2020/12/14 by Johannes Breidenbach, Breidenbach, Johannes, Jānis Ivanovs +9
Environmental Science · Agricultural and Biological Sciences · #Forest Management and Policy #Remote Sensing and LiDAR Applications #Forest Ecology and Biodiversity Studies
paper · pdf · doi:10.48550/arxiv.2012.07921
Policy measures and management decisions aiming at enhancing the role of\nforests in mitigating climate-change require reliable estimates of C-stock\ndynamics in greenhouse gas inventories (GHGIs). Aim of this study was to\nassemble design-based estimators to provide estimates relevant for GHGIs using\nnational forest inventory (NFI) data. We improve basic expansion (BE) estimates\nof living-biomass C-stock loss using field-data only, by leveraging with\nremotely-sensed auxiliary data in model-assisted (MA) estimates. Our case\nstudies from Norway, Sweden, Denmark, and Latvia covered an area of >70 Mha.\nLandsat-based Forest Cover Loss (FCL) and one-time wall-to-wall airborne laser\nscanning (ALS) data served as auxiliary data. ALS provided information on the\nC-stock before a potential disturbance indicated by FCL. The use of FCL in MA\nestimators resulted in considerable efficiency gains which in most cases were\nfurther increased by using ALS in addition. A doubling of efficiency was\npossible for national estimates and even larger efficiencies were observed at\nthe sub-national level. Average annual estimates were considerably more precise\nthan pooled estimates using NFI data from all years at once. The combination of\nremotely-sensed with NFI field data yields reliable estimates which is not\nnecessarily the case when using remotely-sensed data without reference\nobservations.\n