DOI: 10.25824/redu/fi7xim
title: Replication data for: Simulated fields exhibiting varying degrees of spatial structure for research in digital soil mapping and precision agriculture

description: This database contains 10,201 spatial observations of five covariates, each simulated through an Unconditional Gaussian Simulation process. The simulation occurred in a spatial scenario with a grid of 105x105m with one value for every meter. The covariates exhibit distinct spatial structures, defined by different values of the nugget effect (c₀), sill (c₁), and range (r). The covariate values depend on the simulation process, with only the semivariogram parameters varying. Each complete dataset is referred to as a scenario, numbered from 1 to 24. The semivariogram parameters (sill and range) for each scenario are: Scenario 1: V1 (c₁ = 0.1, r = 50), V2 (c₁ = 0.2, r = 10), V3 (c₁ = 0.5, r = 30), V4 (c₁ = 0.8, r = 80), V5 (c₁ = 0.001, r = 1). Scenario 2: V1 (c₁ = 0.8, r = 80), V2 (c₁ = 0.2, r = 50), V3 (c₁ = 0.3, r = 30), V4 (c₁ = 0.5, r = 10), V5 (c₁ = 0.001, r = 1). Scenario 3: V1 (c₁ = 0.5, r = 10), V2 (c₁ = 0.8, r = 80), V3 (c₁ = 0.2, r = 50), V4 (c₁ = 0.1, r = 30), V5 (c₁ = 0.001, r = 1). Scenario 4: V1 (c₁ = 0.5, r = 30), V2 (c₁ = 0.2, r = 10), V3 (c₁ = 0.8, r = 50), V4 (c₁ = 0.1, r = 80), V5 (c₁ = 0.001, r = 1). Scenario 5: V1 (c₁ = 0.8, r = 50), V2 (c₁ = 0.5, r = 80), V3 (c₁ = 0.1, r = 30), V4 (c₁ = 0.2, r = 10), V5 (c₁ = 0.001, r = 1). Scenario 6: V1 (c₁ = 0.5, r = 10), V2 (c₁ = 0.8, r = 50), V3 (c₁ = 0.1, r = 80), V4 (c₁ = 0.2, r = 30), V5 (c₁ = 0.001, r = 1). Scenario 7: V1 (c₁ = 0.1, r = 30), V2 (c₁ = 0.5, r = 80), V3 (c₁ = 0.8, r = 50), V4 (c₁ = 0.2, r = 10), V5 (c₁ = 0.001, r = 1). Scenario 8: V1 (c₁ = 0.2, r = 80), V2 (c₁ = 0.1, r = 30), V3 (c₁ = 0.5, r = 50), V4 (c₁ = 0.8, r = 10), V5 (c₁ = 0.001, r = 1). Scenario 9: V1 (c₁ = 0.8, r = 30), V2 (c₁ = 0.1, r = 50), V3 (c₁ = 0.2, r = 80), V4 (c₁ = 0.5, r = 10), V5 (c₁ = 0.001, r = 1). Scenario 10: V1 (c₁ = 0.2, r = 30), V2 (c₁ = 0.1, r = 50), V3 (c₁ = 0.8, r = 10), V4 (c₁ = 0.5, r = 80), V5 (c₁ = 0.001, r = 1). Scenario 11: V1 (c₁ = 0.8, r = 80), V2 (c₁ = 0.1, r = 30), V3 (c₁ = 0.5, r = 10), V4 (c₁ = 0.2, r = 50), V5 (c₁ = 0.001, r = 1). Scenario 12: V1 (c₁ = 0.2, r = 80), V2 (c₁ = 0.5, r = 10), V3 (c₁ = 0.8, r = 50), V4 (c₁ = 0.1, r = 30), V5 (c₁ = 0.001, r = 1). Scenario 13: V1 (c₁ = 0.1, r = 10), V2 (c₁ = 0.5, r = 30), V3 (c₁ = 0.2, r = 80), V4 (c₁ = 0.8, r = 50), V5 (c₁ = 0.001, r = 1). Scenario 14: V1 (c₁ = 0.8, r = 50), V2 (c₁ = 0.2, r = 30), V3 (c₁ = 0.5, r = 10), V4 (c₁ = 0.1, r = 80), V5 (c₁ = 0.001, r = 1). Scenario 15: V1 (c₁ = 0.2, r = 10), V2 (c₁ = 0.5, r = 50), V3 (c₁ = 0.1, r = 30), V4 (c₁ = 0.8, r = 80), V5 (c₁ = 0.001, r = 1). Scenario 16: V1 (c₁ = 0.5, r = 80), V2 (c₁ = 0.2, r = 50), V3 (c₁ = 0.1, r = 10), V4 (c₁ = 0.8, r = 30), V5 (c₁ = 0.001, r = 1). Scenario 17: V1 (c₁ = 0.1, r = 30), V2 (c₁ = 0.8, r = 80), V3 (c₁ = 0.5, r = 10), V4 (c₁ = 0.2, r = 50), V5 (c₁ = 0.001, r = 1). Scenario 18: V1 (c₁ = 0.2, r = 50), V2 (c₁ = 0.8, r = 10), V3 (c₁ = 0.1, r = 80), V4 (c₁ = 0.5, r = 30), V5 (c₁ = 0.001, r = 1). Scenario 19: V1 (c₁ = 0.1, r = 50), V2 (c₁ = 0.2, r = 80), V3 (c₁ = 0.8, r = 10), V4 (c₁ = 0.5, r = 30), V5 (c₁ = 0.001, r = 1). Scenario 20: V1 (c₁ = 0.2, r = 30), V2 (c₁ = 0.8, r = 10), V3 (c₁ = 0.5, r = 80), V4 (c₁ = 0.1, r = 50), V5 (c₁ = 0.001, r = 1). Scenario 21: V1 (c₁ = 0.5, r = 10), V2 (c₁ = 0.1, r = 80), V3 (c₁ = 0.2, r = 30), V4 (c₁ = 0.8, r = 50), V5 (c₁ = 0.001, r = 1). Scenario 22: V1 (c₁ = 0.5, r = 50), V2 (c₁ = 0.1, r = 30), V3 (c₁ = 0.8, r = 80), V4 (c₁ = 0.2, r = 10), V5 (c₁ = 0.001, r = 1). Scenario 23: V1 (c₁ = 0.1, r = 10), V2 (c₁ = 0.8, r = 30), V3 (c₁ = 0.2, r = 50), V4 (c₁ = 0.5, r = 80), V5 (c₁ = 0.001, r = 1). Scenario 24: V1 (c₁ = 0.8, r = 80), V2 (c₁ = 0.5, r = 10), V3 (c₁ = 0.2, r = 30), V4 (c₁ = 0.1, r = 50), V5 (c₁ = 0.001, r = 1).