Solar PV mapping is closely related to our PV forecasting project. Forecasting will provide solar PV yield predictions for a given location. To accurately forecast solar power generation for entire geographical regions, we need to locate all the PV panels in that area.
The OpenStreetMap (OSM) community has already done an incredible job mapping over 100,000 PV installations in the UK (out of over 1 million we believed to exist in the UK) and many more across the world. Our goal is to help grow the effort and drastically increase the amount of PV mapped in OSM.
Recent research (DeepSolar and SolarMapper from DUKE are just two examples) has shown the power of machine learning (ML) for identifying PV panels in satellite and aerial imagery at scale. We want to help pull together the datasets that are generated into a global open database which can be used for updating OSM.
By helping to create a comprehensive open database of PV installations, we think that other groups will find interesting ways to use the data.
Map PV installations manually from street level or satellite imagery directly in OSM.
Find more details on the OSM wiki.
We are a successful applicant to the Google.org Impact Challenge on Climate. The Google.org Impact Challenge on Climate commits €10M to fund bold ideas that aim to use technology to accelerate Europe’s progress toward a greener, more resilient future. Selected organisations may receive up to €2M in funding and possible customised post-grant support from the Google for Startups Accelerator to help bring their ideas to life.
ESA Business Applications awarded us an AI Kick-Start co-funding for six months. Kick-Start activities are compact Feasibility Studies to explore new service concepts that use space tech. We asked potential users of forecasting what they need; and how best to serve those needs.