer being done, and hence the need for a public solution. If the app could recognise more species of elm (English and American seem to be there, but no Wych or Dutch for example), would be a valuable tool for users trying to contribute to the project. The source for the Django app and PhoneGap-based mobile app will be up on GitHub next week, and the data is publicly available via our CouchOne instance (http://redrobot.couchone.com/_utils/database.html?openelm http://redrobot.couchone.com/_utils/database.html?openelm) – the project isn't live yet so there's only a small amount of data.