FOSS4G Hiroshima 2026 is a chance for developers, researchers, practitioners, and users of free and open-source geospatial technologies to share knowledge, showcase new tools, and discuss how open geospatial solutions can help solve real-world problems. HeiGIT will take part with two talks by Danielle Gatland. The first will cover how deep learning and OpenStreetMap data can be used to detect rooftop solar panels. The second will look at mapping road surface type, width, and passability to support humanitarian logistics, infrastructure analysis, and climate resilience.
Talk: Detecting Rooftop Solar Panels with Deep Learning, using Open Remote Sensing Data and OpenStreetMap
Presenter: Danielle Gatland
How dependent is your town on the electricity grid? How many buildings are supplied by rooftop solar panels? How much unused potential is there to leverage the power of the sun?
We built a deep learning model using FOSS4G and open remote sensing data for Germany. With this model, you can detect which buildings have rooftop solar panels at a neighbourhood level. The input data is orthophotos and OpenStreetMap building footprints, which we feed into a 4-channel image classification model.
The results of the model are visualised in the Rooftop Solar assessment tool of the Climate Action Navigator (https://climate-action.heigit.org) from HeiGIT (https://heigit.org).
In this talk, we will demonstrate our results through our assessment tool. We will also explain the design of our model and how we used OpenStreetMap tagging to significantly speed up the creation of training data for our supervised learning approach.
Talk: Mapping the Changing Surface of the World’s Roads: Open-Source Geospatial Intelligence for Humanitarian Logistics and Climate Resilience
Presenter: Danielle Gatland
We introduce the first open, global dataset of road surface type, width, and passability, covering over 9 million km of roads using satellite and street-level imagery. Built with open-source GeoAI methods, it reveals links between infrastructure quality and development, identifies vulnerabilities in connectivity, and supports disaster logistics through a Humanitarian Passability Index. The dataset is openly available via the Humanitarian Data Exchange, enabling broad use for humanitarian response, infrastructure analysis, and sustainable development.