Menguasai Ilmu Gambut, Menjaga Negeri | Chronicles #42

Understanding scientific approaches to predicting and preventing tropical peatland fires with Dr. Adilan Mahdiyasa. Recorded as part of the National Seminar "Understanding and Preventing Tropical Peat Fires Scientifically" and Training on the Use of Tropical Peat Fire Prediction and Mapping Tools (Peatfr), which brings together research and practice through a collaboration between the University of Nottingham, Bandung Institute of Technology, and IPB University. Dr. Adilan Mahdiyasa is a researcher working in the fields of mathematical modeling, statistics, machine learning, and environmental systems, with a focus on developing computational approaches to understanding the dynamics and risks of tropical peat fires. This research is part of an effort to connect science, technology, and decision-making needs in forest and land fire prevention. Full topic: OPENING 0:00:00 - Intro 0:00:56 - Peat, Burn or Burn? 00:02:37 - Understanding and Predicting Peat 00:10:22 - Science and Local Wisdom DISCUSSION AND PRACTICE 00:18:39 - Peatlands in Indonesia 00:21:59 - Software for Predicting Peatland Fires 00:26:21 - Imputation Method 00:28:58 - Time Series Analysis 00:30:40 - Peatland Fire Risk Index 00:36:15 - Using Peatfr Software 00:40:26 - Practical Use of Peatfr Software Q&A & RESPONSES 01:06:09 - Predicting Dry Peat 01:18:06 - Field Peat Measurement 01:25:43 - Future Agenda for Peatfr Software 01:31:31 - Things that can be done Predicted 01:34:35 - Philosophy and Cultural Customs #chronicles #bagusmuljadi #kebakarangambut ------------------- Other Chronicles episodes you might like: Apakah Keyakinan Bisa Dihitung? - Adilan M... Indonesia Gagap Mitigasi Bencana? - Harkun... 4 Kitab Sunda Kuno: Gerbang ke Peradaban P... ------------------- Notes and references from the Chronicles conversation: Mahdiyasa, A. W., Large, D. J., Muljadi, B. P., Icardi, M. & Triantafyllou, S. (2022). MPeat: A fully coupled mechanical-ecohydrological model of peatland development. Ecohydrology, 15(1), e2361. https://doi.org/10.1002/eco.2361 Mahdiyasa, A. W., Large, D. J., Muljadi, B. P. & Icardi, M. (2023). Modeling the influence of mechanical-ecohydrological feedback on the nonlinear dynamics of peatlands. Ecological Modelling, 478, 110299. https://doi.org/10.1016/j.ecolmodel.2... Mahdiyasa, A. W., Large, D. J., Icardi, M. & Muljadi, B. P. (2024). MPeat2D: A fully coupled mechanical-ecohydrological model of peatland development in two dimensions. Earth Surface Dynamics, 12(4), 929-952. https://doi.org/10.5194/esurf-12-929-... Mahdiyasa, A. W., Melly, M., Pasaribu, U. S., Taufik, M. & Muljadi, B. P. (2025). Peatfr: An R package to forecast tropical peatland fire risk with stochastic, machine learning, and optimization methods. Ecological Informatics, 92, 103532. https://doi.org/10.1016/j.ecoinf.2025... Mahdiyasa, A. W., Large, D. J., Icardi, M., Grebby, S. & Muljadi, B. P. (2026). Mechanical thresholds constrain global peatland carbon accumulation. Scientific Reports. https://doi.org/10.1038/s41598-026-66... Mahdiyasa, A. W., Chaim, J. F., Pasaribu, U. S., Sumarga, E., Muljadi, B. P. & Chrysanti, A. (2026). A Calibrated Spatio-Temporal Machine Learning Model for Tropical Peatland Fire Risk. Natural Hazards Research. https://doi.org/10.1016/j.nhres.2026.... ------------------- For collaboration and cooperation inquiries, contact us here: https://sgpp.me/contactus