Linda See
Principal Research Scholar
Novel Data Ecosystems for Sustainability Research Group
Advancing Systems Analysis Program
Biography
Linda 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
Publications
Fritz, S. , See, Linda , Perger, C., McCallum, I. , Schill, C., Shchepashchenko, D. , Duerauer, M., Karner, M., Dresel, C., Laso Bayas, J.C. , Lesiv, M. , Moorthy, I., Salk, C., Danylo, O., Sturn, T., Albrecht, F., You, L., Kraxner, F., & Obersteiner, M. (2012). A global dataset of crowdsourced land cover and land use reference data (2011-2012).
Demetriou, D., Stillwell, J., & See, L. (2012). An integrated planning and decision support system (IPDSS) for land consolidation: Theoretical framework and application of the land-redistribution modules. Environment and Planning B: Planning and Design 39 (4) 609-628. 10.1068/b37075.
Schepaschenko, D. , Fritz, S. , McCallum, I. , Shvidenko, A., Perger, C., Schill, C., See, L. , Kraxner, F., & Obersteiner, M. (2012). A platform to visualize, analyze and improve biomass datasets: http://biomass.geo-wiki.org. Folia Forestalia Polonica, Series A - Forestry 54 (2) 137-139.
Fritz, S. , Fuss, S., Havlik, P. , Szolgayova, J., McCallum, I. , Obersteiner, M. , & See, L. (2012). The value of determining global land cover for assessing climate change mitigation options. In: The Value of Information: Methodological Frontiers and New Applications in Environment and Health. Eds. Laxminarayan, R & Macauley, MK, Dordrecht: Springer. 10.1007/978-94-007-4839-2_8.
Chaipimonplin, T., See, L. , & Kneale, P. (2011). Improving neural network for flood forecasting using radar data on the Upper Ping River. In: MODSIM 2011 - 19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty. pp. 1070-1076 Perth, WA; Australia. ISBN 978-098721431-7