Linda See profile picture

Linda See

Principal Research Scholar

Novel Data Ecosystems for Sustainability Research Group

Advancing Systems Analysis


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


Bun, R., Marland, G., Oda, T., See, L. , Puliafito, E., Nahorski, Z., Jonas, M. , Kovalyshyn, V., Ialongo, I., Yashchun, O., & Romanchuk, Z. (2024). Tracking unaccounted greenhouse gas emissions due to the war in Ukraine since 2022. Science of the Total Environment 914 e169879. 10.1016/j.scitotenv.2024.169879.

See, L. (2024). The innovative role of cities in solving global problems with local solutions. Environment and Planning B: Urban Analytics and City Science 10.1177/23998083241227294.

Martinez-Sanchez, L., See, L. , Yordanov, M., Verhegghen, A., Elvekjaer, N., Muraro, D., d’Andrimont, R., & van der Velde, M. (2024). Automatic classification of land cover from LUCAS in-situ landscape photos using semantic segmentation and a Random Forest model. Environmental Modelling & Software 172 e105931. 10.1016/j.envsoft.2023.105931.

See, L. (2023). Citizen Science and the Remote Sensing of Land Cover. In: Reference Module in Earth Systems and Environmental Sciences. Elsevier. 10.1016/B978-0-443-13220-9.00002-0.

McCallum, I. , Walker, J., Fritz, S. , Grau, M., Hannan, C., Hsieh, I-S., Lape, D., Mahone, J., McLester, C., Mellgren, S., Piland, N., See, L. , Svolba, G., & de Villiers, M. (2023). Crowd-Driven Deep Learning Tracks Amazon Deforestation. Remote Sensing 15 (21) e5204. 10.3390/rs15215204.