Juan Carlos Laso Bayas profile picture

Juan Carlos Laso Bayas

Research Scholar

Novel Data Ecosystems for Sustainability Research Group

Advancing Systems Analysis Program

Biography

Juan Carlos Laso Bayas joined IIASA in September 2015 as a research scholar. He currently works with the Novel Data Ecosystems for Sustainability (NODES) Research Group of the IIASA Advancing Systems Analysis (ASA) Program. His scientific interests include the use of geographic information systems (GIS) and spatial statistics, more specifically mixed models, to analyze remote sensing and citizen science data, aiming to contribute to agricultural production, food security, disaster management, and community resilience. He has led several projects funded by the European Union, the European Space Agency, the Austrian Research Promotion Agency, and others.

He obtained his BSc in Agricultural Sciences at Zamorano University, Honduras, specializing in Socioeconomic Development and Environment. He continued his studies in Germany where he obtained his MSc in Agricultural Sciences in the Tropics and Subtropics as well as his PhD in Agricultural Sciences at the University of Hohenheim, Stuttgart. For his dissertation, he studied the mega-tsunami event of December 2004 and combined remote sensing, GIS, and generalized linear mixed models to relate land use, distance to the sea, and topography to tsunami casualties and damage in West-Aceh, Indonesia, and the Seychelles.

His previous work experience includes: Advanced tropical agriculture and forestry field work at Zamorano; field technician at a joint USAID-Zamorano rehabilitation project after hurricane Mitch (1998) in south Honduras; student counselor at Zamorano; research assistant for the Illinois Natural History Survey at the University of Illinois Urbana-Champaign; technical assistant for the Illinois Crop Improvement Association, Champaign, USA; and researcher in cooperation with the World Agroforestry Centre (ICRAF-SEA), at Bogor, Indonesia.

Before joining IIASA, he worked as a statistical consultant for the Biostatistics Institute, at the University of Hohenheim, Stuttgart.


Last update: 23 MAR 2023

Publications

Fonte, C. C., See, L. , Laso Bayas, J.-C. , Lesiv, M. , & Fritz, S. (2020). Assessing the accuracy of land use land cover (lulc) maps using class proportions in the reference data. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. pp. 669-674 Nice, France: ISPRS Congress on Technical Commission III. 10.5194/isprs-Annals-V-3-2020-669-2020.

Laso Bayas, J.C. , See, L. , Sturn, T., Karner, M., Fraisl, D. , Moorthy, I., Subash, A., Georgieva, I. , Hager, G. , Lesiv, M. , Hadi, H., Danylo, O., Karanam, S., Dürauer, M., Dahlia, D., Shchepashchenko, D. , McCallum, I. , & Fritz, S. (2020). Monitoring of land use change by citizens: The FotoQuest experience. DOI:10.5194/egusphere-egu2020-7870. In: European Geosciences Union (EGU) General Assembly 2020, 4-8 May 2020, Vienna, Austria.

Elmes, A., Alemohammad, H., Avery, R., Caylor, K., Eastman, J.R., Fishgold, L., Friedl, M.A., Jain, M., Kohli, D., Laso Bayas, J.C. , Lunga, D., McCarty, J.L., Pontius, R.G., Reinmann, A.B., Rogan, J., Song, L., Stoynova, H., Ye, S., Yi, Z.-F., & Estes, L. (2020). Accounting for Training Data Error in Machine Learning Applied to Earth Observations. Remote Sensing 12 (6) e1034. 10.3390/rs12061034.