Ritwika Mukhopadhyay

I am a doctoral student in the Department of Forest Resource Management. The title of my PhD thesis is – ‘Forest Attribute Prediction and Mapping using 3D Remote Sensing Data’ – mainly focusing on modeling of forest attributes in the boreal forest and alpine treeline ecosystem, such as aboveground biomass (AGB), volume and diameter. These variables are estimated at plot, stand, and individual tree level using different sources of 3D remote sensing (RS) data, e.g. (airborne and terrestrial) laser scanning data and space-borne synthetic aperture radar (SAR) data. The work is also focused on accounting for the uncertainties in the estimation of the forest variables within different statistical frameworks, such as model-based inference and hybrid inference, and the impact of spatial auto-correlation on such uncertainty estimates. Lastly, our aim is also to produce precise forecasted maps of forest volume growth using samples of very high-resolution airborne laser scanning data for the years between consecutive national airborne laser scanning campaigns.