CSU begins machine learning project for efficient earthquake-induced landslide prediction

Caraga State University (CSU) welcomes experts from the Department of Science and Technology (DOST) and the Philippine Institute of Volcanology and Seismology (PHIVOLCS) for the inceptual meeting of the Machine Learning of Physics-Based Earthquake-Induced Landslide Parameters for Efficient Prediction and Warning in the Philippines (ML-PREP) Project at the Caraga Center for Geo-Informatics, Hinang Hall on February 20, 2025.

ML-PREP integrates machine learning, remote sensing, and geophysical modeling to develop data-driven solutions and enhance disaster preparedness and risk reduction.

Jayrold P. Arcede, PhD, opened the meeting with a message delivered via Zoom from Thailand. Engr. Arnaldo C. Gagula then presented the accomplishments and milestones of the project. Johanna Gonzales and Carminda R. Tandelcarmen of DOST-Philippine Council for Industry, Energy and Emerging Technology Research and Development (PCIEERD) also oriented the participants on the program, procedures, requirements, and guidelines for grants-in-aid, financial, and administrative protocols. It also featured an open forum and workshop to enhance the project’s effectiveness.  

Participants included staff, students, and representatives from State Universities and Colleges (SUCs), DOST-PCIEERD, DOST-Caraga with Assistant Regional Director for Field Operations Ricardo Varela, and PHIVOLCS represented by Associate Scientist Arturo S. Daag, and Science Research Specialists Margarita P. Dizon, and Roland Joseph B. De Leon. 

ML-PREP represents a significant advancement in the integration of machine learning technology into scientific research, especially for geospatial research in the country. Through leveraging data-driven methodologies, it will enhance predictive capabilities and help address broader social issues. | via ML-PREP Project