Senior Research Scholar
Novel Data Ecosystems for Sustainability Research Group
Advancing Systems Analysis
BiographyLinda See is a senior research scholar in the Novel Data Ecosystems for Sustainability (NODES) Research Group of the IIASA Advancing Systems Analysis Program. Her research interests include artificial intelligence-based methods, geographic information systems (GIS), land cover, crowdsourcing, and citizen science. As part of the NODES group she works with the Geo-Wiki team on crowdsourcing of land cover data, quality assurance of crowdsourced data, and community building. In addition, she coordinated the Austrian ASAP-10 LACO-Wiki project, which is an online tool for the validation of land cover, and the Austrian-funded project ADAPT-UHI, which has developed strategies for climate change mitigation and adaptation in small to medium-sized cities in Austria. She was the IIASA lead of the European Space Agency funded CAMALIOT project and led a successful crowdsourcing campaign to collect satellite navigation data using a mobile app. She also supported the Horizon 2020-funded LandSense and WeObserve projects. She is currently the work package lead in the Horizon Europe Land Management for Sustainability (LAMASUS) project (2022-2026) and supports the Urban ReLeaf project (2023-2026), both of which are led by IIASA. She is an editor of the journal Environment and Planning B: Urban Analytics and City Science.
See has a PhD in spatial applications of fuzzy logic from the School of Geography at the University of Leeds in the UK, where she taught for more than a decade as a senior lecturer in Computational Geography and GIS. She has MSc and BSc degrees in physical geography and environmental management from McMaster University and the University of Toronto in Canada. In between her MSc and PhD, she spent one year working at the Max Planck Institute for Atmospheric Sciences near Goettingen, Germany, followed by four years at the Food and Agriculture Organization (FAO) of the United Nations in Rome, Italy, where she worked on agrometeorology and early warning for food security.
Last update: 19 JAN 2023
Shvidenko, A., Mukhortova, L., Kapitsa, E., Kraxner, F., See, L. , Pyzhev, A., Gordeev, R., Fedorov, S., Korotkov, V., Bartalev, S., & Shchepashchenko, D. (2022). A Modelling System for Dead Wood Assessment in the Forests of Northern Eurasia. Forests 14 (1) p. 45. 10.3390/f14010045.
See, L. , Sturn, T., Karanam, S., Subash, A., McCallum, I. , & Fritz, S. (2022). Combining a rapid image classification app with artificial intelligence through the Picture Pile Platform for citizen science. In: ECSA Conference, 5-8 October 2022, Berlin.
Fritz, S. , See, L. , & Grey, F. (2022). The grand challenges facing environmental citizen science. Frontiers in Environmental Science 10 e1019628. 10.3389/fenvs.2022.1019628.
Hadi, H., Yowargana, P., Zulkarnain, M.T., Mohamad, F., Goib, B.K., Hultera, P., Sturn, T., Karner, M., Dürauer, M., See, L. , Fritz, S. , Hendriatna, A., Nursafingi, Afi, Melati, D.N., Prasetya, F.V.A.S., Carolita, I., Kiswanto, Firdaus, M.I., Rosidi, M., & Kraxner, F. (2022). A national-scale land cover reference dataset from local crowdsourcing initiatives in Indonesia. Scientific Data 9 (1) 10.1038/s41597-022-01689-5.
Proden, E., Bett, K., Chen, H., Duerto Valero, S., Fraisl, D. , Gamez, G., MacFeely, S., Mondardini, R., See, L. , & Min, Y. (2022). Citizen science data to track SDG progress: Low-hanging fruit for Governments and National Statistical Offices. Crowd4SDG, Policy Brief, July 2022