Just published in Environmental Modelling & Software this paper where a new spatial model is used to produce yearly growing stock volume (GSV), above-ground biomass (AGB), and carbon stock wall-to-wall estimates for the whole Italy. We tested the model for the period 2005–2018, obtaining a time-series of yearly maps at 23 m spatial resolution. Results were validated against the 2015 Italian NFI reaching an average RMSE% of 19% for aggregated areas. Results were also compared against data reported by the Italian GHG inventory, reaching an RMSE% of 28% and 20% for GSV and carbon stock respectively.
We integrated Landsat based forest disturbance maps, and advanced methods for estimating GSV/AGB and carbon combining multiplatform remotely sensed data with plot based NFI data. A good example to demonstrate that the integration with remote sensing brings NFI data to a potential use in supporting sustainable foresta management and the estimation of Ecosystem Services.
We demonstrated that the modeling approach can be successfully used for setting up a forest monitoring system to meet the interests of governments in inventories of GHG emissions and private entities in carbon offset investments.
Access the paper here: https://doi.org/10.1016/j.envsoft.2022.105580