A comparison of direct and indirect approaches for mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m‾²), covering an area of 122 km², with accompanying maps of estimated error. Although the indirect approach fit the spatial variation better and had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. The optimal approach would depend upon the intended use of the map.
Tag: error propagation
Quantifying uncertainty can be a very useful and often important aspect of evaluating results of calculations, particularly in modelling. The same applies for spatial layer mashups where the grids provide the input variables for equations that are calculated spatially (i.e. raster calculator). This toolbox for ArcGIS uses standard error propagation equations to simultaneously calculate the … Continue reading Error Propagation Toolbox