Latin hypercube sampling in natural resources using R

In sampling strategies numerous goals like prediction in time and space is greate of importance. A great number of limitations include time and cost and in access sources make sampling to important for all experts. Hence, sampling optimization is seeking with every expert. Latin Hypercube Sampling (LHS) is a stratified random procedure that provides an efficient way of sampling variables from their multivariate distributions. It provides a full coverage of the range of each variable by maximally stratifying the marginal distribution. This paper presents the conditioned Latin hypercube as a sampling strategy of an area with prior information (profile and plan curvature) as exhaustive ancillary data of soil erodibility. in. For this, paired- sub-catchments as area of interest was chosen in Golestan province. For both sub-catchments, 60 samples were chosen using sequential- based method. Average of spatial distances for LHS for Testifire and Sample sub-catchments is 639,693, meter in turn.