The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLIII-B5-2022
02 Jun 2022
 | 02 Jun 2022


F. Pirotti, M. Piragnolo, M. Yoshimura, J. P. Hernandez, M. A. Brovelli, B. Leblon, and M. Yamashita

Keywords: crowdsourcing, data sharing, open data, geographic information systems, webGIS

Abstract. The 2021 Scientific Initiatives in ISPRS funded this project called ISRS-SHY from “SHare mY ground truth”. It was intended as a collector of geographic data to support image analysis by sharing the necessary ground truth data needed for rigorous analysis. Regression and classification tasks that use remote sensing imagery necessarily require some control on the ground. The rationale behind this project is that often data on the ground is collected during projects, but is not valued by sharing across projects and teams globally. Internet has improved the way that data are shared, but there are still limitations related to discoverability of the data and its integrity. In other words, data are usually kept in local storage or, if in an accessible server, they are not documented and therefore they will not be picked up during search. In this initiative we created a portal using the Geonode environment to provide a hub for sharing data between research groups and openly to the community. The portal was then tested within the framework of three projects, with several participants each. The data that was uploaded and shared covered all types of geographic data formats and sizes. Further sharing was done in the context of teaching activities in higher education.

The results show the importance of creating easy means to find data and share it across stakeholders. Qualitative results are discussed, and future steps will focus on quantitative assessment of the portal’s usage, e.g. number of registered users in time, number of visits, and other key performance indicators. The results of this project are to be considered also in light of the effort in the scientific community to make research data available, i.e. FAIR - Findability, Accessibility, Interoperability, and Reuse of digital assets.