The C4C project aims at developing an Austrian citizen science (CS) data component to bridge the in-situ data gap for more reliable forest mapping with Copernicus data. Whereas forest inventory data can be used to calibrate satellite data, they are not openly available in many countries and do not have a high sampling density. Furthermore, modern machine learning-based mapping with big Copernicus data is extremely in-situ data-hungry, requiring novel solutions for building big in-situ data components. This project will engage citizens in monitoring forest state and change by collecting images with their phones, utilizing modern 3D vision and AI techniques for 3D forest information extraction and forest mapping with Sentinel-1 and -2 images. IIASA will utilize its experience in engaging with citizens and extend its crowdsource mobile data collection to handle stereo-like images. The CS images will be streamed to a backend for forest information extraction using novel 3D vision approaches. Several permanent plots will be established along the gradient of forest disturbances for repeated CS image collection campaigns. Those plots will be the base for evaluating the CS in-situ data quality and later for supervised learning of satellite images in the forest resource mapping task.

The potential of combining CS and Sentinel images will be demonstrated through a use case focusing on forest biomass mapping where one of the project partners, the Tree.ly GmbH company, will be involved as the end user. Another use case will be developed together with BFW to understand how CS data, in combination with Sentinel-2 images, can contribute to their existing workflows for tree species mapping. The last (third) use case will focus on assessing the biomass of trees outside the forest and understanding how CS data and Sentinel images can complement and contribute to the land cover and land cover change forests reporting at Umveltbundesamt GmbH.

The C4C project will have a solid social component by increasing the understanding of citizens about the benefits of the Copernicus data and by demonstrating, in return, how citizen science can provide more reliable forest mapping with Copernicus satellite images and contribute to climate neutrality. Finally, the Austrian CS data component will serve as the permanent source for training and validation of current and future Copernicus satellite data, setting standards for developing the European and global Copernicus CS in-situ data components.