Inferring weed spatial distribution from multi-type data

► Accurate mapping of weeds in arable fields helps to better understand dynamics of weed population. ► We build a spatial hierarchical Bayesian model to interpolate weed spatial distributions. ► The model includes as input data several types of weed measurements. ► Combining multi-type data leads to more accurate weed mapping.