William Krista Mahendra

• •Implement Machine Learning (ML) and Deep Learning (DL) models through multisource satellite data for land use change anlaysis and deforestation with overall accuracy >90%.

• • Contributed to 12 carbon projects (REDD+ and ARR) in Africa, Latin America and Asia using different standards (i.e., Verra and Planvivo), inclusive of Biomass modelling, spatial analysis and PDD writing.

• •Developed a Kalman filter-based time-series noise- reduction workflow to improve timeseries data quality and transparancy for performance benchmark analysis under VM007.

• •Project Acorn aimed at supporting large-scale CO₂ storage for smallholder agroforestry farmers across Africa, Asia, and Latin America. I contributed on developing the potential of SAR data for above ground biomass mapping by integrating Sentinel-1 and ALOS PALSAR-2 with Random Forest and multiple regression models, achieving an R² value above 0.70.

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A joint research between University of Sydney and Gadjah Mada on analyzing Indonesian tropical peatlands.

• •Monitored land-use/land-cover change over 30-years in four peat hydrological units (>3 million ha) and assessed peat depth using integrated elevation data and field measurements.