What is the accepted level of erroneous decision for the Swiss arable land inventory? Uncertainty perception of digital soil maps.

Abstract

Detailed soil maps are crucial to balance interests of urban planning and soil protection. In Switzerland, high-quality arable land is protected by an inventory and surfaces inside the inventory can only exceptionally be developed. Recently, legal frameworks were modified to require detailed soil maps to change the inventory. So far, conventional soil maps at scale of 1:5'000 – directly linked to a prescribed sampling density – are acknowledged to be sufficiently accurate. As conventional mapping is very time-consuming digital soil mapping is currently considered by regional governments to accelerate data collection.To test digital soil mapping to generate such detailed maps we selected a typical area on the Swiss Plateau of 800 hectares. We sampled 1'120 locations by feature space coverage design. Spatial predictions were computed for soil properties and soil suitability classes were derived. Additional independent validation data was sampled by a stratified random design at 120 locations and used to evaluate overall prediction accuracy. For rootable soil depth, the main soil attribute decisions are based on, model uncertainty was quantified by quantile regression forest.  Various representations of uncertainty at selected point locations and for a map excerpt were prepared. Following one of the recently formulated ten Pedometrics challenges, we evaluated (mis)understanding thereof by in-depth guided expert interviews with six inventory decision makers. Level of acceptable uncertainty for the inventory and whether end users rather trusted certain sampling densities as opposed to statistical accuracy measures was further discussed in the interviews.