Overview | Mathematical modelling | Warning on vignette example | Previous steps | Load inventory, plot coordinates and LiDAR data | Compute AGBD | Spatialize AGBD | Spatialize LiDAR metric | Calibrate model | Predict AGBD map on the LiDAR footprint | Run prediction in parallel | What about validation ?

Overview | Required data | Checking plot's coordinates | Checking the corners of the plot | If we rely on the GPS coordinates of the corners: | If we rely on the shape of the plot measured on the field: | Recovering reference corner coordinates and the associated polygon(s) | Visualising and retrieving projected tree coordinates | Integrating LiDAR data | Checking multiple plots at once | Dividing plots | Summarising metrics at subplot level | Summarising tree metrics | Summarising the AGBD and its uncertainties | Summarising LiDAR metrics | All at once | Customizing the ggplot

General workflow and required data | Wood density | Checking and retrieving tree taxonomy | Getting wood density | Height | Building a local H-D model | Using the continent- or region-specific H–D model (Feldpausch) | Using the generic H–D model based on a bioclimatic predictor (Chave) | Estimate AGB | Propagate AGB errors | Diameter measurement error | Wood density error | Height error | All together and AGB visualisation of plots | Some tricks | Mixing measured and estimated height values | Building bayesian Height-Diameter models | Add your tricks