For anyone who’s looking for an interesting challenge. Our non-profit research group openclimatefix.org is working to map solar PV globally using ML: http://jack-kelly.com/blog/2019-07-09-solar-pv-mapping
There are several groups mapping different areas. But there is lots of help needed to map small roof top solar panels. For example in the UK we have found access to 25cm aerial imagery, and in the USA there are a few groups doing this. There is also a global utility scale dataset being released soon.
But we haven’t got any other countries in progress! If you’d like to have a go at solar PV detection (mainly small roof top panels) using ML for a particular country, we invite you to.
The biggest hurdle is usually imagery. We’ve found Mapbox has high resolution global coverage, but for many countries the quality is too low. So it’s worth exploring domestic satellite and aerial imagery providers. Some may be open to giving access to data for educational or research purposes.
Please pay particular attention to imagery licensing. We want to be able to aggregate and freely distribute PV panel maps for research and impact climate change. This includes pushing results to OpenStreetMap. For example, results derived from Google Maps imagery cannot be openly distributed. But Mapbox explicitly states you can use their imagery to improve OpenStreetMap.
There is some great code to base your work on, such as:
http://web.stanford.edu/group/deepsolar/home
Using DeepSolar with Mapbox: http://openclimatefix.discourse.group/t/solarpaneldatawrangler/26
SolarMapper https://arxiv.org/pdf/1902.10895.pdf
I’d you’d like to chat just drop me a DM twitter.com/dctanner