Items where IIASA Author is "Jo, Hyun-Woo"

Article

Park, E. ORCID: https://orcid.org/0000-0002-0442-7621, Jo, H.-W. ORCID: https://orcid.org/0000-0001-6127-883X, Biging, G.S., Chun, J.A., Jeon, S.W., Son, Y., Kraxner, F. & Lee, W.-K. (2024). Advancement of a diagnostic prediction model for spatiotemporal calibration of earth observation data: a case study on projecting forest net primary production in the mid-latitude region. GIScience & Remote Sensing 61 (1), e2401247. 10.1080/15481603.2024.2401247.

Jo, H.-W. ORCID: https://orcid.org/0000-0001-6127-883X, Krasovskiy, A. ORCID: https://orcid.org/0000-0003-0940-9366, Hong, M., Corning, S. ORCID: https://orcid.org/0009-0001-5277-5380, Kim, W., Kraxner, F. & Lee, W.-K. (2023). Modeling Historical and Future Forest Fires in South Korea: The FLAM Optimization Approach. Remote Sensing 15 (5), e1446. 10.3390/rs15051446.

Monograph

Jo, H.-W. ORCID: https://orcid.org/0000-0001-6127-883X (2022). Optimization of the IIASA’s FLAM model to represent forest fires in South Korea. IIASA YSSP Report. Laxenburg, Austria: IIASA

Conference or Workshop Item

Jo, H.-W. ORCID: https://orcid.org/0000-0001-6127-883X, Corning, S. ORCID: https://orcid.org/0009-0001-5277-5380, Kiparisov, P. ORCID: https://orcid.org/0000-0003-1223-7964, San Pedro, J. ORCID: https://orcid.org/0000-0001-9317-7275, Krasovskiy, A. ORCID: https://orcid.org/0000-0003-0940-9366, Kraxner, F. & Lee, W.-K. (2024). Integrating Human Domain Knowledge into Artificial Intelligence for Hybrid Forest Fire Prediction: Case Studies from South Korea and Italy. DOI:10.5194/egusphere-egu24-12320. In: EGU General Assembly 2024, 14-19 April 2024, Vienna.