Pragmatic soil survey design using flexible Latin hypercube sampling

Can citizen science assist digital soil mapping?

“…In DSM approaches sampling is statistically-based, e.g., using conditional Latin hypercube sampling based on environmental covariates (Minasny and McBratney, 2006;Mulder et al, 2013;Clifford et al, 2014). In both approaches spatial inference requires observations to be of sufficient number and collectively representative of the area to be mapped.…”

Digital soil assessment for regional agricultural land evaluation

“…To maximise the value of the additional sites, and to sample the landscape in an efficient and unbiased way, we used the flexible Latin hypercube sampling technique described by Clifford et al (2014). This method restricted the sites to locations o1 km from public roads and tracks, but each site was placed within a particular target 'covariate space' using the set of DSM environmental covariates (see Section 2.4).…”

Optimising sampling designs for the maximum coverage problem of plume detection

“…For example Grafström and Tillé (2013) intended better coverage, be it according to a co-variable or in space, and suggested several algorithms (local pivotal method, cube method, spread and balanced sampling) to obtain such samples. For similar purposes Latin hypercube sampling has been proposed, among others by Clifford et al (2014) who proposed a modification that allows alternative sampling locations that are easier to access. Also Haq et al (2013) proposed to balance samples by the rank of known properties to obtain better coverage of the parameter space.…”